WO2022174756A1 - 一种车辆定位的方法、相关装置、设备以及存储介质 - Google Patents

一种车辆定位的方法、相关装置、设备以及存储介质 Download PDF

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Publication number
WO2022174756A1
WO2022174756A1 PCT/CN2022/076131 CN2022076131W WO2022174756A1 WO 2022174756 A1 WO2022174756 A1 WO 2022174756A1 CN 2022076131 W CN2022076131 W CN 2022076131W WO 2022174756 A1 WO2022174756 A1 WO 2022174756A1
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Prior art keywords
moment
target vehicle
satellite
vehicle
matrix
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PCT/CN2022/076131
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English (en)
French (fr)
Inventor
苏景岚
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腾讯科技（深圳）有限公司
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Priority to EP22755529.9A priority Critical patent/EP4206743A1/en
Publication of WO2022174756A1 publication Critical patent/WO2022174756A1/zh
Priority to US17/988,009 priority patent/US20230072669A1/en

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    • G—PHYSICS
    • G01—MEASURING; TESTING
    • G01S—RADIO DIRECTION-FINDING; RADIO NAVIGATION; DETERMINING DISTANCE OR VELOCITY BY USE OF RADIO WAVES; LOCATING OR PRESENCE-DETECTING BY USE OF THE REFLECTION OR RERADIATION OF RADIO WAVES; ANALOGOUS ARRANGEMENTS USING OTHER WAVES
    • G01S19/00—Satellite radio beacon positioning systems; Determining position, velocity or attitude using signals transmitted by such systems
    • G01S19/38—Determining a navigation solution using signals transmitted by a satellite radio beacon positioning system
    • G01S19/39—Determining a navigation solution using signals transmitted by a satellite radio beacon positioning system the satellite radio beacon positioning system transmitting time-stamped messages, e.g. GPS [Global Positioning System], GLONASS [Global Orbiting Navigation Satellite System] or GALILEO
    • G01S19/396—Determining accuracy or reliability of position or pseudorange measurements
    • G—PHYSICS
    • G01—MEASURING; TESTING
    • G01S—RADIO DIRECTION-FINDING; RADIO NAVIGATION; DETERMINING DISTANCE OR VELOCITY BY USE OF RADIO WAVES; LOCATING OR PRESENCE-DETECTING BY USE OF THE REFLECTION OR RERADIATION OF RADIO WAVES; ANALOGOUS ARRANGEMENTS USING OTHER WAVES
    • G01S5/00—Position-fixing by co-ordinating two or more direction or position line determinations; Position-fixing by co-ordinating two or more distance determinations
    • G01S5/01—Determining conditions which influence positioning, e.g. radio environment, state of motion or energy consumption
    • G01S5/017—Detecting state or type of motion
    • G—PHYSICS
    • G01—MEASURING; TESTING
    • G01S—RADIO DIRECTION-FINDING; RADIO NAVIGATION; DETERMINING DISTANCE OR VELOCITY BY USE OF RADIO WAVES; LOCATING OR PRESENCE-DETECTING BY USE OF THE REFLECTION OR RERADIATION OF RADIO WAVES; ANALOGOUS ARRANGEMENTS USING OTHER WAVES
    • G01S19/00—Satellite radio beacon positioning systems; Determining position, velocity or attitude using signals transmitted by such systems
    • G01S19/01—Satellite radio beacon positioning systems transmitting time-stamped messages, e.g. GPS [Global Positioning System], GLONASS [Global Orbiting Navigation Satellite System] or GALILEO
    • G01S19/03—Cooperating elements; Interaction or communication between different cooperating elements or between cooperating elements and receivers
    • G01S19/05—Cooperating elements; Interaction or communication between different cooperating elements or between cooperating elements and receivers providing aiding data
    • G—PHYSICS
    • G01—MEASURING; TESTING
    • G01S—RADIO DIRECTION-FINDING; RADIO NAVIGATION; DETERMINING DISTANCE OR VELOCITY BY USE OF RADIO WAVES; LOCATING OR PRESENCE-DETECTING BY USE OF THE REFLECTION OR RERADIATION OF RADIO WAVES; ANALOGOUS ARRANGEMENTS USING OTHER WAVES
    • G01S19/00—Satellite radio beacon positioning systems; Determining position, velocity or attitude using signals transmitted by such systems
    • G01S19/01—Satellite radio beacon positioning systems transmitting time-stamped messages, e.g. GPS [Global Positioning System], GLONASS [Global Orbiting Navigation Satellite System] or GALILEO
    • G01S19/13—Receivers
    • G01S19/24—Acquisition or tracking or demodulation of signals transmitted by the system
    • G01S19/25—Acquisition or tracking or demodulation of signals transmitted by the system involving aiding data received from a cooperating element, e.g. assisted GPS
    • G01S19/254—Acquisition or tracking or demodulation of signals transmitted by the system involving aiding data received from a cooperating element, e.g. assisted GPS relating to Doppler shift of satellite signals
    • G—PHYSICS
    • G01—MEASURING; TESTING
    • G01S—RADIO DIRECTION-FINDING; RADIO NAVIGATION; DETERMINING DISTANCE OR VELOCITY BY USE OF RADIO WAVES; LOCATING OR PRESENCE-DETECTING BY USE OF THE REFLECTION OR RERADIATION OF RADIO WAVES; ANALOGOUS ARRANGEMENTS USING OTHER WAVES
    • G01S19/00—Satellite radio beacon positioning systems; Determining position, velocity or attitude using signals transmitted by such systems
    • G01S19/01—Satellite radio beacon positioning systems transmitting time-stamped messages, e.g. GPS [Global Positioning System], GLONASS [Global Orbiting Navigation Satellite System] or GALILEO
    • G01S19/13—Receivers
    • G01S19/24—Acquisition or tracking or demodulation of signals transmitted by the system
    • G01S19/25—Acquisition or tracking or demodulation of signals transmitted by the system involving aiding data received from a cooperating element, e.g. assisted GPS
    • G01S19/258—Acquisition or tracking or demodulation of signals transmitted by the system involving aiding data received from a cooperating element, e.g. assisted GPS relating to the satellite constellation, e.g. almanac, ephemeris data, lists of satellites in view
    • G—PHYSICS
    • G01—MEASURING; TESTING
    • G01S—RADIO DIRECTION-FINDING; RADIO NAVIGATION; DETERMINING DISTANCE OR VELOCITY BY USE OF RADIO WAVES; LOCATING OR PRESENCE-DETECTING BY USE OF THE REFLECTION OR RERADIATION OF RADIO WAVES; ANALOGOUS ARRANGEMENTS USING OTHER WAVES
    • G01S19/00—Satellite radio beacon positioning systems; Determining position, velocity or attitude using signals transmitted by such systems
    • G01S19/38—Determining a navigation solution using signals transmitted by a satellite radio beacon positioning system
    • G01S19/39—Determining a navigation solution using signals transmitted by a satellite radio beacon positioning system the satellite radio beacon positioning system transmitting time-stamped messages, e.g. GPS [Global Positioning System], GLONASS [Global Orbiting Navigation Satellite System] or GALILEO
    • G01S19/393—Trajectory determination or predictive tracking, e.g. Kalman filtering
    • G—PHYSICS
    • G01—MEASURING; TESTING
    • G01S—RADIO DIRECTION-FINDING; RADIO NAVIGATION; DETERMINING DISTANCE OR VELOCITY BY USE OF RADIO WAVES; LOCATING OR PRESENCE-DETECTING BY USE OF THE REFLECTION OR RERADIATION OF RADIO WAVES; ANALOGOUS ARRANGEMENTS USING OTHER WAVES
    • G01S19/00—Satellite radio beacon positioning systems; Determining position, velocity or attitude using signals transmitted by such systems
    • G01S19/38—Determining a navigation solution using signals transmitted by a satellite radio beacon positioning system
    • G01S19/39—Determining a navigation solution using signals transmitted by a satellite radio beacon positioning system the satellite radio beacon positioning system transmitting time-stamped messages, e.g. GPS [Global Positioning System], GLONASS [Global Orbiting Navigation Satellite System] or GALILEO
    • G01S19/40—Correcting position, velocity or attitude
    • G—PHYSICS
    • G01—MEASURING; TESTING
    • G01S—RADIO DIRECTION-FINDING; RADIO NAVIGATION; DETERMINING DISTANCE OR VELOCITY BY USE OF RADIO WAVES; LOCATING OR PRESENCE-DETECTING BY USE OF THE REFLECTION OR RERADIATION OF RADIO WAVES; ANALOGOUS ARRANGEMENTS USING OTHER WAVES
    • G01S19/00—Satellite radio beacon positioning systems; Determining position, velocity or attitude using signals transmitted by such systems
    • G01S19/38—Determining a navigation solution using signals transmitted by a satellite radio beacon positioning system
    • G01S19/39—Determining a navigation solution using signals transmitted by a satellite radio beacon positioning system the satellite radio beacon positioning system transmitting time-stamped messages, e.g. GPS [Global Positioning System], GLONASS [Global Orbiting Navigation Satellite System] or GALILEO
    • G01S19/40—Correcting position, velocity or attitude
    • G01S19/41—Differential correction, e.g. DGPS [differential GPS]
    • G—PHYSICS
    • G01—MEASURING; TESTING
    • G01S—RADIO DIRECTION-FINDING; RADIO NAVIGATION; DETERMINING DISTANCE OR VELOCITY BY USE OF RADIO WAVES; LOCATING OR PRESENCE-DETECTING BY USE OF THE REFLECTION OR RERADIATION OF RADIO WAVES; ANALOGOUS ARRANGEMENTS USING OTHER WAVES
    • G01S19/00—Satellite radio beacon positioning systems; Determining position, velocity or attitude using signals transmitted by such systems
    • G01S19/38—Determining a navigation solution using signals transmitted by a satellite radio beacon positioning system
    • G01S19/39—Determining a navigation solution using signals transmitted by a satellite radio beacon positioning system the satellite radio beacon positioning system transmitting time-stamped messages, e.g. GPS [Global Positioning System], GLONASS [Global Orbiting Navigation Satellite System] or GALILEO
    • G01S19/42—Determining position
    • G—PHYSICS
    • G01—MEASURING; TESTING
    • G01S—RADIO DIRECTION-FINDING; RADIO NAVIGATION; DETERMINING DISTANCE OR VELOCITY BY USE OF RADIO WAVES; LOCATING OR PRESENCE-DETECTING BY USE OF THE REFLECTION OR RERADIATION OF RADIO WAVES; ANALOGOUS ARRANGEMENTS USING OTHER WAVES
    • G01S19/00—Satellite radio beacon positioning systems; Determining position, velocity or attitude using signals transmitted by such systems
    • G01S19/38—Determining a navigation solution using signals transmitted by a satellite radio beacon positioning system
    • G01S19/39—Determining a navigation solution using signals transmitted by a satellite radio beacon positioning system the satellite radio beacon positioning system transmitting time-stamped messages, e.g. GPS [Global Positioning System], GLONASS [Global Orbiting Navigation Satellite System] or GALILEO
    • G01S19/42—Determining position
    • G01S19/45—Determining position by combining measurements of signals from the satellite radio beacon positioning system with a supplementary measurement

Definitions

  • the present application relates to the technical field of positioning and navigation, and in particular, to vehicle positioning.
  • the related art provides a method for suppressing the data drift of the vehicle-mounted positioning device, which determines whether to discard the positioning data obtained by the vehicle-mounted positioning device according to whether the on-board positioning device is turned on or the cold start time reaches a set value, and when the vehicle is driving, Determine whether to discard the positioning data acquired by the vehicle-mounted positioning device according to the speed of the vehicle.
  • the above method utilizes global positioning system (GPS) positioning to determine the stationary or moving state of the vehicle.
  • GPS global positioning system
  • Embodiments of the present application provide a vehicle positioning method, related apparatus, equipment, and storage medium.
  • Pseudorange observations and Doppler observations determined based on satellite ephemeris have high reliability.
  • Auxiliary satellite positioning with Doppler observations can enhance the accuracy of satellite positioning in weak satellite signal scenarios, thereby improving the accuracy of vehicle positioning information.
  • one aspect of the present application provides a method for vehicle positioning, including:
  • satellite filtering parameters and data to be processed wherein the satellite filtering parameters include clock bias and the rate of change of the clock bias, and the satellite filtering parameters also include at least one item of position information and speed information corresponding to the target vehicle at the first moment, and are to be processed
  • the data includes at least one of a pseudorange observation value and a Doppler observation value corresponding to the target vehicle at the first moment;
  • a constraint matrix corresponding to the motion state is obtained, wherein the constraint matrix represents the variation of the positioning information satisfied in the motion state;
  • the positioning information at the first moment is updated by using the second parameter correction amount to obtain the positioning information of the target vehicle at the second moment.
  • a vehicle positioning device comprising:
  • the acquisition module is used to acquire satellite filtering parameters and data to be processed, wherein the satellite filtering parameters include clock deviation and the rate of change of the clock deviation, and the satellite filtering parameters also include at least the position information and speed information corresponding to the target vehicle at the first moment.
  • the data to be processed includes at least one of a pseudorange observation value and a Doppler observation value corresponding to the target vehicle at the first moment;
  • a determining module configured to determine the first parameter correction amount corresponding to the target vehicle at the first moment according to the satellite filtering parameters and the data to be processed;
  • an update module used for updating the satellite filtering parameters by using the first parameter correction amount to obtain the positioning information of the target vehicle at the first moment
  • the acquiring module is further configured to acquire the motion state of the target vehicle at a second moment, wherein the second moment is a moment after the first moment;
  • the acquiring module is further configured to acquire a constraint matrix corresponding to the motion state if the motion state of the target vehicle at the second moment satisfies the positioning correction condition, wherein the constraint matrix represents the variation of the positioning information satisfied in the motion state;
  • a determination module configured to determine the second parameter correction amount corresponding to the target vehicle at the second moment according to the constraint matrix corresponding to the motion state
  • the updating module is used for updating the positioning information at the first moment by using the second parameter correction amount to obtain the positioning information of the target vehicle at the second moment.
  • a terminal device including: a memory, a processor, and a bus system;
  • the memory is used to store programs
  • the processor is configured to execute the program in the memory, and the processor is configured to execute the methods of the above aspects according to instructions in the program code;
  • the bus system is used to connect the memory and the processor so that the memory and the processor communicate.
  • Another aspect of the present application provides a computer-readable storage medium, in which instructions are stored, which, when executed on a computer, cause the computer to perform the methods of the above aspects.
  • Another aspect of the present application provides a computer program product or computer program, the computer program product or computer program comprising computer instructions stored in a computer-readable storage medium.
  • a processor of the computer device reads the computer instructions from the computer-readable storage medium, and the processor executes the computer instructions to cause the computer device to perform the methods of the above-described aspects.
  • the embodiments of the present application have the following advantages:
  • a method for vehicle positioning is provided.
  • the satellite filtering parameters include a clock deviation and a rate of change of the clock deviation, and the satellite filtering parameters also include the target vehicle at the first moment.
  • At least one of the corresponding position information and speed information the data to be processed includes at least one of the pseudorange observation value and the Doppler observation value corresponding to the target vehicle at the first moment, and then according to the satellite filtering parameters and the data to be processed,
  • the first parameter correction amount corresponding to the target vehicle at the first moment is determined, and based on this, the satellite filtering parameter can be updated by using the first parameter correction amount to obtain the positioning information of the target vehicle at the first moment.
  • the pseudorange observation value and the Doppler observation value can be used to correct the vehicle's positioning information, and the pseudorange observation value determined based on the satellite ephemeris and the Doppler observation value can be used to correct the positioning information. Therefore, using pseudorange observations and Doppler observations to assist satellite positioning can strengthen the reliability of satellite positioning in weak satellite signal scenarios, thereby improving the accuracy of vehicle positioning information. Further, constraints are constructed based on the vehicle motion state, which can better improve the positioning accuracy.
  • FIG. 1 is a schematic structural diagram of a vehicle positioning system in an embodiment of the application
  • FIG. 2 is a schematic diagram of an interaction flow of a vehicle positioning method in an embodiment of the present application
  • FIG. 3 is a schematic diagram of an embodiment of a vehicle positioning method in an embodiment of the present application.
  • FIG. 4 is a schematic flowchart of a vehicle positioning method in an embodiment of the present application
  • FIG. 5 is a schematic structural diagram of a vehicle-mounted positioning system in an embodiment of the application.
  • FIG. 6 is a schematic diagram of obtaining satellite filtering parameters in the embodiment of the application.
  • FIG. 7 is a schematic diagram of obtaining data to be processed in an embodiment of the present application.
  • FIG. 8 is a schematic diagram of determining the motion state of a vehicle based on a vehicle-mounted image in an embodiment of the application
  • FIG. 9 is another schematic diagram of determining the motion state of the vehicle based on the vehicle-mounted image in the embodiment of the application.
  • FIG. 10 is a schematic diagram of determining the motion state of a vehicle based on steering wheel position information in an embodiment of the application
  • FIG. 11 is another schematic diagram of determining the motion state of a vehicle based on steering wheel position information in an embodiment of the application;
  • FIG. 12 is a schematic diagram of an embodiment of a vehicle positioning device in an embodiment of the application.
  • FIG. 13 is a schematic structural diagram of a terminal device in an embodiment of the present application.
  • Embodiments of the present application provide a vehicle positioning method, related apparatus, equipment, and storage medium.
  • Pseudorange observations and Doppler observations determined based on satellite ephemeris have high reliability.
  • Auxiliary satellite positioning with Doppler observations can strengthen the reliability of satellite positioning in weak satellite signal scenarios, thereby improving the accuracy of vehicle positioning information.
  • GNSS Global Navigation Satellite System
  • the positioning coordinates of the terminal device are prone to change, sometimes with large changes, and may even display errors. This phenomenon is the so-called "positioning drift". In places with dense tall buildings or bad weather conditions, signal errors and positioning drift may occur due to multiple reflections and reflections of signals. If the situation of positioning drift cannot be well solved, the promotion and use of positioning applications will be limited to a certain extent.
  • an embodiment of the present application provides a vehicle positioning method, which is applied to the vehicle positioning system shown in FIG. 1 .
  • the vehicle positioning system includes continuous operation.
  • Reference station Continuous Operating Reference Stations, CORS
  • CORS Continuous Operating Reference Stations
  • the service server may be a navigation service server
  • the client may be a navigation application.
  • the business server involved in this application may be an independent physical server, or a server cluster or distributed system composed of multiple physical servers, or may provide cloud services, cloud databases, cloud computing, cloud functions, cloud storage, and network services.
  • the terminal device may be a vehicle terminal, a smart phone, a tablet computer, a notebook computer, a palmtop computer, a personal computer, a smart TV, a smart watch, etc., but is not limited thereto.
  • the terminal device and the server can be directly or indirectly connected through wired or wireless communication, which is not limited in this application.
  • the number of servers and terminal devices is also not limited.
  • the CORS server consists of four parts, namely the reference station part, the data center part, the data communication part and the user application part.
  • the parts form a private network that is distributed throughout the city.
  • the reference station section consists of evenly distributed base stations within the control area.
  • the base station is composed of GNSS, computer, meteorological equipment, communication equipment, power supply equipment and observation site. It has the ability to continuously track and record satellite signals for a long time. It is the data source of CORS. Recording and transmission, and equipment integrity monitoring, etc.
  • GNSS is a space-based radio navigation and positioning system that can provide users with all-weather three-dimensional coordinates, speed and time information at any location on the earth's surface or near-Earth space.
  • the data center part consists of computers, networks and software systems.
  • the data center part includes the system control center and the user data center.
  • the system control center is the nerve center of CORS, which can continuously perform overall modeling and calculation in the region according to the real-time observation data collected by each reference station 24 hours a day.
  • Existing data communication network and wireless data broadcasting network provide all kinds of users who need measurement and navigation with code phase and carrier phase difference correction information in an international format, so as to calculate the precise point position of the rover in real time.
  • the user data center provides the downlink of the CORS service, and transmits the data results of the control center to the user.
  • the data communication part consists of a public or dedicated communication network, including data transmission hardware equipment and software control modules.
  • the main function of the data communication part is to transmit the GNSS observation data of the base station to the system control center, and to transmit the system differential information to the users.
  • the user application part is composed of receiver, demodulator of wireless communication and related equipment.
  • the main function of the user application part is to perform different precision positioning according to user needs.
  • FIG. 2 is a schematic diagram of an interaction flow of the vehicle positioning method in the embodiment of the present application. As shown in the figure, specifically :
  • step S1 the vehicle-mounted terminal sends an ephemeris issuing request to the CORS server.
  • step S2 the CORS server sends broadcast ephemeris information to the vehicle terminal, that is, the vehicle terminal receives the satellite real-time navigation ephemeris broadcast by the CORS base station server.
  • step S3 the vehicle-mounted terminal obtains the pseudorange observation value and the Doppler observation value through the satellite positioning device.
  • step S4 the vehicle-mounted terminal updates the positioning information of the vehicle by using at least one of the pseudorange observation value and the Doppler observation value, wherein the positioning information includes the position and speed of the vehicle.
  • step S5 the vehicle-mounted terminal determines that the vehicle is in a stationary state or a linear motion state according to information such as the vehicle steering wheel, odometer, camera, or road network matching.
  • step S6 when the vehicle is in a stationary or linear motion state, the vehicle-mounted terminal constructs a vehicle motion state constraint.
  • step S7 the vehicle-mounted terminal uses the vehicle motion state constraints to assist satellite positioning.
  • step S8 the vehicle-mounted terminal updates the positioning information of the vehicle.
  • the vehicle positioning method of the present application can realize automatic driving or assisted driving in combination with automatic driving technology.
  • Automatic driving technology usually includes technologies such as high-precision map, environment perception, behavioral decision-making, path planning, and motion control.
  • Self-driving technology has a wide range of technologies. application prospects.
  • Autonomous driving technology is a branch of artificial intelligence (Artificial Intelligence, AI) technology, in which AI is the use of digital computers or machines controlled by digital computers to simulate, extend and expand human intelligence, perceive the environment, acquire knowledge and use knowledge to obtain the most Theories, methods, techniques and applied systems for optimal results.
  • AI is a comprehensive technique of computer science that attempts to understand the essence of intelligence and produce a new kind of intelligent machine that can respond in a similar way to human intelligence.
  • AI is the study of the design principles and implementation methods of various intelligent machines, so that the machines have the functions of perception, reasoning and decision-making.
  • AI technology is a comprehensive discipline involving a wide range of fields, including both hardware-level technologies and software-level technologies.
  • AI basic technologies generally include technologies such as sensors, dedicated AI chips, cloud computing, distributed storage, big data processing technology, operation/interaction systems, and mechatronics.
  • AI software technology mainly includes computer vision technology, speech processing technology, natural language processing technology, and machine learning/deep learning.
  • An embodiment of the vehicle positioning method in the embodiment of the present application includes:
  • the terminal device obtains satellite filtering parameters and data to be processed, wherein the satellite filtering parameters include a clock deviation and a rate of change of the clock deviation, and the satellite filtering parameters also include at least one of the position information and speed information corresponding to the target vehicle at the first moment.
  • the data to be processed includes at least one of a pseudorange observation value and a Doppler observation value corresponding to the target vehicle at the first moment;
  • the terminal device acquires the satellite filtering parameters at the first moment, and the satellite filtering parameters include the clock deviation and the rate of change of the clock deviation corresponding to the first moment. At least one item of position information and speed information corresponding to the target vehicle at the first moment is included.
  • the first time represents the current time
  • the target vehicle represents the vehicle to be located.
  • the clock deviation represents the difference between the time indicated by the clock and the standard time of the system under a certain time system. For example, the difference between the GPS receiver's clock reading and the GPS standard time at a certain moment.
  • the rate of change of the clock bias represents the change in the clock bias of the satellite positioning device.
  • the terminal device acquires data to be processed at the first moment, and the data to be processed includes at least one of a pseudorange observation value and a Doppler observation value corresponding to the target vehicle at the first moment.
  • the pseudorange observation value represents the difference between the local receiving moment of the signal and the characterization time value carried by the signal.
  • Doppler observations represent the average velocity during two adjacent observation intervals.
  • FIG. 5 is a schematic diagram of the structure of the vehicle-mounted positioning system in the embodiment of the present application.
  • the vehicle positioning system includes satellite systems, connecting lines, satellite positioning equipment and terminal equipment.
  • satellite systems include but are not limited to GPS in the United States, BeiDou Navigation Satellite System (BDS) in China, and Globo in Russia. Nas (GLONASS) and Europe's Galileo (GALILEO) four major satellite navigation systems.
  • GLONASS BeiDou Navigation Satellite System
  • GALILEO Galileo
  • Satellite navigation systems have been widely used in aviation, navigation, communications, personnel tracking, consumer entertainment, surveying and mapping, timing, vehicle monitoring and management, and car navigation and information services, and the general development trend is to provide high-precision services for real-time applications.
  • the satellite positioning device used in the present application may be a consumer-grade satellite positioning device, and the consumer-grade satellite positioning device is used to provide data to be processed for a terminal device.
  • the terminal device can be a vehicle-mounted terminal or a computer.
  • the connecting line may be a Universal Serial Bus (Universal Serial Bus, USB) or a High Definition Multimedia Interface (High Definition Multimedia Interface, HDMI) connecting line, and the connecting line is mainly used to connect satellite positioning equipment and terminal equipment.
  • the terminal device involved in this application may be a vehicle-mounted terminal, a smart phone, or other types of computers, which are not limited here.
  • the terminal device determines, according to the satellite filtering parameters and the data to be processed, a first parameter correction amount corresponding to the target vehicle at the first moment;
  • the terminal device calculates and obtains the first parameter correction amount of the target vehicle at the first moment according to the satellite filtering parameters corresponding to the first moment and the data to be processed.
  • the terminal device uses the first parameter correction to update the satellite filtering parameters to obtain the positioning information of the target vehicle at the first moment;
  • the terminal device uses the first parameter correction to update the satellite filtering parameters, that is, the terminal device can obtain the positioning information of the target vehicle at the first moment after adding the first parameter correction and the satellite filtering parameters.
  • the satellite filtering parameters include location information
  • the positioning information includes updated location information.
  • the satellite filtering parameters include velocity information
  • the positioning information includes updated velocity information.
  • the satellite filtering parameters include velocity information and position information
  • the positioning information includes updated velocity information and updated position information.
  • the terminal device acquires the motion state of the target vehicle at a second moment, where the second moment is a moment after the first moment;
  • the terminal device may further update the positioning information of the target vehicle based on the motion state of the target vehicle, where the positioning information mainly includes position information and speed information.
  • the terminal device acquires a constraint matrix corresponding to the motion state, where the constraint matrix represents the amount of variation of the positioning information satisfied in the motion state;
  • the terminal device needs to determine whether the motion state of the target vehicle at the second moment satisfies the positioning correction condition, and if so, continues to acquire the constraint matrix corresponding to the motion state. Conversely, if it is not satisfied, the positioning information at the first moment can be determined as the positioning information at the second moment, or, based on the Doppler observation value and the pseudorange observation value at the second moment, the positioning information at the second moment can be recalculated. .
  • the terminal device determines the second parameter correction amount corresponding to the target vehicle at the second moment according to the constraint matrix corresponding to the motion state;
  • the terminal device calculates and obtains the second parameter correction amount based on the constraint matrix in the stationary state, or calculates and obtains the second parameter correction amount based on the constraint matrix in the straight state.
  • the terminal device uses the second parameter correction to update the positioning information at the first moment to obtain the positioning information of the target vehicle at the second moment.
  • the terminal device uses the second parameter correction amount to update the positioning information at the first moment to obtain the positioning information of the target vehicle at the second moment.
  • FIG. 4 is a schematic flowchart of the vehicle positioning method in the embodiment of the application, as shown in the figure, specifically:
  • a terminal device eg, a vehicle-mounted terminal sets satellite filtering parameters and performs initialization processing on the satellite filtering parameters.
  • step 202 the terminal device (for example, a vehicle-mounted terminal) determines whether to receive the data to be processed output by the satellite positioning device. If the data to be processed output by the satellite positioning device is received, step 204 is executed. For the data to be processed output by the positioning device, step 203 is executed.
  • the terminal device advances and updates the filter time, for example, advancing time t to time t+1.
  • step 204 when the terminal device (for example, a vehicle-mounted terminal) receives the data to be processed output by the satellite positioning device, it updates the positioning information of the target vehicle based on the pseudorange observation value and the Doppler observation value, where the positioning information includes the position At least one of information and speed information.
  • the terminal device for example, a vehicle-mounted terminal
  • the terminal device determines the motion state of the target vehicle according to the steering wheel, odometer, camera or road network matching result of the target vehicle.
  • step 206 if the target vehicle is in a stationary state, the terminal device (eg, a vehicle-mounted terminal) constructs a constraint matrix in the stationary state, and updates the position information and speed information of the vehicle based on the constraint matrix in the stationary state.
  • the terminal device eg, a vehicle-mounted terminal
  • step 207 if the target vehicle is in a straight driving state, the terminal device (eg, a vehicle-mounted terminal) constructs a constraint matrix in the straight driving state, and updates the position information and speed information of the vehicle based on the constraint matrix in the straight driving state.
  • the terminal device eg, a vehicle-mounted terminal
  • a method for vehicle positioning is provided.
  • the pseudorange observation value and the Doppler observation value can be used to correct the vehicle's positioning information, and the pseudorange observation value determined based on the satellite ephemeris and the Doppler observation value can be used to correct the positioning information. Therefore, using pseudorange observations and Doppler observations to assist satellite positioning can strengthen the reliability of satellite positioning in weak satellite signal scenarios, thereby improving the accuracy of vehicle positioning information. Further, constraints are constructed based on the vehicle motion state, which can better improve the positioning accuracy.
  • the terminal device acquires satellite filtering parameters and data to be processed, which may specifically include:
  • the terminal device sends an ephemeris issue request to the server, so that the server responds to the ephemeris issue request to obtain broadcast ephemeris information corresponding to the first moment, wherein the broadcast ephemeris information includes ephemeris parameters corresponding to N satellites , N is an integer greater than or equal to 1;
  • the terminal device receives the broadcast ephemeris information corresponding to the first moment sent by the server;
  • the terminal device determines the satellite filtering parameter corresponding to the first moment according to the broadcast ephemeris information corresponding to the first moment;
  • the to-be-processed data corresponding to the first moment is acquired through a satellite positioning device.
  • a method for acquiring satellite filtering parameters is introduced.
  • the terminal device can obtain satellite positions and satellite filtering parameters before updating the vehicle positioning information with pseudorange observations and Doppler observations.
  • the terminal device sends an ephemeris sending request to the CORS server to receive broadcast ephemeris information sent by the CORS server.
  • the broadcast ephemeris information refers to the broadcast ephemeris information corresponding to the first moment.
  • the broadcast ephemeris information mainly includes a header file and satellite-related parameters, and the header file includes some basic information of the file, such as ionospheric parameters, data types , the time increment caused by jumping seconds, and the almanac parameters used to calculate the Universal Time Coordinated (UTC) time.
  • UTC Universal Time Coordinated
  • Satellite-related parameters include pseudorandom noise code (PRN), clock time, satellite clock error, orbit eccentricity, and ephemeris reference time. Based on this, the terminal device may also calculate the satellite position corresponding to each satellite at the first moment according to the broadcast ephemeris information corresponding to the first moment.
  • PRN pseudorandom noise code
  • FIG. 6 is a schematic diagram of obtaining satellite filtering parameters in the embodiment of the present application, as shown in the figure, specifically:
  • step A1 the terminal device sends an ephemeris sending request to the CORS server through the 4th generation mobile communication technology (4G) network or WIFI network, and the ephemeris sending request can carry the first moment the corresponding time stamp.
  • 4G 4th generation mobile communication technology
  • WIFI WIFI
  • the CORS server may issue a request based on the ephemeris, and send real-time broadcast ephemeris information to the terminal device through a 4G network or a WIFI network. , or in the form of data packets.
  • the broadcast ephemeris information includes ephemeris parameter tables of different satellites, and each ephemeris parameter table can be represented as a set of ephemeris parameters used to calculate satellite positions, that is, the broadcast ephemeris information includes the ephemeris corresponding to N satellites parameter.
  • the terminal device uses the satellite information processing unit to calculate N satellite positions and satellite filtering parameters at the first moment (ie the current moment) according to the broadcast ephemeris information, wherein the first moment can be obtained by the terminal device (for example, the vehicle The system time of the terminal) or the timescale of the pseudorange observations are obtained.
  • the satellite information processing unit may be built in the terminal device, and may also be externally placed in the terminal device, which is not limited here.
  • the terminal device Before updating the vehicle positioning information by using the pseudorange observation value and the Doppler observation value, the terminal device may obtain the data to be processed, that is, obtain at least one of the pseudorange observation value and the Doppler observation value.
  • FIG. 7 is a schematic diagram of obtaining data to be processed in an embodiment of the present application.
  • a terminal device for example, a vehicle-mounted terminal
  • uses a connection cable for example, a USB or HDMI) Connecting line
  • a connection cable for example, a USB or HDMI
  • Satellite positioning equipment is used to track and process satellite signals, and to measure the geometric distance between the terminal device and the satellite (i.e. pseudorange observations) and the Doppler effect of satellite signals (i.e. Doppler observations) .
  • Satellite positioning equipment usually includes modules such as antennas, satellite signal tracking loops, and baseband signal processing.
  • Terminal equipment integrated with satellite positioning equipment calculates the current position coordinates of the terminal equipment based on pseudorange observations and Doppler observations. Satellite positioning equipment is widely used in map navigation, surveying and mapping, aerospace and location services, such as smartphone map navigation, high-precision geodetic surveying, and civil aviation.
  • the vehicle-mounted terminal is mainly composed of three parts, including the vehicle-mounted (GPS and/or Beidou) monitoring terminal, the communication network and the dispatch monitoring center.
  • Beidou) terminal or (GPS and/or Beidou) monitoring terminal which is responsible for calculating the positioning coordinates according to the received GPS and/or Beidou satellite signals, and at the same time, sending positioning information, status information and sending and receiving control information through the communication network.
  • the communication network is the carrier that realizes the information exchange between the vehicle and the dispatching monitoring center, generally referring to the Global System for Mobile Communications (GSM), the General Packet Radio Service (GPRS), the Code Division Multiple Access (Code Division Multiple Access) Division Multiple Access, CDMA) base station and Internet (Internet), the dispatch monitoring center is the communication core of the entire information system, responsible for information exchange with the vehicle GPS monitoring terminal, classification, recording and forwarding of various content and control information.
  • GSM Global System for Mobile Communications
  • GPRS General Packet Radio Service
  • CDMA Code Division Multiple Access
  • Internet Internet
  • the CORS server can deliver real-time broadcast ephemeris information to the terminal device, so that the terminal device can determine the current broadcast ephemeris information according to the broadcast ephemeris information.
  • the position of each satellite at time Since the broadcast ephemeris information has high real-time performance, the calculated satellite positions are also more accurate. Accurate pseudorange observations and Doppler observations can be captured by satellite positioning equipment, thereby improving the feasibility and operability of the scheme.
  • the satellite filtering parameter includes the position information corresponding to the target vehicle at the first moment
  • the data to be processed includes Pseudo-range observations corresponding to the target vehicle at the first moment
  • the terminal device determines the first parameter correction amount corresponding to the target vehicle at the first moment according to the satellite filtering parameters and the data to be processed, which may specifically include:
  • the terminal device obtains the covariance matrix corresponding to the first moment
  • the terminal device obtains the first Jacobian matrix corresponding to the N unit observation vectors, wherein each unit observation vector included in the N unit observation vectors represents the direction vector of the connection line between the satellite and the target vehicle;
  • the terminal device obtains the pseudorange measurement error matrix corresponding to the first moment
  • the terminal device obtains the first gain matrix corresponding to the first moment
  • the terminal device determines the first prediction residual vector according to the satellite filtering parameter and the pseudorange observation value corresponding to the first moment;
  • the terminal device determines the first parameter corresponding to the target vehicle at the first moment according to the covariance matrix, the first Jacobian matrix, the pseudorange measurement error matrix, the first gain matrix and the first prediction residual vector corresponding to the first moment Correction amount.
  • a method for determining the first parameter correction amount based on the pseudorange observation value is introduced.
  • the position information, velocity information, clock bias, and rate of change of the clock bias are set as satellite filtering parameters, and the satellite filtering parameters are expressed as:
  • X [x y z v x v y v z dt GPS dt GLO dt GAL dt BDS dtr] T ;
  • X represents the satellite filtering parameters
  • x represents the x-axis coordinate of the vehicle
  • y represents the y-axis coordinate of the vehicle
  • z represents the y-axis coordinate of the vehicle
  • v x represents the speed of the vehicle in the x-axis direction
  • v y represents the vehicle in the y-axis direction.
  • v z is the speed of the vehicle in the z-axis direction
  • dt GPS is the clock deviation of the satellite positioning device clock relative to GPS
  • dt GLO is the clock deviation of the satellite positioning device clock relative to GLONASS
  • dt BDS is the satellite positioning device clock.
  • dt BDS is the clock deviation of the satellite positioning device clock relative to the Beidou system
  • dtr is the rate of change of the clock deviation of the satellite positioning device.
  • the initial position information can be given by the network positioning result or the output result of the satellite positioning device, and the initial speed information can be given by the speed output by the satellite positioning device or set to zero.
  • the clock offset dt GPS , the clock offset dt GLO , the clock offset dt GAL and the clock offset dt BDS of the satellite positioning device are all set to 0, and the clock offset change rate dtr of the satellite positioning device is set to zero.
  • the initialized satellite filtering parameters are expressed as:
  • X(t 0 ) [x 0 y 0 z 0 v x0 v y0 v z0 0 0 0 0] T ;
  • X(t 0 ) represents the initialized satellite filtering parameters
  • x 0 represents the initial x-axis coordinate of the vehicle
  • y 0 represents the initial y-axis coordinate of the vehicle
  • z 0 represents the initial z-axis coordinate of the vehicle
  • v x0 represents the vehicle at x
  • v y0 represents the initial speed of the vehicle in the y-axis direction
  • v z0 represents the initial speed of the vehicle in the z-axis direction.
  • a filtered covariance matrix can also be set, and the covariance matrix is initialized to obtain the following form:
  • P(t 0 ) represents the initialized covariance matrix
  • diag(10 6 ,11) represents an 11-dimensional diagonal matrix whose diagonal element values are all 10 6 .
  • the filtering parameter at time t k is X(t k )
  • the filtering parameter t k+1 at the next time is:
  • X(t k+1 ) represents the satellite filtering parameter corresponding to the first moment
  • X(t k ) represents the satellite filtering parameter corresponding to the moment before the first moment
  • F represents the state transition matrix of the system.
  • P(t k+1 ) represents the covariance matrix corresponding to the first moment
  • P(t k ) represents the covariance matrix corresponding to the previous moment
  • F represents the state transition matrix of the system
  • Q(t k +1 ) represents the system noise matrix corresponding to the first moment
  • the system noise matrix corresponding to the first moment is expressed as:
  • S x represents the density spectrum of the acceleration in the x-axis direction
  • S y represents the density spectrum of the acceleration in the y-axis direction
  • S z represents the density spectrum of the acceleration in the z-axis direction
  • S f represents the frequency drift spectral density of the satellite positioning device clock frequency
  • S g represents the spectral density of the clock phase drift of the satellite positioning device relative to the previous moment.
  • the terminal device receives N satellites fed back by the satellite positioning device.
  • the pseudorange observations of the signal including m Beidou satellites, n GPS satellites, p GLONASS satellites and q GALILEO satellites, the pseudorange observations are:
  • ⁇ BDS,1 represents the pseudorange observation value of the first Beidou satellite
  • ⁇ BDS,m represents the pseudorange observation value of the mth Beidou satellite
  • ⁇ GPS,1 represents the pseudorange observation value of the first GPS satellite
  • ⁇ GPS,n denotes the pseudorange observation value of the nth GPS satellite
  • ⁇ GLO,1 the pseudorange observation value of the first GLONASS satellite
  • ⁇ GLO,p denotes the pseudorange observation value of the pth GLONASS satellite
  • ⁇ GAL, 1 The pseudorange observations of the first GALILEO satellite, ⁇ GAL,q represents the pseudorange observations of the qth GLONASS satellite.
  • n, p and q may be integers greater than or equal to 0, and the sum of m+n+p+q is equal to N, where N is an integer greater than or equal to 1.
  • the terminal device determines the first prediction residual vector according to the satellite filtering parameters and the pseudorange observation value corresponding to the first moment, that is, calculates the first prediction residual vector in the following manner:
  • ⁇ z represents the first prediction residual vector
  • t k+1 represents the first moment
  • r(t k+1 ) represents the location information of the target vehicle at the first moment (the location information is derived from the satellite filtering parameters)
  • r i represents the satellite position of the ith satellite (for example, r GPS,1 represents the satellite position of the 1st GPS satellite, r GPS,n represents the satellite position of the nth GPS satellite)
  • c represents the vacuum value of light speed value
  • dt i represents For the clock deviation of the i-th satellite, the above parameters can be calculated from the satellite real-time navigation ephemeris, that is, calculated from the broadcast ephemeris information at the first moment.
  • the terminal device can determine, according to the covariance matrix, the first Jacobian matrix, the pseudorange measurement error matrix, the first gain matrix, and the first prediction residual vector corresponding to the first moment, the target vehicle corresponding to the first moment
  • the first parameter correction amount of that is, the calculation method of the first parameter correction amount is:
  • ⁇ X(t k+1 ) represents the first parameter correction amount corresponding to the target vehicle at the first moment
  • P(t k+1 ) represents the covariance matrix corresponding to the first moment
  • H represents the first Jacobian matrix
  • R ⁇ (t k+1 ) represents the pseudorange measurement error matrix corresponding to the first moment (which can be directly obtained by the satellite positioning device)
  • ⁇ z represents the first prediction residual vector
  • K(t k+1 ) represents the first The first gain matrix corresponding to a moment.
  • the first Jacobian matrix is determined based on N unit observation vectors, each unit observation vector is used to represent the direction vector of the connection between the satellite and the target vehicle, and the first Jacobian matrix is calculated as follows:
  • H represents the first Jacobian matrix
  • e i represents the unit observation vector from the ith satellite to the target vehicle, which is the direction vector of the line connecting the two spatial points of the satellite and the terminal device
  • ⁇ ⁇ i represents the variance of the measurement noise value
  • CN0 represents the carrier-to-noise ratio of the ith satellite
  • r(t k+1 ) represents the position information of the target vehicle at the first moment
  • x(t k+1 ) represents the x-axis coordinate of the target vehicle at the first moment
  • y(t k+1 ) represents the y-axis coordinate of the target vehicle at the first moment
  • z(t k+1 ) represents the z-axis coordinate of the target vehicle at the first moment.
  • the calculation method of e i is as follows:
  • ri represents the satellite position of the ith satellite
  • r(t k+1 ) represents the position information of the target vehicle at the first moment.
  • the speed information in the satellite filtering parameters may be set to 0.
  • X(t k+1 ) represents the satellite filtering parameter
  • ⁇ X(t k+1 ) represents the first parameter correction amount corresponding to the target vehicle at the first moment.
  • the covariance matrix of the filtering parameters can be updated as follows:
  • I 11 ⁇ 11 represents the 11 ⁇ 11 matrix
  • H represents the first Jacobian matrix
  • P(t k+1 ) represents the covariance matrix at the first moment
  • K(t k +1 ) represents the first gain matrix corresponding to the first moment.
  • the parameter correction amount (eg, the first parameter correction amount) is used to correct the position information and speed information of the target vehicle, and the covariance matrix represents the accuracy of the position information and speed information of the target vehicle.
  • a method for determining a first parameter correction amount based on a pseudorange observation value is provided.
  • the satellite filtering parameter is corrected by using the pseudorange observation value, and the pseudorange determined based on the satellite ephemeris is used.
  • Observation values have high reliability. Therefore, satellite positioning assistance can enhance the reliability of satellite positioning in weak satellite signal scenarios, thereby improving the accuracy of vehicle positioning information.
  • the satellite filtering parameter includes speed information corresponding to the target vehicle at the first moment
  • the data to be processed includes Doppler observations corresponding to the target vehicle at the first moment
  • the terminal device determines the first parameter correction amount corresponding to the target vehicle at the first moment according to the satellite filtering parameters and the data to be processed, which may specifically include:
  • the terminal device obtains the covariance matrix corresponding to the first moment
  • the terminal device acquires the second Jacobian matrix corresponding to the N unit observation vectors, wherein each unit observation vector included in the N unit observation vectors represents the direction vector of the connection line between the satellite and the target vehicle;
  • the terminal device obtains the Doppler measurement error matrix corresponding to the first moment
  • the terminal device obtains the second gain matrix corresponding to the first moment
  • the terminal device determines the second prediction residual vector according to the satellite filtering parameter and the Doppler observation value corresponding to the first moment;
  • the terminal device determines the first time corresponding to the target vehicle at the first time according to the covariance matrix, the second Jacobian matrix, the Doppler measurement error matrix, the second gain matrix and the second prediction residual vector corresponding to the first time. parameter correction.
  • a method for determining the correction amount of the first parameter based on the Doppler observation value is introduced. Similar to the previous embodiment, when constructing a position and velocity filter of a terminal device (for example, an in-vehicle terminal), the position information, velocity information, clock bias, and clock bias change rate are set as satellite filtering parameters, and the satellite filtering parameters need to be determined.
  • the initial position information can be given by the network positioning result or the output result of the satellite positioning device, and the initial speed information can be given by the speed output by the satellite positioning device or set to zero.
  • the filtering parameter at time t k is X(t k )
  • the filtering parameter t k+1 at the next time is:
  • X(t k+1 ) represents the satellite filtering parameter corresponding to the first moment
  • X(t k ) represents the satellite filtering parameter corresponding to the previous moment
  • F represents the state transition matrix of the system.
  • P(t k+1 ) represents the covariance matrix corresponding to the first moment
  • P(t k ) represents the covariance matrix corresponding to the previous moment
  • F represents the state transition matrix of the system
  • Q(t k +1 ) represents the system noise matrix corresponding to the first moment.
  • the terminal device receives N feedbacks from the satellite positioning device.
  • Doppler observations of satellite signals the pseudorange observations are expressed as
  • the terminal device determines the second prediction residual vector according to the satellite filtering parameters and the Doppler observation value corresponding to the first moment, that is, calculates the second prediction residual vector in the following way:
  • r GPS,1 is the satellite position of the 1st GPS satellite
  • r GPS,n is the satellite position of the nth GPS satellite
  • c is the vacuum value of the speed of light value
  • dtr is the clock of the satellite positioning device deviation rate
  • the above parameters can be calculated by satellite real-time navigation ephemeris, that is, calculated from the broadcast ephemeris information at the first moment.
  • the terminal device can determine, according to the covariance matrix, the second Jacobian matrix, the Doppler measurement error matrix, the second gain matrix and the second prediction residual vector corresponding to the first moment, the The corresponding first parameter correction amount, that is, the calculation method of the first parameter correction amount is:
  • the second Jacobian matrix is determined based on N unit observation vectors, each unit observation vector is used to represent the direction vector of the connection between the satellite and the target vehicle, and the second Jacobian matrix is calculated as follows:
  • M represents the second Jacobian matrix
  • e i represents the unit observation vector from the ith satellite to the target vehicle, which is the direction vector of the line connecting the two space points of the satellite and the terminal device, represents the variance value of the measurement noise
  • CN0 represents the carrier-to-noise ratio of the ith satellite
  • v(t k+1 ) represents the speed information of the target vehicle at the first moment
  • v x (t k+1 ) represents the target vehicle in the ith satellite Speed information in the x-axis direction at a moment
  • v y (t k+1 ) represents the speed information of the target vehicle in the y-axis direction at the first moment
  • v z (t k+1 ) represents the target vehicle in the z-direction at the first moment speed information on .
  • the calculation method of e i is as follows:
  • ri represents the satellite position of the ith satellite
  • r(t k+1 ) represents the position information of the target vehicle at the first moment.
  • the position information in the satellite filtering parameter may be set to 0. It can be understood that m, n, p and q may be integers greater than or equal to 0, and the sum of m+n+p+q is equal to N, where N is an integer greater than or equal to 1.
  • X(t k+1 ) represents the satellite filtering parameter
  • the covariance matrix of the filtering parameters can be updated as follows:
  • I 11 ⁇ 11 represents the 11 ⁇ 11 matrix
  • M represents the second Jacobian matrix
  • P(t k+1 ) represents the covariance matrix at the first moment
  • the parameter correction amount (eg, the first parameter correction amount) is used to correct the position information and speed information of the target vehicle, and the covariance matrix represents the accuracy of the position information and speed information of the target vehicle.
  • a method for determining the correction amount of the first parameter based on the Doppler observation value is provided.
  • the Doppler observation value is used to correct the satellite filtering parameters, and the determined value based on the satellite ephemeris is determined.
  • Doppler observations have high reliability. Therefore, satellite positioning assistance can enhance the reliability of satellite positioning in weak satellite signal scenarios, thereby improving the accuracy of vehicle positioning information.
  • the satellite filtering parameters include speed information and position information corresponding to the target vehicle at the first moment, and the parameters to be The processed data includes pseudorange observations and Doppler observations corresponding to the target vehicle at the first moment;
  • the terminal device determines the first parameter correction amount corresponding to the target vehicle at the first moment according to the satellite filtering parameters and the data to be processed, which may specifically include:
  • the terminal device obtains the covariance matrix corresponding to the first moment
  • the terminal device obtains the first Jacobian matrix corresponding to the N unit observation vectors, wherein each unit observation vector included in the N unit observation vectors represents the direction vector of the connection line between the satellite and the target vehicle;
  • the terminal device obtains the pseudorange measurement error matrix corresponding to the first moment
  • the terminal device obtains the first gain matrix corresponding to the first moment
  • the terminal device determines the first prediction residual vector according to the satellite filtering parameter and the pseudorange observation value corresponding to the first moment;
  • the terminal device determines the target parameter correction corresponding to the target vehicle at the first moment according to the covariance matrix, the first Jacobian matrix, the pseudorange measurement error matrix, the first gain matrix and the first prediction residual vector corresponding to the first moment. amount, wherein the target parameter correction amount is used to update the satellite filtering parameters;
  • the terminal device determines the target covariance matrix according to the covariance matrix, the first gain matrix and the first Jacobian matrix corresponding to the first moment;
  • the terminal device determines the first parameter correction amount corresponding to the target vehicle at the first moment according to the target covariance matrix.
  • a method for jointly determining the first parameter correction amount based on the pseudorange observation value and the Doppler observation value is introduced. Similar to the previous embodiment, when constructing a position and velocity filter of a terminal device (for example, an in-vehicle terminal), the position information, velocity information, clock bias, and clock bias change rate are set as satellite filtering parameters, and the satellite filtering parameters need to be determined.
  • the initial position information can be given by the network positioning result or the output result of the satellite positioning device, and the initial speed information can be given by the speed output by the satellite positioning device or set to zero.
  • the filtering parameter at time t k is X(t k )
  • the filtering parameter t k+1 at the next time is:
  • X(t k+1 ) represents the satellite filtering parameter corresponding to the first moment
  • X(t k ) represents the satellite filtering parameter corresponding to the previous moment
  • F represents the state transition matrix of the system.
  • P(t k+1 ) represents the covariance matrix corresponding to the first moment
  • P(t k ) represents the covariance matrix corresponding to the previous moment
  • F represents the state transition matrix of the system
  • Q(t k +1 ) represents the system noise matrix corresponding to the first moment.
  • the terminal device receives N satellites fed back by the satellite positioning device.
  • the pseudorange observations of the signal including m Beidou satellites, n GPS satellites, p GLONASS satellites and q GALILEO satellites, the pseudorange observations are:
  • ⁇ BDS,1 represents the pseudorange observation value of the first Beidou satellite
  • ⁇ BDS,m represents the pseudorange observation value of the mth Beidou satellite
  • ⁇ GPS,1 represents the pseudorange observation value of the first GPS satellite
  • ⁇ GPS,n denotes the pseudorange observation value of the nth GPS satellite
  • ⁇ GLO,1 the pseudorange observation value of the first GLONASS satellite
  • ⁇ GLO,p denotes the pseudorange observation value of the pth GLONASS satellite
  • ⁇ GAL, 1 The pseudorange observations of the first GALILEO satellite, ⁇ GAL,q represents the pseudorange observations of the qth GLONASS satellite.
  • n, p and q may be integers greater than or equal to 0, and the sum of m+n+p+q is equal to N, where N is an integer greater than or equal to 1.
  • the terminal device determines the first prediction residual vector according to the satellite filtering parameters and the pseudorange observation value corresponding to the first moment, that is, calculates the first prediction residual vector in the following manner:
  • ⁇ z represents the first prediction residual vector
  • t k+1 represents the first moment
  • r(t k+1 ) represents the location information of the target vehicle at the first moment (the location information is derived from the satellite filtering parameters)
  • r i represents the satellite position of the ith satellite (for example, r GPS,1 represents the satellite position of the 1st GPS satellite, r GPS,n represents the satellite position of the nth GPS satellite)
  • c represents the vacuum value of light speed value
  • dt i represents For the clock deviation of the i-th satellite, the above parameters can be calculated from the satellite real-time navigation ephemeris, that is, calculated from the broadcast ephemeris information at the first moment.
  • the terminal device can determine, according to the covariance matrix, the first Jacobian matrix, the pseudorange measurement error matrix, the first gain matrix, and the first prediction residual vector corresponding to the first moment, the target vehicle corresponding to the first moment
  • the target parameter correction amount of that is, the calculation method of the target parameter correction amount is:
  • ⁇ X(t k+1 ) represents the target parameter correction amount corresponding to the target vehicle at the first moment
  • P(t k+1 ) represents the covariance matrix corresponding to the first moment
  • H represents the first Jacobian matrix
  • R ⁇ (t k+1 ) represents the pseudorange measurement error matrix corresponding to the first moment (which can be obtained directly from the satellite positioning device)
  • ⁇ z represents the first prediction residual vector
  • K(t k+1 ) represents the first The first gain matrix corresponding to the moment.
  • the first Jacobian matrix is determined based on N unit observation vectors, each unit observation vector is used to represent the direction vector of the connection between the satellite and the target vehicle, and the first Jacobian matrix is calculated as follows:
  • H represents the first Jacobian matrix
  • e i represents the unit observation vector from the ith satellite to the target vehicle, which is the direction vector of the line connecting the two spatial points of the satellite and the terminal device
  • ⁇ ⁇ i represents the variance of the measurement noise value
  • CN0 represents the carrier-to-noise ratio of the ith satellite
  • r(t k+1 ) represents the position information of the target vehicle at the first moment
  • x(t k+1 ) represents the x-axis coordinate of the target vehicle at the first moment
  • y(t k+1 ) represents the y-axis coordinate of the target vehicle at the first moment
  • z(t k+1 ) represents the z-axis coordinate of the target vehicle at the first moment.
  • the calculation method of e i is as follows:
  • ri represents the satellite position of the ith satellite
  • r(t k+1 ) represents the position information of the target vehicle at the first moment.
  • Satellite filter parameters After obtaining the target parameter correction amount ⁇ X(t k+1 ), update the satellite filtering parameter X(t k+1 ) to obtain the updated satellite filtering parameters of the target vehicle at the first moment, that is, obtain the updated satellite filtering parameters in the following manner Satellite filter parameters:
  • X(t k+1 ) represents the satellite filtering parameters
  • ⁇ X(t k+1 ) represents the target parameter correction amount corresponding to the target vehicle at the first moment.
  • the covariance matrix of the filtering parameters can be updated as follows:
  • I 11 ⁇ 11 represents the 11 ⁇ 11 matrix
  • H represents the first Jacobian matrix
  • P(t k+1 ) represents the covariance matrix corresponding to the first moment
  • K (t k+1 ) represents the first gain matrix corresponding to the first moment.
  • the terminal device determines the updated satellite filtering parameters according to the target parameter correction amount and the satellite filtering parameters, and then determines the updated satellite filtering parameters according to the target covariance matrix, the second Jacobian matrix, the Doppler measurement error matrix, the second gain matrix and the second The residual vector is predicted, and the first parameter correction amount corresponding to the target vehicle at the first moment is determined. Finally, the updated satellite filtering parameters are updated using the first parameter correction amount to obtain the positioning information of the target vehicle at the first moment.
  • a method for jointly determining the first parameter correction amount based on the pseudorange observation value and the Doppler observation value is provided.
  • the filtering parameters are corrected, and the pseudorange observations and Doppler observations determined based on the satellite ephemeris have high reliability. Therefore, satellite positioning assistance can enhance the reliability of satellite positioning in weak satellite signal scenarios, thereby improving the vehicle. The accuracy of the positioning information.
  • the terminal device determines, according to the target covariance matrix, the first time corresponding to the target vehicle at the first moment.
  • Parameter correction amount which can include:
  • the terminal device acquires the second Jacobian matrix corresponding to the N unit observation vectors, wherein each unit observation vector included in the N unit observation vectors represents the direction vector of the connection line between the satellite and the target vehicle;
  • the terminal device obtains the Doppler measurement error matrix corresponding to the first moment
  • the terminal device obtains the second gain matrix corresponding to the first moment
  • the terminal device determines the second prediction residual vector according to the satellite filtering parameter and the Doppler observation value corresponding to the first moment;
  • the terminal device determines the first parameter correction amount corresponding to the target vehicle at the first moment according to the target covariance matrix, the second Jacobian matrix, the Doppler measurement error matrix, the second gain matrix and the second prediction residual vector;
  • the terminal device uses the first parameter correction to update the satellite filtering parameters to obtain the positioning information of the target vehicle at the first moment, which may specifically include:
  • the terminal device determines the updated satellite filtering parameters according to the target parameter correction amount and the satellite filtering parameters, wherein the updated satellite filtering parameters include the updated speed information and the updated position information corresponding to the target vehicle at the first moment;
  • the terminal device uses the first parameter correction amount to update the updated satellite filtering parameters to obtain the positioning information of the target vehicle at the first moment.
  • a method of jointly determining the first parameter correction amount based on the pseudorange observation value and the Doppler observation value is introduced. Combined with the above introduction, when calculating the first parameter correction of the target vehicle at the first moment, it is necessary to obtain the Doppler observation value. It is assumed that at the first moment t k+1 , the terminal device receives N feedbacks from the satellite positioning device. Doppler observations of satellite signals, the pseudorange observations are expressed as
  • the terminal device determines the second prediction residual vector according to the satellite filtering parameters and the Doppler observation value corresponding to the first moment, that is, calculates the second prediction residual vector in the following way:
  • r GPS,1 is the satellite position of the 1st GPS satellite
  • r GPS,n is the satellite position of the nth GPS satellite
  • c is the vacuum value of the speed of light value
  • dtr is the clock of the satellite positioning device deviation rate
  • the above parameters can be calculated by satellite real-time navigation ephemeris, that is, calculated from the broadcast ephemeris information at the first moment.
  • the terminal device can determine, according to the covariance matrix, the second Jacobian matrix, the Doppler measurement error matrix, the second gain matrix and the second prediction residual vector corresponding to the first moment, the The corresponding first parameter correction amount, that is, the calculation method of the first parameter correction amount is:
  • M represents the second Jacobian matrix
  • Doppler measurement error matrix corresponding to the first moment (which can be obtained directly from the satellite positioning device)
  • the second prediction residual vector represents the second gain matrix corresponding to the first moment.
  • the second Jacobian matrix is determined based on N unit observation vectors, each unit observation vector is used to represent the direction vector of the connection between the satellite and the target vehicle, and the second Jacobian matrix is calculated as follows:
  • M represents the second Jacobian matrix
  • e i represents the unit observation vector from the ith satellite to the target vehicle, which is the direction vector of the line connecting the two space points of the satellite and the terminal device, represents the variance value of the measurement noise
  • CN0 represents the carrier-to-noise ratio of the ith satellite
  • v(t k+1 ) represents the speed information of the target vehicle at the first moment
  • v x (t k+1 ) represents the target vehicle in the ith satellite Speed information in the x-axis direction at a moment
  • v y (t k+1 ) represents the speed information of the target vehicle in the y-axis direction at the first moment
  • v z (t k+1 ) represents the target vehicle in the z-direction at the first moment speed information on .
  • the calculation method of e i is as follows:
  • ri represents the satellite position of the ith satellite
  • r(t k+1 ) represents the position information of the target vehicle at the first moment.
  • the position information in the satellite filtering parameter may be set to 0. It can be understood that m, n, p and q may be integers greater than or equal to 0, and the sum of m+n+p+q is equal to N, where N is an integer greater than or equal to 1.
  • filter parameters for the updated satellites Update to obtain the positioning information of the target vehicle at the first moment, that is, update the positioning information in the following way:
  • the covariance matrix of the filtering parameters can be updated as follows:
  • I 11 ⁇ 11 represents the 11 ⁇ 11 matrix
  • M represents the second Jacobian matrix
  • the parameter correction amount (eg, the first parameter correction amount) is used to correct the position information and speed information of the target vehicle, and the covariance matrix represents the accuracy of the position information and speed information of the target vehicle.
  • a method for jointly determining the first parameter correction amount based on the pseudorange observation value and the Doppler observation value is provided.
  • the filtering parameters are corrected, and the pseudorange observations and Doppler observations determined based on the satellite ephemeris have high reliability. Therefore, satellite positioning assistance can enhance the reliability of satellite positioning in weak satellite signal scenarios, thereby improving the vehicle. The accuracy of the positioning information.
  • the terminal device uses the second parameter correction amount to update the positioning information at the first moment to obtain the target.
  • the positioning information of the vehicle at the second moment may specifically include:
  • the terminal device uses the second parameter correction amount to update the positioning information at the first moment to obtain the positioning information to be processed;
  • the terminal device determines the first positioning information according to the positioning information at the first moment and the first weight value
  • the terminal device determines the second positioning information according to the positioning information to be processed and the second weight value
  • the terminal device determines the positioning information of the target vehicle at the second moment according to the first positioning information and the second positioning information.
  • a method for updating positioning information is introduced.
  • the terminal device can use the second parameter correction amount to update the positioning information at the first moment. For example, after adding the second parameter correction amount and the positioning information at the first moment, the pending processing of the target vehicle at the second moment can be obtained. location information.
  • the terminal device may also use the first weight value to calculate the positioning information at the first moment. Assuming that the first weight value is 0.1, then the positioning information at the first moment (including speed information and position information) is combined with the first weight. The values are multiplied to obtain the corresponding first positioning information.
  • the terminal device may also use the second weight value to calculate the pending positioning information at the second moment. Assuming that the second weight value is 0.9, then the pending positioning information at the first moment (including speed information and position information) The second weight value is multiplied to obtain the corresponding second positioning information. After adding the first positioning information and the second positioning information, the positioning information of the target vehicle at the second moment is obtained.
  • first weight value and the second weight value can be adjusted according to actual conditions, and this is only an illustration, and should not be construed as a limitation of the present application.
  • a method for updating the positioning information is provided.
  • the positioning information calculated based on the Doppler observation value and the pseudorange observation value and the positioning information calculated based on the constraint matrix are combined according to A certain proportion of the corresponding weight value is allocated to adjust the confidence of the positioning information, thereby improving the reliability of the scheme.
  • the satellite filtering parameter includes position information and speed information corresponding to the target vehicle at the first moment;
  • the terminal device Before the terminal device acquires the motion state of the target vehicle at the second moment, it may further include:
  • the terminal device obtains the position confidence factor and the speed confidence factor corresponding to the satellite filtering parameters, wherein the position confidence factor represents the position accuracy of the target vehicle, and the speed confidence factor represents the speed accuracy of the target vehicle;
  • the terminal device obtains the number of visible satellites
  • the terminal device determines to execute the step of acquiring the motion state of the target vehicle at the second moment.
  • a method for determining whether to execute a positioning constraint based on a position confidence factor, a velocity confidence factor, and the number of visible satellites is introduced.
  • the terminal device may acquire the position information and speed information corresponding to the target vehicle at a certain moment, and further acquire the position confidence factor of the position information and the speed confidence factor of the speed information.
  • the terminal device can detect the number of visible satellites.
  • the position confidence factor and the speed confidence factor can be determined according to the scene. It is assumed that the value range of the position confidence factor and the speed confidence factor is 0 to 1. The larger the value, the higher the confidence.
  • the location confidence factor and speed confidence factor are related to the scene where the target vehicle is located. For example, in lane-level navigation, the location confidence factor and speed confidence factor are both 0.3, and in map navigation, the location confidence factor and speed confidence factor are both 0.5. It should be noted that the above scenario is only an illustration, and in practical applications, the position confidence factor and the velocity confidence factor may also be flexibly defined based on other scenarios.
  • the vehicle constraints are satisfied. Conversely, if the position confidence factor is smaller than the first threshold, or the velocity confidence factor is smaller than the second threshold, or the number of visible satellites is smaller than the third threshold, the vehicle constraint is not satisfied.
  • the first threshold can be set to 0.5
  • the second threshold can be set to 0.6
  • the third threshold can be set to 6, wherein the first threshold, the second threshold and the third threshold can be flexibly set according to the actual situation. It is only an illustration and should not be construed as a limitation to the present application.
  • a method for determining whether to execute the positioning constraint based on the position confidence factor, the speed confidence factor and the number of visible satellites.
  • the above method provides certain restrictions for the positioning constraint, and on the one hand, the positioning can be improved.
  • the accuracy of the constraints on the other hand, for the case where the vehicle constraints are not met, no subsequent calculation is required, thus saving computing resources.
  • the terminal device obtains the motion state of the target vehicle at the second moment, which may specifically include:
  • the terminal device obtains the first vehicle image through the image acquisition device
  • the terminal device acquires the second vehicle-mounted image through the image acquisition device, wherein the second vehicle-mounted image and the first vehicle-mounted image are two adjacent frames of images;
  • the terminal device performs feature point matching on the first vehicle-mounted image and the second vehicle-mounted image
  • the terminal device determines the motion state of the target vehicle at the second moment according to the feature point matching result.
  • the method of judging the driving state of the vehicle based on the vehicle-mounted image is introduced.
  • the terminal device shoots continuous vehicle images through the image acquisition device, and then performs feature point matching on two adjacent frames of vehicle images in the vehicle image, and judges whether the vehicle is stationary or whether the vehicle in linear motion.
  • FIG. 8 is a schematic diagram of determining the motion state of the vehicle based on the vehicle-mounted image in the embodiment of the application.
  • the first vehicle-mounted image has eight Feature points
  • the second on-board image have 8 feature points in the second on-board image. If the 8 feature points in the first on-board image and the 8 feature points in the second on-board image are not offset, If the offset is smaller than a preset value (for example, 10 pixels), the target vehicle is considered to be stationary.
  • a preset value for example, 10 pixels
  • FIG. 9 is another schematic diagram of determining the motion state of the vehicle based on the vehicle-mounted image in the embodiment of the application.
  • (A) of FIG. 9 there are 8 feature points in the first vehicle-mounted image, as shown in FIG. 9 .
  • (B) there are 8 feature points in the second on-board image, if the 8 feature points in the first on-board image and the 8 feature points in the second on-board image are offset, and the offset direction is Convergence or divergence, the target vehicle is considered to be in a state of linear motion.
  • the situation shown in FIG. 9 can be understood as the target vehicle is moving in a straight line.
  • a method for judging the driving state of the vehicle based on the vehicle image is provided.
  • the current driving state of the target vehicle can be determined, which is convenient for subsequent processing, thereby improving the feasibility and operability of the solution.
  • the terminal device obtains the motion state of the target vehicle at the second moment, which may specifically include:
  • the terminal device determines the motion state of the target vehicle at the second moment according to the steering wheel position information corresponding to the target vehicle;
  • the terminal device determines the motion state of the target vehicle at the second moment based on the road network matching result.
  • FIG. 10 is a schematic diagram of determining the motion state of the vehicle based on the steering wheel position information in the embodiment of the application.
  • the steering wheel position information is 0 degrees, if it is deflected, the steering wheel position information is changed according to the angle change, for example, if it is turned 5 degrees to the left, the steering wheel position information is -5 degrees, and for example, if it is turned 5 degrees to the right degrees, the steering wheel position information is 5 degrees.
  • the steering wheel position information is 0 degrees at this time, thereby determining that the target vehicle is in a stationary state or a linear motion state.
  • FIG. 11 is another schematic diagram of determining the motion state of the vehicle based on the steering wheel position information in the embodiment of the present application.
  • the steering wheel position information is: 0 degree.
  • the steering wheel position information is -5 degrees at this time, so it is determined that the target vehicle is in a non-stationary state and is also in a non-linear motion state .
  • road network matching can be understood as map matching.
  • the driving trajectory of the target vehicle is obtained, and then the location of the target vehicle is determined based on Location Based Services (LBS), and then the road network matching result is obtained by matching according to the map data. .
  • LBS Location Based Services
  • LBS is a location-related service provided by wireless operators for users. Based on LBS, it uses various types of positioning technologies to obtain the current location of the positioning device, and provides information resources to the positioning device through the mobile Internet. and basic services.
  • the LBS service integrates various information technologies such as mobile communication, Internet, spatial positioning, location information and big data, and uses the mobile Internet service platform for data update and interaction, so that users can obtain corresponding services through spatial positioning.
  • a method for judging the driving state of the vehicle based on the steering wheel position information and the road network matching result is provided. Through the above method, the current driving state of the target vehicle can be determined, which is convenient for subsequent processing, thereby improving the feasibility of the solution. performance and operability.
  • the terminal device determines that the motion state of the target vehicle at the second moment satisfies the positioning correction condition
  • the terminal device obtains the constraint matrix corresponding to the motion state, which may specifically include:
  • the terminal device constructs the constraint matrix corresponding to the static state
  • the terminal device determines the second parameter correction amount corresponding to the target vehicle at the second moment according to the constraint matrix corresponding to the motion state, which may specifically include:
  • the terminal device obtains the covariance matrix corresponding to the second moment
  • the terminal device obtains the first measurement error variance matrix
  • the terminal device obtains the velocity matrix corresponding to the second moment
  • the terminal device obtains the third gain matrix corresponding to the second moment
  • the terminal device determines the target vehicle at the second time. Corresponding second parameter correction amount.
  • a method for constructing a vehicle stationary state constraint-assisted satellite positioning is introduced. Assuming that the current moment is the second moment, the second moment is represented as t p+1 , and the moment before the second moment is t p . If the target vehicle is in a stationary state during the time interval between time t p and time t p+1 , then the positioning information X(t p+1 ) of the first time corresponding to the second time can be obtained, and The corresponding covariance matrix P(t p+1 ).
  • the second parameter correction amount is calculated in the following manner:
  • ⁇ X 0 (t p+1 ) represents the second parameter correction amount corresponding to the target vehicle at the second moment
  • P(t p+1 ) represents the covariance matrix corresponding to the second moment
  • V represents the static state corresponding to the The constraint matrix of
  • R 0 (t p+1 ) represents the first measurement error variance matrix corresponding to the second moment
  • K 0 (t p+1 ) represents the third gain matrix corresponding to the second moment
  • ⁇ z 0 represents the first The velocity matrix corresponding to the two moments.
  • ⁇ z 0 represents the speed matrix corresponding to the second moment
  • v x (t p+1 ) represents the speed information of the target vehicle in the x-axis direction at the second moment
  • v y (t p+1 ) represents the target vehicle at the th
  • v z (t p+1 ) represents the speed information of the target vehicle in the z-direction at the second time.
  • V represents the constraint matrix corresponding to the static state.
  • the first measurement error variance matrix corresponding to the second moment is specifically expressed as:
  • R 0 (t p+1 ) represents the first measurement error variance matrix corresponding to the second moment.
  • the terminal device uses the second parameter correction to update the positioning information at the first moment, and obtains the positioning information of the target vehicle at the second moment, that is, calculates the positioning information of the target vehicle at the second moment in the following way:
  • X(t p+1 ) represents the positioning information of the target vehicle at the first moment of the second moment
  • ⁇ X 0 (t p+1 ) represents the second parameter correction amount
  • the covariance matrix of the filter parameters can also be updated as follows:
  • I 11 ⁇ 11 represents the 11 ⁇ 11 matrix
  • V represents the constraint matrix corresponding to the static state
  • P(t p+1 ) represents the covariance matrix corresponding to the second moment
  • K 0 (t p+1 ) represents the third gain matrix corresponding to the second moment.
  • a method for constructing a stationary state constraint of the vehicle to assist satellite positioning is provided. Through the above method, constructing a reasonable constraint can improve the positioning accuracy when the vehicle is stationary.
  • the terminal device after the terminal device acquires the motion state of the target vehicle at the second moment, it may further include:
  • the terminal device determines that the motion state of the target vehicle at the second moment satisfies the positioning correction condition
  • the terminal device obtains the constraint matrix corresponding to the motion state, which may specifically include:
  • the terminal device constructs the constraint matrix corresponding to the straight-line driving state
  • the terminal device determines the second parameter correction amount corresponding to the target vehicle at the second moment according to the constraint matrix corresponding to the motion state, which may specifically include:
  • the terminal device obtains the covariance matrix corresponding to the second moment
  • the terminal device obtains the second measurement error variance matrix
  • the terminal device obtains the movement direction difference, wherein the movement direction difference is the difference between the movement direction of the target vehicle at the second moment and the movement direction of the target vehicle at the third moment, where the third moment is before the second moment. a moment;
  • the terminal device obtains the fourth gain matrix corresponding to the second moment
  • the terminal device determines, according to the covariance matrix corresponding to the second time, the constraint matrix corresponding to the straight-line driving state, the second measurement error variance matrix, the movement direction difference, and the fourth gain matrix, the first time corresponding to the target vehicle at the second time. Two parameter corrections.
  • a method for constructing a vehicle linear motion state constraint to assist satellite positioning is introduced. Assuming that the current moment is the second moment, the second moment is represented as t p+1 , and the moment before the second moment is t p . If the target vehicle is in a stationary state during the time interval between time t p and time t p+1 , then the positioning information X(t p+1 ) of the first time corresponding to the second time can be obtained, and The corresponding covariance matrix P(t p+1 ), and at time t p , the speed of the target vehicle is:
  • v(t p ) represents the speed of the target vehicle at time t p
  • v x (t p ) represents the speed information of the target vehicle in the x-axis direction at time t p
  • v y (t p ) represents the speed of the target vehicle at time t p
  • v z (t p ) represents the speed information of the target vehicle in the z-direction at time t p .
  • ⁇ represents the longitude of the terminal device
  • ⁇ represents the latitude of the terminal device
  • v(t p+1 ) represents the speed of the target vehicle at time (t p+1 ) (ie, the second time)
  • v x (t p+1 ) represents the speed of the target vehicle at time (t p +1 ) (ie, the second time).
  • the second time) speed information in the x-axis direction v y (t p+1 ) represents the speed information of the target vehicle in the y-axis direction at (t p+1 ) time (ie, the second time)
  • v z (t p +1 ) represents the speed information of the target vehicle in the z direction at time (t p+1 ) (ie, the second time).
  • ⁇ represents the longitude of the terminal device
  • ⁇ represents the latitude of the terminal device
  • the second parameter correction amount is calculated in the following manner:
  • ⁇ X L (t p+1 ) represents the second parameter correction amount corresponding to the target vehicle at the second moment
  • P(t p+1 ) represents the covariance matrix corresponding to the second moment
  • G represents the straight line driving state.
  • R L (t p+1 ) represents the second measurement error variance matrix corresponding to the second moment
  • K L (t p+1 ) represents the fourth gain matrix corresponding to the second moment
  • ⁇ z L represents Motion direction difference.
  • J vx represents the velocity constraint in the x direction
  • J vy represents the velocity constraint in the y direction
  • J vz represents the velocity constraint in the z direction.
  • the second measurement error variance matrix corresponding to the second moment is specifically expressed as:
  • R L (t p+1 ) represents the second measurement error variance matrix corresponding to the second moment.
  • the terminal device uses the second parameter correction to update the positioning information at the first moment, and obtains the positioning information of the target vehicle at the second moment, that is, calculates the positioning information of the target vehicle at the second moment in the following way:
  • X(t p+1 ) represents the positioning information of the target vehicle at the first moment of the second moment
  • ⁇ XL (t p+1 ) represents the second parameter correction amount
  • the covariance matrix of the filter parameters can also be updated as follows:
  • I 11 ⁇ 11 represents the 11 ⁇ 11 matrix
  • G represents the constraint matrix corresponding to the straight-line driving state
  • P(t p+1 ) represents the covariance matrix corresponding to the second moment
  • KL (t p+1 ) represents the fourth gain matrix corresponding to the second moment.
  • a method for constructing a vehicle linear motion state constraint to assist satellite positioning is provided.
  • constructing a reasonable constraint can improve the positioning accuracy in the case of the vehicle linear motion.
  • FIG. 12 is a schematic diagram of an embodiment of the vehicle positioning device in the embodiment of the application.
  • the vehicle positioning device 30 includes:
  • the acquisition module 301 is used to acquire satellite filtering parameters and data to be processed, wherein the satellite filtering parameters include clock deviation and the rate of change of the clock deviation, and the satellite filtering parameters also include the position information and speed information corresponding to the target vehicle at the first moment
  • the data to be processed includes at least one of a pseudorange observation value and a Doppler observation value corresponding to the target vehicle at the first moment;
  • a determination module 302 configured to determine the first parameter correction amount corresponding to the target vehicle at the first moment according to the satellite filtering parameters and the data to be processed;
  • the updating module 303 is used to update the satellite filtering parameter by adopting the first parameter correction amount to obtain the positioning information of the target vehicle at the first moment;
  • the acquiring module 301 is further configured to acquire the motion state of the target vehicle at a second moment, wherein the second moment is a moment after the first moment;
  • the obtaining module 301 is further configured to obtain a constraint matrix corresponding to the motion state if the motion state of the target vehicle at the second moment satisfies the positioning correction condition, wherein the constraint matrix represents the variation of the positioning information satisfied in the motion state;
  • the determining module 302 is configured to determine the second parameter correction amount corresponding to the target vehicle at the second moment according to the constraint matrix corresponding to the motion state;
  • the updating module 303 is configured to update the positioning information at the first moment by using the second parameter correction amount to obtain the positioning information of the target vehicle at the second moment.
  • the obtaining module 301 is specifically configured to send an ephemeris issuing request to the server, so that the server responds to the ephemeris issuing request and obtains the broadcast ephemeris information corresponding to the first moment, wherein the broadcast ephemeris information includes the information of N satellites.
  • the corresponding ephemeris parameter, N is an integer greater than or equal to 1;
  • the to-be-processed data corresponding to the first moment is acquired through a satellite positioning device.
  • the satellite filtering parameter includes the position information corresponding to the target vehicle at the first moment
  • the data to be processed includes the pseudorange observation value corresponding to the target vehicle at the first moment
  • the determining module 302 is specifically configured to obtain the covariance matrix corresponding to the first moment
  • each unit observation vector included in the N unit observation vectors represents the direction vector of the connection line between the satellite and the target vehicle;
  • the first parameter correction amount corresponding to the target vehicle at the first moment is determined .
  • the satellite filtering parameter includes the speed information corresponding to the target vehicle at the first moment
  • the data to be processed includes the Doppler observation value corresponding to the target vehicle at the first moment
  • the determining module 302 is specifically configured to obtain the covariance matrix corresponding to the first moment
  • each unit observation vector included in the N unit observation vectors represents the direction vector of the connection line between the satellite and the target vehicle;
  • the first parameter correction corresponding to the target vehicle at the first moment is determined quantity.
  • the satellite filtering parameters include speed information corresponding to the target vehicle at the first moment and Position information
  • the data to be processed includes the pseudorange observation value and Doppler observation value corresponding to the target vehicle at the first moment;
  • the determining module 302 is specifically configured to obtain the covariance matrix corresponding to the first moment
  • each unit observation vector included in the N unit observation vectors represents the direction vector of the connection line between the satellite and the target vehicle;
  • the target parameter correction amount corresponding to the target vehicle at the first moment is determined, Among them, the target parameter correction amount is used to update the satellite filtering parameters;
  • the first parameter correction amount corresponding to the target vehicle at the first moment is determined.
  • the determination module 302 is specifically configured to obtain the second Jacobian matrix corresponding to the N unit observation vectors, wherein each unit observation vector included in the N unit observation vectors represents the direction vector of the connection between the satellite and the target vehicle;
  • the target covariance matrix, the second Jacobian matrix, the Doppler measurement error matrix, the second gain matrix and the second prediction residual vector determine the first parameter correction amount corresponding to the target vehicle at the first moment
  • Use the first parameter correction to update the satellite filtering parameters to obtain the positioning information of the target vehicle at the first moment including:
  • the updated satellite filtering parameters include updated speed information and updated position information corresponding to the target vehicle at the first moment;
  • the updated satellite filtering parameters are updated using the first parameter correction amount to obtain the positioning information of the target vehicle at the first moment.
  • the updating module 303 is specifically configured to use the second parameter correction amount to update the positioning information at the first moment to obtain the positioning information to be processed;
  • the positioning information of the target vehicle at the second moment is determined.
  • the satellite filtering parameter includes the position information corresponding to the target vehicle at the first moment and speed information
  • the obtaining module 301 is further configured to obtain the position confidence factor and the speed confidence factor corresponding to the satellite filtering parameters before obtaining the motion state of the target vehicle at the second moment, wherein the position confidence factor represents the position accuracy of the target vehicle, and the speed confidence factor represents The speed accuracy of the target vehicle;
  • the obtaining module 301 is also used to obtain the number of visible satellites
  • the determining module 302 is further configured to determine and execute the step of acquiring the motion state of the target vehicle at the second moment if the position confidence factor, the velocity confidence factor and the number of visible satellites satisfy the vehicle constraint condition.
  • the acquiring module 301 is specifically configured to acquire the first vehicle-mounted image through the image acquisition device;
  • the motion state of the target vehicle at the second moment is determined according to the feature point matching result.
  • the obtaining module 301 is specifically configured to determine the motion state of the target vehicle at the second moment according to the steering wheel position information corresponding to the target vehicle;
  • the motion state of the target vehicle at the second moment is determined based on the road network matching result.
  • the determination module 302 is also used for obtaining the motion state of the target vehicle at the second moment by the acquisition module 301, if the motion state of the target vehicle at the second moment is a stationary state, then determine that the motion state of the target vehicle at the second moment satisfies the positioning correction condition;
  • the acquisition module 301 is specifically used for constructing the constraint matrix corresponding to the static state
  • a determination module 302 specifically configured to obtain the covariance matrix corresponding to the second moment
  • the constraint matrix corresponding to the stationary state determines the target vehicle corresponding to the second time.
  • the second parameter correction amount determines the target vehicle corresponding to the second time.
  • the determination module 302 is also used for obtaining the motion state of the target vehicle at the second moment by the acquisition module 301, if the motion state of the target vehicle at the second moment is a straight-line driving state, then determine that the motion state of the target vehicle at the second moment satisfies the positioning modify the conditions;
  • the obtaining module 301 is specifically configured to construct a constraint matrix corresponding to the straight-line driving state
  • a determination module 302 specifically configured to obtain the covariance matrix corresponding to the second moment
  • the movement direction difference is the difference between the movement direction of the target vehicle at the second moment and the movement direction of the target vehicle at the third moment, where the third moment is the moment before the second moment ;
  • the embodiment of the present application also provides another vehicle positioning device, as shown in FIG. 13 .
  • the terminal device is an on-board terminal as an example for description:
  • FIG. 13 is a block diagram showing a partial structure of a vehicle-mounted terminal related to the terminal device provided by the embodiment of the present application.
  • the in-vehicle terminal includes: a radio frequency (RF) circuit 410, a memory 420, an input unit 430, a display unit 440, a sensor 450, an audio circuit 460, a wireless fidelity (WiFi) module 370, a processor 480, and Power 490 and other components.
  • RF radio frequency
  • the RF circuit 410 can be used for receiving and sending signals during transmission and reception of information or during a call. In particular, after receiving the downlink information of the base station, it is processed by the processor 480; in addition, the designed uplink data is sent to the base station.
  • RF circuitry 410 includes, but is not limited to, an antenna, at least one amplifier, a transceiver, a coupler, a low noise amplifier (LNA), a duplexer, and the like.
  • LNA low noise amplifier
  • RF circuitry 410 may also communicate with networks and other devices via wireless communications. The above wireless communication may use any communication standard or protocol, including but not limited to GSM, GPRS, CDMA, wideband code division multiple access (WCDMA), long term evolution (LTE), email, Short message service (short messaging service, SMS), etc.
  • the memory 420 may be used to store software programs and modules, and the processor 480 executes various functional applications and data processing of the vehicle terminal by running the software programs and modules stored in the memory 420 .
  • the memory 420 may mainly include a storage program area and a storage data area, wherein the storage program area may store an operating system, an application program (such as a sound playback function, an image playback function, etc.) required for at least one function, and the like; Data (such as audio data, phone book, etc.) created by the use of the in-vehicle terminal, etc.
  • memory 420 may include high-speed random access memory, and may also include non-volatile memory, such as at least one magnetic disk storage device, flash memory device, or other volatile solid state storage device.
  • the input unit 430 may be used to receive input numerical or character information, and generate key signal input related to user setting and function control of the vehicle-mounted terminal.
  • the input unit 430 may include a touch panel 431 and other input devices 432.
  • the touch panel 431 also referred to as a touch screen, can collect the user's touch operations on or near it (such as the user's finger, stylus, etc., any suitable object or accessory on or near the touch panel 431). operation), and drive the corresponding connection device according to the preset program.
  • the display unit 440 may be used to display information input by the user or information provided to the user and various menus of the in-vehicle terminal.
  • the display unit 440 may include a display panel 441 .
  • the in-vehicle terminal may also include at least one sensor 450, such as a light sensor, a motion sensor, and other sensors.
  • the light sensors may include ambient light sensors and proximity sensors.
  • the audio circuit 460, the speaker 461, and the microphone 462 can provide an audio interface between the user and the in-vehicle terminal.
  • WiFi is a short-distance wireless transmission technology.
  • the vehicle-mounted terminal can help users to send and receive emails, browse web pages, and access streaming media through the WiFi module 370. It provides users with wireless broadband Internet access.
  • the processor 480 is the control center of the in-vehicle terminal, using various interfaces and lines to connect various parts of the entire in-vehicle terminal, by running or executing the software programs and/or modules stored in the memory 420, and calling the data stored in the memory 420. , perform various functions of the vehicle terminal and process data.
  • the steps performed by the terminal device in the above embodiment may be based on the structure of the terminal device shown in FIG. 13 .
  • Embodiments of the present application also provide a computer-readable storage medium, where a computer program is stored in the computer-readable storage medium, and when it runs on a computer, causes the computer to execute the methods described in the foregoing embodiments.
  • the embodiments of the present application also provide a computer program product including a program, which, when run on a computer, causes the computer to execute the methods described in the foregoing embodiments.
  • the disclosed system, apparatus and method may be implemented in other manners.
  • the apparatus embodiments described above are only illustrative.
  • the division of the units is only a logical function division. In actual implementation, there may be other division methods.
  • multiple units or components may be combined or Can be integrated into another system, or some features can be ignored, or not implemented.
  • the shown or discussed mutual coupling or direct coupling or communication connection may be through some interfaces, indirect coupling or communication connection of devices or units, and may be in electrical, mechanical or other forms.
  • the units described as separate components may or may not be physically separated, and components displayed as units may or may not be physical units, that is, may be located in one place, or may be distributed to multiple network units. Some or all of the units may be selected according to actual needs to achieve the purpose of the solution in this embodiment.
  • each functional unit in each embodiment of the present application may be integrated into one processing unit, or each unit may exist physically alone, or two or more units may be integrated into one unit.
  • the above-mentioned integrated units may be implemented in the form of hardware, or may be implemented in the form of software functional units.
  • the integrated unit if implemented in the form of a software functional unit and sold or used as an independent product, may be stored in a computer-readable storage medium.
  • the technical solutions of the present application can be embodied in the form of software products in essence, or the parts that contribute to the prior art, or all or part of the technical solutions, and the computer software products are stored in a storage medium , including several instructions for causing a computer device (which may be a personal computer, a server, or a network device, etc.) to execute all or part of the steps of the methods described in the various embodiments of the present application.
  • the aforementioned storage medium includes: U disk, mobile hard disk, read-only memory (ROM), random access memory (RAM), magnetic disk or optical disk and other media that can store program codes .

Abstract

提供了一种应用于自动驾驶领域的车辆定位方法、装置、终端设备、计算机可读存储介质以及包括指令的计算机程序产品，其中该方法包括：获取卫星滤波参数及待处理数据（101）；确定第一时刻的第一参数修正量（102）；采用第一参数修正量对卫星滤波参数更新，得到第一时刻的定位信息（103）；获取目标车辆在第二时刻的运动状态（104）；若第二时刻的运动状态满足定位修正条件，则获取运动状态所对应的约束矩阵（105）；根据约束矩阵确定在第二时刻的第二参数修正量（106）；采用第二参数修正量对第一时刻的定位信息更新，得到在第二时刻的定位信息（107）。该方法利用伪距观测值与多普勒观测值对车辆的定位信息进行修正，伪距观测值与多普勒观测值具有较高的可靠性，能够强化弱卫星信号场景下卫星定位的准确性，基于车辆运动状态构建约束，进一步提升定位的准确性。

Description

一种车辆定位的方法、相关装置、设备以及存储介质
本申请要求于2021年02月22日提交中国专利局、申请号为202110196837.8、申请名称为“一种车辆定位的方法、相关装置、设备以及存储介质”的中国专利申请的优先权，其全部内容通过引用结合在本申请中。
技术领域
本申请涉及定位与导航技术领域，尤其涉及车辆定位。
背景技术
随着自动驾驶及辅助驾驶技术的快速发展，定位作为一个自车位姿评估的技术显得尤为重要。在高级辅助驾驶以及自动驾驶系统中，高精度定位确定了车的地理信息位置，是保证高级辅助驾驶乃至自动驾驶安全的关键一环。
目前，相关技术提供一种抑制车载定位装置数据漂移的方法，根据车载定位装置开机或冷启动时间是否达到设定值来决定是否丢弃车载定位装置获取的定位数据，以及，车辆在行驶过程中，根据车辆行驶速度判断是否丢弃车载定位装置获取的定位数据。
上述方法利用全球定位系统(global positioning system，GPS)定位判断车辆静止或运动状态，当车辆处于静止状态时，则根据历史定位数据进行状态约束，否则进行正常定位流程。
发明内容
本申请实施例提供了一种车辆定位的方法、相关装置、设备以及存储介质，基于卫星星历确定的伪距观测值与多普勒观测值具有较高的可靠性，因此，通过伪距观测值与多普勒观测值辅助卫星定位能够强化弱卫星信号场景下卫星定位的准确性，从而提升车辆定位信息的准确度。
有鉴于此，本申请一方面提供一种车辆定位的方法，包括：
获取卫星滤波参数以及待处理数据，其中，卫星滤波参数包括时钟偏差以及时钟偏差变化率，且卫星滤波参数还包括目标车辆在第一时刻所对应的位置信息以及速度信息中至少一项，待处理数据包括目标车辆在第一时刻所对应的伪距观测值以及多普勒观测值中至少一项；
根据卫星滤波参数以及待处理数据，确定目标车辆在第一时刻所对应的第一参数修正量；
采用第一参数修正量对卫星滤波参数进行更新，得到目标车辆在第一时刻的定位信息；
获取目标车辆在第二时刻的运动状态，其中，第二时刻为出现在第一时刻之后的一个时刻；
若目标车辆在第二时刻的运动状态满足定位修正条件，则获取运动状态所对应的约束矩阵，其中，约束矩阵表示在运动状态下满足的定位信息变化量；
根据运动状态所对应的约束矩阵，确定目标车辆在第二时刻所对应的第二参数修正量；
采用第二参数修正量对第一时刻的定位信息进行更新，得到目标车辆在第二时刻的定位信息。
本申请另一方面提供一种车辆定位装置，包括：
获取模块，用于获取卫星滤波参数以及待处理数据，其中，卫星滤波参数包括时钟偏差以及时钟偏差变化率，且卫星滤波参数还包括目标车辆在第一时刻所对应的位置信息以及速度信息中至少一项，待处理数据包括目标车辆在第一时刻所对应的伪距观测值以及多普勒观测值中至少一项；
确定模块，用于根据卫星滤波参数以及待处理数据，确定目标车辆在第一时刻所对应的第一参数修正量；
更新模块，用于采用第一参数修正量对卫星滤波参数进行更新，得到目标车辆在第一时刻的定位信息；
获取模块，还用于获取目标车辆在第二时刻的运动状态，其中，第二时刻为出现在第一时刻之后的一个时刻；
获取模块，还用于若目标车辆在第二时刻的运动状态满足定位修正条件，则获取运动状态所对应的约束矩阵，其中，约束矩阵表示在运动状态下满足的定位信息变化量；
确定模块，用于根据运动状态所对应的约束矩阵，确定目标车辆在第二时刻所对应的第二参数修正量；
更新模块，用于采用第二参数修正量对第一时刻的定位信息进行更新，得到目标车辆在第二时刻的定位信息。
本申请另一方面提供一种终端设备，包括：存储器、处理器以及总线系统；
其中，所述存储器用于存储程序；
所述处理器用于执行所述存储器中的程序，所述处理器用于根据程序代码中的指令执行上述各方面的方法；
所述总线系统用于连接所述存储器以及所述处理器，以使所述存储器以及所述处理器进行通信。
本申请的另一方面提供了一种计算机可读存储介质，计算机可读存储介质中存储有指令，当其在计算机上运行时，使得计算机执行上述各方面的方法。
本申请的另一个方面，提供了一种计算机程序产品或计算机程序，该计算机程序产品或计算机程序包括计算机指令，该计算机指令存储在计算机可读存储介质中。计算机设备的处理器从计算机可读存储介质读取该计算机指令，处理器执行该计算机指令，使得该计算机设备执行上述各方面的方法。
从以上技术方案可以看出，本申请实施例具有以下优点：
本申请实施例中，提供了一种车辆定位的方法，首先获取卫星滤波参数以及待处理数据，卫星滤波参数包括时钟偏差以及时钟偏差变化率，且卫星滤波参数还包括目标车辆在第一时刻所对应的位置信息以及速度信息中至少一项，待处理数据包括目标车辆在第一时刻所对应的伪距观测值以及多普勒观测值中至少一项，然后根据卫星滤波参数以及待处理数据，确定目标车辆在第一时刻所对应的第一参数修正量，基于此，可以采用第一参数修正量对卫星滤波参数进行更新，得到目标车辆在第一时刻的定位信息。获取目标车辆在第二时刻的运动状态，其中，第二时刻为出现在第一时刻之后的一个时刻；若目标车辆在第二时刻的运动状态满足定位修正条件，则获取运动状态所对应的约束矩阵，接下来，根据 运动状态所对应的约束矩阵，确定目标车辆在第二时刻所对应的第二参数修正量，最后采用第二参数修正量对第一时刻的定位信息进行更新，得到目标车辆在第二时刻的定位信息。通过上述方式，当车辆位于弱卫星信号场景时，可利用伪距观测值与多普勒观测值中至少一项对车辆的定位信息进行修正，基于卫星星历确定的伪距观测值与多普勒观测值具有较高的可靠性，因此，通过伪距观测值与多普勒观测值辅助卫星定位能够强化弱卫星信号场景下卫星定位的可靠性，从而提升车辆定位信息的准确度。进一步地，再基于车辆运动状态构建约束，能够更好地提升定位精度。
附图说明
图1为本申请实施例中车辆定位系统的一个架构示意图；
图2为本申请实施例中车辆定位方法的一个交互流程示意图；
图3为本申请实施例中车辆定位方法的一个实施例示意图；
图4为本申请实施例中车辆定位方法的一个流程示意图
图5为本申请实施例中车载定位系统的一个架构示意图；
图6为本申请实施例中获取卫星滤波参数的一个示意图；
图7为本申请实施例中获取待处理数据的一个示意图；
图8为本申请实施例中基于车载图像判定车辆运动状态的一个示意图；
图9为本申请实施例中基于车载图像判定车辆运动状态的另一个示意图；
图10为本申请实施例中基于方向盘摆位信息判定车辆运动状态的一个示意图；
图11为本申请实施例中基于方向盘摆位信息判定车辆运动状态的另一个示意图；
图12为本申请实施例中车辆定位装置的一个实施例示意图；
图13为本申请实施例中终端设备的一个结构示意图。
具体实施方式
本申请实施例提供了一种车辆定位的方法、相关装置、设备以及存储介质，基于卫星星历确定的伪距观测值与多普勒观测值具有较高的可靠性，因此，通过伪距观测值与多普勒观测值辅助卫星定位能够强化弱卫星信号场景下卫星定位的可靠性，从而提升车辆定位信息的准确度。
本申请的说明书和权利要求书及上述附图中的术语“第一”、“第二”、“第三”、“第四”等(如果存在)是用于区别类似的对象，而不必用于描述特定的顺序或先后次序。应该理解这样使用的数据在适当情况下可以互换，以便这里描述的本申请的实施例例如能够以除了在这里图示或描述的那些以外的顺序实施。此外，术语“包括”和“对应于”以及他们的任何变形，意图在于覆盖不排他的包含，例如，包含了一系列步骤或单元的过程、方法、系统、产品或设备不必限于清楚地列出的那些步骤或单元，而是可包括没有清楚地列出的或对于这些过程、方法、产品或设备固有的其它步骤或单元。
随着社会的进步和科技的发展，定位技术在技术手段、定位精度和可用性等方面均取得质的飞越，并且逐步从航海、航天、航空、测绘、军事和自然灾害预防等领域，逐步渗透社会生活的方方面面，成为人们日常中不可或缺的重要应用，例如，人员搜寻、位置查找、交通管理、车辆导航与路线规划等，其中，全球卫星导航系统(Global Navigation Satellite  System，GNSS)在上述场景中起到了非常重要的作用。然而，终端设备定位坐标很容易发生变化，有时候变化较大，甚至还可能显示错误，这种现象就是所谓的“定位漂移”。在高大建筑密集或天气情况不好的地方，由于信号经过多次的反射和反射，可能造成信号误差，出现定位漂移。如果不能很好地解决定位漂移的情况，那么会导致定位应用的推广和使用受到一定限制。
为了降低定位漂移给车辆定位所带来的影响，本申请实施例提供了一种车辆定位的方法，该方法应用于图1所示的车辆定位系统，如图所示，车辆定位系统包括连续运行参考站(Continuously Operating Reference Stations，CORS)服务器、业务服务器和终端设备，且客户端部署于终端设备上。业务服务器具体可以是导航业务服务器，相应地，客户端可以是导航应用。本申请涉及的业务服务器可以是独立的物理服务器，也可以是多个物理服务器构成的服务器集群或者分布式系统，还可以是提供云服务、云数据库、云计算、云函数、云存储、网络服务、云通信、中间件服务、域名服务、安全服务、内容分发网络(Content Delivery Network，CDN)、以及大数据和人工智能平台等基础云计算服务的云服务器。终端设备可以是车载终端、智能手机、平板电脑、笔记本电脑、掌上电脑、个人电脑、智能电视、智能手表等，但并不局限于此。终端设备以及服务器可以通过有线或无线通信方式进行直接或间接地连接，本申请在此不做限制。服务器和终端设备的数量也不做限制。
CORS服务器由四个部分组成，分别为参考站部分、数据中心部分、数据通信部分及用户应用部分。各部分形成一个分布于整个城市的专用网络。
参考站部分由控制区域内均匀分布的基准站组成。基准站由GNSS、计算机、气象设备、通信设备、电源设备及观测场地等构成，具备长期连续跟踪和记录卫星信号的能力，是CORS的数据源，其主要功能为，卫星信号的捕获、跟踪、记录与传输，以及设备完好性监测等。其中，GNSS是能在地球表面或近地空间的任何地点为用户提供全天候的三维坐标和速度以及时间信息的空基无线电导航定位系统。
数据中心部分由计算机、网络和软件系统构成。数据中心部分包括系统控制中心以及用户数据中心，系统控制中心是CORS的神经中枢，可24小时连续不间断地根据各基准站所采集的实时观测数据在区域内进行整体建模解算，并通过现有的数据通讯网络和无线数据播发网，向各类需要测量和导航的用户以国际通用格式提供码相位和载波相位差分修正信息，以便实时解算出流动站的精确点位。用户数据中心提供CORS服务的下行链路，将控制中心的数据成果传递给用户。
数据通信部分由公用或专用的通信网络构成，包括数据传输硬件设备及软件控制模块。数据通信部分的主要功能为，把基准站GNSS观测数据传输至系统控制中心，把系统差分信息传输至用户等。
用户应用部分由接收机、无线通讯的解调器及相关的设备组成。用户应用部分的主要功能为按照用户需求进行不同精度定位。
为了便于说明，下面将结合图2，对本申请提供的车辆定位确定方法进行介绍，请参阅图2，图2为本申请实施例中车辆定位方法的一个交互流程示意图，如图所示，具体地：
在步骤S1中，车载终端向CORS服务器发送星历下发请求。
在步骤S2中，CORS服务器向车载终端发送广播星历信息，即车载终端接收CORS基站服务器播发的卫星实时导航星历。
在步骤S3中，车载终端通过卫星定位设备获取伪距观测值和多普勒观测值。
在步骤S4中，车载终端利用伪距观测值和多普勒观测值中的至少一种，更新车辆的定位信息，其中，定位信息包括车辆的位置和速度。
在步骤S5中，车载终端根据车辆方向盘、里程计、摄像头或者路网匹配等信息，判定车辆处于静止状态或者直线运动状态。
在步骤S6中，当车辆处于静止或直线运动状态时，车载终端构建车辆运动状态约束。
在步骤S7中，车载终端利用车辆运动状态约束辅助卫星定位。
在步骤S8中，车载终端更新车辆的定位信息。
基于上述介绍，本申请车辆定位方法可结合自动驾驶技术实现自动驾驶或辅助驾驶，自动驾驶技术通常包括高精地图、环境感知、行为决策、路径规划、运动控制等技术，自定驾驶技术有着广泛的应用前景。
自动驾驶技术为基于人工智能(Artificial Intelligence，AI)技术的一个分支，其中，AI是利用数字计算机或者数字计算机控制的机器模拟、延伸和扩展人的智能，感知环境、获取知识并使用知识获得最佳结果的理论、方法、技术及应用系统。换句话说，AI是计算机科学的一个综合技术，它企图了解智能的实质，并生产出一种新的能以人类智能相似的方式做出反应的智能机器。AI也就是研究各种智能机器的设计原理与实现方法，使机器具有感知、推理与决策的功能。
AI技术是一门综合学科，涉及领域广泛，既有硬件层面的技术也有软件层面的技术。AI基础技术一般包括如传感器、专用AI芯片、云计算、分布式存储、大数据处理技术、操作/交互系统、机电一体化等技术。AI软件技术主要包括计算机视觉技术、语音处理技术、自然语言处理技术以及机器学习/深度学习等几大方向。
结合上述介绍，下面将对本申请中车辆定位的方法进行介绍，请参阅图3，本申请实施例中车辆定位方法的一个实施例包括：
101、终端设备获取卫星滤波参数以及待处理数据，其中，卫星滤波参数包括时钟偏差以及时钟偏差变化率，且卫星滤波参数还包括目标车辆在第一时刻所对应的位置信息以及速度信息中至少一项，待处理数据包括目标车辆在第一时刻所对应的伪距观测值以及多普勒观测值中至少一项；
本实施例中，终端设备(例如可以为目标车辆的车载终端)获取在第一时刻的卫星滤波参数，该卫星滤波参数包括第一时刻所对应的时钟偏差以及时钟偏差变化率，此外，还可以包括目标车辆在第一时刻所对应的位置信息以及速度信息中至少一项。其中，第一时刻表示当前时刻，目标车辆表示待定位的车辆。时钟偏差表示某个时间系统下，时钟指示时间相对于该系统的标准时之差。例如，某时刻GPS接收机的时钟读数与GPS标准时之差。时钟偏差变化率表示卫星定位设备的时钟偏差变化情况。
终端设备获取在第一时刻的待处理数据，待处理数据包括目标车辆在第一时刻所对应的伪距观测值以及多普勒观测值中至少一项。其中，伪距观测值表示信号的本地接收时刻 与信号所携的表征时间值之差。多普勒观测值表示相邻两个观测时间间隔期间的平均速度。
具体地，本申请提供的终端设备可应用于如图5所示的车载定位系统，为了便于理解，请参阅图5，图5为本申请实施例中车载定位系统的一个架构示意图，如图所示，车载定位系统包括卫星系统、连接线、卫星定位设备以及终端设备，其中，卫星系统包含但不仅限于美国的GPS、中国的北斗卫星导航系统(BeiDou Navigation Satellite System，BDS)、俄罗斯的格洛纳斯(GLONASS)和欧洲的伽利略(GALILEO)四大卫星导航系统。随着近年来BDS和GLONASS在亚太地区的全面服务开启，尤其是BDS在民用领域发展越来越快。卫星导航系统已经在航空、航海、通信、人员跟踪、消费娱乐、测绘、授时、车辆监控管理和汽车导航与信息服务等方面广泛使用，而且总的发展趋势是为实时应用提供高精度服务。
本申请采用的卫星定位设备可以是消费级卫星定位设备，该消费级卫星定位设备用于为终端设备提供待处理数据。终端设备可以是车载终端或者计算机。连接线可以是通用串行总线(Universal Serial Bus，USB)或高清多媒体接口(High Definition Multimedia Interface，HDMI)连接线，且连接线主要用于连接卫星定位设备和终端设备。
需要说明的是，本申请涉及的终端设备可以是车载终端，也可以是智能手机，还可以是其他类型的计算机，此处不做限定。
102、终端设备根据卫星滤波参数以及待处理数据，确定目标车辆在第一时刻所对应的第一参数修正量；
本实施例中，终端设备根据第一时刻所对应的卫星滤波参数以及待处理数据，计算得到目标车辆在第一时刻的第一参数修正量。
103、终端设备采用第一参数修正量对卫星滤波参数进行更新，得到目标车辆在第一时刻的定位信息；
本实施例中，终端设备采用第一参数修正量对卫星滤波参数进行更新，即终端设备将第一参数修正量与卫星滤波参数进行相加后，可得到目标车辆在第一时刻的定位信息。需要说明的是，如果卫星滤波参数包括位置信息，则定位信息包括更新后的位置信息。如果卫星滤波参数包括速度信息，则定位信息包括更新后的速度信息。如果卫星滤波参数包括速度信息以及位置信息，则定位信息包括更新后的速度信息以及更新后的位置信息。
104、终端设备获取目标车辆在第二时刻的运动状态，其中，第二时刻为出现在第一时刻之后的一个时刻；
本实施例中，终端设备可进一步基于目标车辆的运动状态，对目标车辆的定位信息进行更新，其中，定位信息主要包括位置信息和速度信息。
105、若目标车辆在第二时刻的运动状态满足定位修正条件，则终端设备获取运动状态所对应的约束矩阵，其中，约束矩阵表示在运动状态下满足的定位信息变化量；
本实施例中，终端设备需判断目标车辆在第二时刻的运动状态是否满足定位修正条件，如果满足，则继续获取运动状态所对应的约束矩阵。反之，如果不满足，则可以将第一时刻的定位信息确定为第二时刻的定位信息，或者，基于第二时刻下多普勒观察值和伪距观察值，重新计算第二时刻的定位信息。
具体地，在满足定位修正条件时，主要讨论两种情况，一种情况为，目标车辆处于静止状态的情况下，构建静止状态下的约束矩阵，另一种情况为，目标车辆处于直行状态的情况下，构建直行状态下的约束矩阵。
106、终端设备根据运动状态所对应的约束矩阵，确定目标车辆在第二时刻所对应的第二参数修正量；
本实施例中，终端设备基于静止状态下的约束矩阵计算得到第二参数修正量，或者，基于直行状态下的约束矩阵计算得到第二参数修正量。
107、终端设备采用第二参数修正量对第一时刻的定位信息进行更新，得到目标车辆在第二时刻的定位信息。
本实施例中，终端设备使用第二参数修正量对第一时刻的定位信息进行更新，得到目标车辆在第二时刻的定位信息。
为了便于理解，请参阅图4，图4为本申请实施例中车辆定位方法的一个流程示意图，如图所示，具体地：
在步骤201中，终端设备(例如，车载终端)设置卫星滤波参数以及对卫星滤波参数进行初始化处理。
在步骤202中，终端设备(例如，车载终端)判断是否接收到卫星定位设备输出的待处理数据，如果接收到卫星定位设备输出的待处理数据，则执行步骤204，反之，如果未接收到卫星定位设备输出的待处理数据，则执行步骤203。
在步骤203中，终端设备(例如，车载终端)对滤波器时间进行推进更新，例如，将t时刻推进为t+1时刻。
在步骤204中，当终端设备(例如，车载终端)接收到卫星定位设备输出的待处理数据时，基于本伪距观测值和多普勒观测值更新目标车辆的定位信息，该定位信息包括位置信息和速度信息中的至少一项。
在步骤205中，终端设备(例如，车载终端)根据目标车辆的方向盘、里程计、摄像头或者路网匹配结果，确定目标车辆的运动状态。
在步骤206中，如果目标车辆处于静止状态，则终端设备(例如，车载终端)构建静止状态下的约束矩阵，基于静止状态下的约束矩阵，更新车辆的位置信息和速度信息。
在步骤207中，如果目标车辆处于直线行驶状态，则终端设备(例如，车载终端)构建直线行驶状态下的约束矩阵，基于直线行驶状态下的约束矩阵，更新车辆的位置信息和速度信息。
本申请实施例中，提供了一种车辆定位的方法。通过上述方式，当车辆位于弱卫星信号场景时，可利用伪距观测值与多普勒观测值中至少一项对车辆的定位信息进行修正，基于卫星星历确定的伪距观测值与多普勒观测值具有较高的可靠性，因此，通过伪距观测值与多普勒观测值辅助卫星定位能够强化弱卫星信号场景下卫星定位的可靠性，从而提升车辆定位信息的准确度。进一步地，再基于车辆运动状态构建约束，能够更好地提升定位精度。
可选地，在上述图3对应的实施例的基础上，本申请实施例提供的另一个可选实施例中， 终端设备获取卫星滤波参数以及待处理数据，具体可以包括：
终端设备向服务器发送星历下发请求，以使服务器响应于星历下发请求，获取第一时刻所对应的广播星历信息，其中，广播星历信息包括N个卫星所对应的星历参数，N为大于或等于1的整数；
终端设备接收服务器发送的第一时刻所对应的广播星历信息；
终端设备根据第一时刻所对应的广播星历信息确定在第一时刻所对应的卫星滤波参数；
通过卫星定位设备获取所述第一时刻所对应的所述待处理数据。
本实施例中，介绍了一种获取卫星滤波参数的方式。终端设备在利用伪距观测值和多普勒观测值更新车辆定位信息之前，可以获取卫星位置以及卫星滤波参数。具体地，终端设备向CORS服务器发送星历下发请求，以接收CORS服务器发送的广播星历信息。其中，该广播星历信息是指第一时刻所对应的广播星历信息，广播星历信息主要包括头文件和卫星相关参数，头文件包括文件的一些基本信息，例如，电离层参数、数据类型、跳秒引起的时间增量以及用于计算协调世界时(Universal Time Coordinated，UTC)时间的历书参数等。卫星相关参数包括伪随机噪声码(pseudo random noise code，PRN)、时钟时间、卫星钟差、轨道偏心率以及星历参考时刻等。基于此，终端设备还可以根据第一时刻所对应的广播星历信息，计算在第一时刻每个卫星所对应的卫星位置。
为了便于说明，请参阅图6，图6为本申请实施例中获取卫星滤波参数的一个示意图，如图所示，具体地：
在步骤A1中，终端设备通过第四代移动通信技术(the 4th generation mobile communication technology，4G)网络或者WIFI网络，向CORS服务器发送星历下发请求，该星历下发请求可携带第一时刻所对应的时间标识。
在步骤A2中，CORS服务器可以基于星历下发请求，通过4G网络或者WIFI网络，向终端设备发送实时的广播星历信息，发送广播星历信息的方式包含但不仅限于采用二进制流的形式发送，或者采用数据包的形式发送。其中，广播星历信息包括不同卫星的星历参数表，每个星历参数表可表示为一组用于计算卫星位置的星历参数，即广播星历信息包括N个卫星所对应的星历参数。
在步骤A3中，终端设备根据广播星历信息，利用卫星信息处理单元计算出第一时刻(即当前时刻)的N个卫星位置以及卫星滤波参数，其中，第一时刻可由终端设备(例如，车载终端)的系统时间或伪距观测值时标获取到。需要说明的是，卫星信息处理单元可内置于终端设备，还可以外置于终端设备，此处不做限定。
终端设备在利用伪距观测值和多普勒观测值更新车辆定位信息之前，可以获取待处理数据，即获取伪距观测值和多普勒观测值中的至少一种。
具体地，为了便于理解，请参阅图7，图7为本申请实施例中获取待处理数据的一个示意图，如图所示，终端设备(例如，车载终端)通过连接线(例如，USB或者HDMI连接线)接收卫星定位设备获取到的伪距观测值和多普勒观测值。
可以理解的是，卫星定位设备用于跟踪和处理卫星信号，并测量终端设备与卫星之间的几何距离(即伪距观测值)以及卫星信号的多普勒效应(即多普勒观测值)。卫星定位设 备通常包括天线、卫星信号跟踪环路以及基带信号处理等模块，集成卫星定位设备的终端设备根据伪距观测值和多普勒观测值，计算终端设备当前的位置坐标。卫星定位设备广泛应用于地图导航、测绘、航空航天以及位置服务等领域，例如，智能手机地图导航、高精度大地测量以及民航等。
车载终端主要由三大部分组成，包括车载(GPS和/或北斗)监控终端、通信网络及调度监控中心，其中，车载(GPS和/或北斗)监控终端又称车机、(GPS和/或北斗)终端或者(GPS和/或北斗)监控终端，它负责根据接收到GPS和/或北斗卫星信号计算出定位坐标，同时，通过通讯网络发送定位信息、状态信息及发送接收控制信息。通信网络则是实现车辆与调度监控中心信息交换的载体，一般指全球移动通信系统(Global System for Mobile Communications，GSM)、通用无线分组业务(General packet radio service，GPRS)、码分多址(Code Division Multiple Access，CDMA)基站及互联网(Internet)，调度监控中心是整个信息系统的通讯核心，负责与车载GPS监控终端的信息交换，各种内容和控制信息的分类、记录和转发。
其次，本申请实施例中，提供了一种获取卫星滤波参数的方式，通过上述方式，CORS服务器可以向终端设备下发实时的广播星历信息，使得终端设备能够根据广播星历信息，确定当前时刻每个卫星所在的位置。由于广播星历信息具有较高的实时性，因此，计算得到的卫星位置也更准确。利用卫星定位设备能够捕获到准确的伪距观测值和多普勒观测值，从而提升方案的可行性和可操作性。
可选地，在上述图3对应的实施例的基础上，本申请实施例提供的另一个可选实施例中，卫星滤波参数包括目标车辆在第一时刻所对应的位置信息，待处理数据包括目标车辆在第一时刻所对应的伪距观测值；
终端设备根据卫星滤波参数以及待处理数据，确定目标车辆在第一时刻所对应的第一参数修正量，具体可以包括：
终端设备获取第一时刻所对应的协方差矩阵；
终端设备获取N个单位观测向量所对应的第一雅克比矩阵，其中，N个单位观测向量所包括的每个单位观测向量表示卫星与目标车辆之间连线的方向向量；
终端设备获取第一时刻所对应的伪距测量误差矩阵；
终端设备获取第一时刻所对应的第一增益矩阵；
终端设备根据卫星滤波参数以及第一时刻所对应的伪距观测值，确定第一预测残差向量；
终端设备根据第一时刻所对应的协方差矩阵、第一雅克比矩阵、伪距测量误差矩阵、第一增益矩阵以及第一预测残差向量，确定目标车辆在第一时刻所对应的第一参数修正量。
本实施例中，介绍了一种基于伪距观测值确定第一参数修正量的方式。首先，在构建终端设备(例如，车载终端)的位置和速度滤波器时，将位置信息、速度信息、时钟偏差以及时钟偏差变化率设置为卫星滤波参数，卫星滤波参数表示为：
X＝[x y z v x v y v z dt GPS dt GLO dt GAL dt BDS dtr] T；
其中，X表示卫星滤波参数，x表示车辆的x轴坐标，y表示车辆的y轴坐标，z表示车辆 的y轴坐标，v x表示车辆在x轴方向上的速度，v y表示车辆在y轴方向上的速度，v z表示车辆在z轴方向上的速度，dt GPS表示卫星定位设备时钟相对于GPS的时钟偏差，dt GLO表示卫星定位设备时钟相对于GLONASS的时钟偏差，dt BDS表示卫星定位设备时钟相对于GALILEO的时钟偏差，dt BDS表示卫星定位设备时钟相对于北斗系统的时钟偏差，dtr表示卫星定位设备的时钟偏差变化率。
基于此，需要对卫星滤波参数进行初始化，初始位置信息可由网络定位结果或者卫星定位设备输出结果给定，初始速度信息可由卫星定位设备输出的速度给定或者设置为零。卫星定位设备的时钟偏差dt GPS、时钟偏差dt GLO、时钟偏差dt GAL和时钟偏差dt BDS均设置为0，且将卫星定位设备的钟差变化率dtr设置为零。初始化的卫星滤波参数表示为：
X(t 0)＝[x 0 y 0 z 0 v x0 v y0 v z0 0 0 0 0 0] T；
其中，X(t 0)表示初始化的卫星滤波参数，x 0表示车辆初始的x轴坐标，y 0表示车辆初始的y轴坐标，z 0表示车辆初始的z轴坐标，v x0表示车辆在x轴方向上的初始速度，v y0表示车辆在y轴方向上的初始速度，v z0表示车辆在z轴方向上的初始速度。
此外，还可以设置一个滤波的协方差矩阵，对协方差矩阵进行初始化后得到如下形式：
P(t 0)＝diag(10 6,11)；
其中，P(t 0)表示初始化的协方差矩阵，diag(10 6,11)表示对角线元素值均为10 6的11维对角矩阵。
结合上述介绍，假设在t k时刻滤波参数为X(t k)，则下一时刻(即当前时刻或第一时刻)t k+1滤波参数为：
X(t k+1)＝F·X(t k)；
其中，X(t k+1)表示在第一时刻所对应的卫星滤波参数，X(t k)表示在第一时刻的前一个时刻所对应的卫星滤波参数，F表示系统的状态转移矩阵。
此外，假设在t k时刻滤波参数的协方差矩阵P(t k)，则下一时刻(即当前时刻或第一时刻)t k+1滤波参数的协方差矩阵为：
P(t k+1)＝F·P(t k)·F T+Q(t k+1)；
其中，P(t k+1)表示在第一时刻所对应的协方差矩阵，P(t k)表示在前一个时刻所对应的协方差矩阵，F表示系统的状态转移矩阵，Q(t k+1)表示在第一时刻所对应的系统噪声矩阵，该第一时刻所对应的系统噪声矩阵表示为：
Figure PCTCN2022076131-appb-000001
dt＝t k+1-t k；
Figure PCTCN2022076131-appb-000002
其中，S x表示x轴方向的加速度的密度谱，S y表示y轴方向的加速度的密度谱，S z表示z轴方向的加速度的密度谱，S f表示卫星定位设备时钟频率漂移谱密度，S g表示卫星定位设备相对于前一个时刻的时钟相位漂移谱密度。
结合上述介绍，在计算目标车辆在第一时刻的第一参数修正量时，需要获取伪距观测值，假设在第一时刻t k+1下，终端设备接收到卫星定位设备反馈的N个卫星信号的伪距观测值，其中包括m个北斗卫星，n个GPS卫星，p个GLONASS卫星以及q个GALILEO卫星，则伪距观测值为：
Figure PCTCN2022076131-appb-000003
其中，ρ BDS,1表示第1个北斗卫星的伪距观测值，ρ BDS,m表示第m个北斗卫星的伪距观测值，ρ GPS,1表示第1个GPS卫星的伪距观测值，ρ GPS,n表示第n个GPS卫星的伪距观测值，ρ GLO,1第1个GLONASS卫星的伪距观测值，ρ GLO,p表示第p个GLONASS卫星的伪距观测值，ρ GAL,1第1个GALILEO卫星的伪距观测值，ρ GAL,q表示第q个GLONASS卫星的伪距观测值。
需要说明的是，m、n、p和q可以是大于或等于0的整数，且m+n+p+q之和等于N，N为大于或等于1的整数。
此时，终端设备根据卫星滤波参数以及第一时刻所对应的伪距观测值，确定第一预测残差向量，即采用如下方式计算第一预测残差向量：
Figure PCTCN2022076131-appb-000004
i＝1,2,……,N；
其中，δz表示第一预测残差向量，t k+1表示第一时刻，r(t k+1)表示目标车辆在第一时刻的位置信息(该位置信息来源于卫星滤波参数)，r i表示第i个卫星的卫星位置(例如，r GPS,1表示第1个GPS卫星的卫星位置，r GPS,n表示第n个GPS卫星的卫星位置)，c表示真空值光速值，dt i表示第i个卫星的时钟偏差，上述参数可由卫星实时导航星历计算得到的，即通过第一时刻的广播星历信息计算得到的。η i,i＝1,2,……,N表示误差改正数(包括电离层、对流 层以及S地球自转改正)，上述参数可由经验模型计算得到的。
基于此，终端设备可以根据第一时刻所对应的协方差矩阵、第一雅克比矩阵、伪距测量误差矩阵、第一增益矩阵以及第一预测残差向量，确定目标车辆在第一时刻所对应的第一参数修正量，即，第一参数修正量的计算方式为：
Figure PCTCN2022076131-appb-000005
其中，δX(t k+1)表示目标车辆在第一时刻所对应的第一参数修正量，P(t k+1)表示第一时刻所对应的协方差矩阵，H表示第一雅克比矩阵，R ρ(t k+1)表示第一时刻所对应的伪距测量误差矩阵(可直接由卫星定位设备获取到)，δz表示第一预测残差向量，K(t k+1)表示第一时刻所对应的第一增益矩阵。
具体地，第一雅克比矩阵是基于N个单位观测向量确定的，每个单位观测向量用于表示卫星与目标车辆之间连线的方向向量，采用如下方式计算第一雅克比矩阵：
Figure PCTCN2022076131-appb-000006
Figure PCTCN2022076131-appb-000007
Figure PCTCN2022076131-appb-000008
Figure PCTCN2022076131-appb-000009
其中，H表示第一雅克比矩阵，e i表示第i个卫星至目标车辆的单位观测向量，即为卫星和终端设备这两个空间点连线的方向向量，σ ρi表示测量噪声的方差值，CN0表示第i个卫星的载噪比，r(t k+1)表示目标车辆在第一时刻的位置信息，x(t k+1)表示目标车辆在第一时刻的x轴坐标，y(t k+1)表示目标车辆在第一时刻的y轴坐标，z(t k+1)表示目标车辆在第一时刻的z轴坐标。进一步地，e i的计算方式如下：
Figure PCTCN2022076131-appb-000010
其中，r i表示第i个卫星的卫星位置，r(t k+1)表示目标车辆在第一时刻的位置信息。
需要说明的是，如果卫星滤波参数包括目标车辆在第一时刻所对应的位置信息，而不包括速度信息，则可以将卫星滤波参数中的速度信息设置为0。
在得到第一参数修正量δX(t k+1)之后，对卫星滤波参数X(t k+1)进行更新，得到目标车辆在第一时刻的定位信息，即采用如下方式更新得到定位信息：
Figure PCTCN2022076131-appb-000011
其中，
Figure PCTCN2022076131-appb-000012
表示目标车辆在第一时刻的定位信息，X(t k+1)表示卫星滤波参数，δX(t k+1)表示目标车辆在第一时刻所对应的第一参数修正量。
此外，还可以采用如下方式更新滤波参数的协方差矩阵：
Figure PCTCN2022076131-appb-000013
其中，
Figure PCTCN2022076131-appb-000014
表示第一时刻更新后的协方差矩阵，I 11×11表示11×11的矩阵，H表示第一雅克比矩阵，P(t k+1)表示第一时刻的协方差矩阵，K(t k+1)表示第一时刻所对应的第一增益矩阵。
需要说明的是，参数修正量(例如，第一参数修正量)用于修正目标车辆的位置信息和速度信息，而协方差矩阵表示目标车辆的位置信息和速度信息的准确度。
其次，本申请实施例中，提供了一种基于伪距观测值确定第一参数修正量的方式，通过上述方式，利用伪距观测值对卫星滤波参数进行修正，基于卫星星历确定的伪距观测值具有较高的可靠性，因此，通过辅助卫星定位能够强化弱卫星信号场景下卫星定位的可靠性，从而提升车辆定位信息的准确度。
可选地，在上述图3对应的实施例的基础上，本申请实施例提供的另一个可选实施例中，卫星滤波参数包括目标车辆在第一时刻所对应的速度信息，待处理数据包括目标车辆在第一时刻所对应的多普勒观测值；
终端设备根据卫星滤波参数以及待处理数据，确定目标车辆在第一时刻所对应的第一参数修正量，具体可以包括：
终端设备获取第一时刻所对应的协方差矩阵；
终端设备获取N个单位观测向量所对应的第二雅克比矩阵，其中，N个单位观测向量所包括的每个单位观测向量表示卫星与目标车辆之间连线的方向向量；
终端设备获取第一时刻所对应的多普勒测量误差矩阵；
终端设备获取第一时刻所对应的第二增益矩阵；
终端设备根据卫星滤波参数以及第一时刻所对应的多普勒观测值，确定第二预测残差向量；
终端设备根据第一时刻所对应的协方差矩阵、第二雅克比矩阵、多普勒测量误差矩阵、第二增益矩阵以及第二预测残差向量，确定目标车辆在第一时刻所对应的第一参数修正量。
本实施例中，介绍了一种基于多普勒观测值确定第一参数修正量的方式。与前述实施例类似，在构建终端设备(例如，车载终端)的位置和速度滤波器时，将位置信息、速度信息、时钟偏差以及时钟偏差变化率设置为卫星滤波参数，并且需要对卫星滤波参数进行初始化，初始位置信息可由网络定位结果或者卫星定位设备输出结果给定，初始速度信息可由卫星定位设备输出的速度给定或者设置为零。
结合上述介绍，假设在t k时刻滤波参数为X(t k)，则下一时刻(即当前时刻或第一时刻)t k+1滤波参数为：
X(t k+1)＝F·X(t k)；
其中，X(t k+1)表示在第一时刻所对应的卫星滤波参数，X(t k)表示在前一个时刻所对应的卫星滤波参数，F表示系统的状态转移矩阵。
此外，假设在t k时刻滤波参数的协方差矩阵P(t k)，则下一时刻(即当前时刻或第一时刻)t k+1滤波参数的协方差矩阵为：
P(t k+1)＝F·P(t k)·F T+Q(t k+1)；
其中，P(t k+1)表示在第一时刻所对应的协方差矩阵，P(t k)表示在前一个时刻所对应的协方差矩阵，F表示系统的状态转移矩阵，Q(t k+1)表示在第一时刻所对应的系统噪声矩阵。可以理解的是，第一时刻的系统噪声矩阵计算方式与前述实施例类似，故此处不做赘述。
结合上述介绍，在计算目标车辆在第一时刻的第一参数修正量时，需要获取多普勒观测值，假设在第一时刻t k+1下，终端设备接收到卫星定位设备反馈的N个卫星信号的多普勒观测值，则伪距观测值表示为
Figure PCTCN2022076131-appb-000015
此时，终端设备根据卫星滤波参数以及第一时刻所对应的多普勒观测值，确定第二预测残差向量，即采用如下方式计算第二预测残差向量：
Figure PCTCN2022076131-appb-000016
其中，
Figure PCTCN2022076131-appb-000017
表示第二预测残差向量，t k+1表示第一时刻，
Figure PCTCN2022076131-appb-000018
表示伪距观测值，v i表示第i个卫星的速度，v(t k+1)表示目标车辆在第一时刻的速度信息(该速度信息来源于卫星滤波参数)，r i表示第i个卫星的卫星位置(例如，r GPS,1表示第1个GPS卫星的卫星位置，r GPS,n表示第n个GPS卫星的卫星位置)，c表示真空值光速值，dtr表示卫星定位设备的时钟偏差变化率，
Figure PCTCN2022076131-appb-000019
表示第i个卫星的时钟偏差变化率。上述参数可由卫星实时导航星历计算得到的，即通过第一时刻的广播星历信息计算得到的。
基于此，终端设备可以根据第一时刻所对应的协方差矩阵、第二雅克比矩阵、多普勒测量误差矩阵、第二增益矩阵以及第二预测残差向量，确定目标车辆在第一时刻所对应的第一参数修正量，即，第一参数修正量的计算方式为：
Figure PCTCN2022076131-appb-000020
其中，
Figure PCTCN2022076131-appb-000021
表示目标车辆在第一时刻所对应的第一参数修正量，P(t k+1)表示第一时刻所对应的协方差矩阵，M表示第二雅克比矩阵，
Figure PCTCN2022076131-appb-000022
表示第一时刻所对应的多普勒测量误差矩阵(可直接由卫星定位设备获取到)，
Figure PCTCN2022076131-appb-000023
表示第二预测残差向量，
Figure PCTCN2022076131-appb-000024
表示第一时刻所对应的第二增益矩阵。
具体地，第二雅克比矩阵是基于N个单位观测向量确定的，每个单位观测向量用于表示卫星与目标车辆之间连线的方向向量，采用如下方式计算第二雅克比矩阵：
Figure PCTCN2022076131-appb-000025
Figure PCTCN2022076131-appb-000026
Figure PCTCN2022076131-appb-000027
Figure PCTCN2022076131-appb-000028
其中，M表示第二雅克比矩阵，e i表示第i个卫星至目标车辆的单位观测向量，即为卫星和终端设备这两个空间点连线的方向向量，
Figure PCTCN2022076131-appb-000029
表示测量噪声的方差值，CN0表示第i个卫星的载噪比，v(t k+1)表示目标车辆在第一时刻的速度信息，v x(t k+1)表示目标车辆在第一时刻x轴方向上的速度信息，v y(t k+1)表示目标车辆在第一时刻y轴方向上的速度信息，v z(t k+1)表示目标车辆在第一时刻z方向上的速度信息。进一步地，e i的计算方式如下：
Figure PCTCN2022076131-appb-000030
其中，r i表示第i个卫星的卫星位置，r(t k+1)表示目标车辆在第一时刻的位置信息。
需要说明的是，如果卫星滤波参数包括目标车辆在第一时刻所对应的速度信息，而不包括位置信息，则可以将卫星滤波参数中的位置信息设置为0。可以理解的是，m、n、p和q可以是大于或等于0的整数，且m+n+p+q之和等于N，N为大于或等于1的整数。
在得到第一参数修正量
Figure PCTCN2022076131-appb-000031
之后，对卫星滤波参数X(t k+1)进行更新，得到目标车辆在第一时刻的定位信息，即采用如下方式更新得到定位信息：
Figure PCTCN2022076131-appb-000032
其中，
Figure PCTCN2022076131-appb-000033
表示目标车辆在第一时刻的定位信息，X(t k+1)表示卫星滤波参数，
Figure PCTCN2022076131-appb-000034
表示目标车辆在第一时刻所对应的第一参数修正量。
此外，还可以采用如下方式更新滤波参数的协方差矩阵：
Figure PCTCN2022076131-appb-000035
其中，
Figure PCTCN2022076131-appb-000036
表示第一时刻更新后的协方差矩阵，I 11×11表示11×11的矩阵，M表示第二雅克比矩阵，P(t k+1)表示第一时刻的协方差矩阵，
Figure PCTCN2022076131-appb-000037
表示第一时刻所对应的第二增益矩阵。
需要说明的是，参数修正量(例如，第一参数修正量)用于修正目标车辆的位置信息和速度信息，而协方差矩阵表示目标车辆的位置信息和速度信息的准确度。
其次，本申请实施例中，提供了一种基于多普勒观测值确定第一参数修正量的方式，通过上述方式，利用多普勒观测值对卫星滤波参数进行修正，基于卫星星历确定的多普勒观测值具有较高的可靠性，因此，通过辅助卫星定位能够强化弱卫星信号场景下卫星定位的可靠性，从而提升车辆定位信息的准确度。
可选地，在上述图3对应的实施例的基础上，本申请实施例提供的另一个可选实施例中，卫星滤波参数包括目标车辆在第一时刻所对应的速度信息以及位置信息，待处理数据包括目标车辆在第一时刻所对应的伪距观测值以及多普勒观测值；
终端设备根据卫星滤波参数以及待处理数据，确定目标车辆在第一时刻所对应的第一参数修正量，具体可以包括：
终端设备获取第一时刻所对应的协方差矩阵；
终端设备获取N个单位观测向量所对应的第一雅克比矩阵，其中，N个单位观测向量所包括的每个单位观测向量表示卫星与目标车辆之间连线的方向向量；
终端设备获取第一时刻所对应的伪距测量误差矩阵；
终端设备获取第一时刻所对应的第一增益矩阵；
终端设备根据卫星滤波参数以及第一时刻所对应的伪距观测值，确定第一预测残差向量；
终端设备根据第一时刻所对应的协方差矩阵、第一雅克比矩阵、伪距测量误差矩阵、第一增益矩阵以及第一预测残差向量，确定目标车辆在第一时刻所对应的目标参数修正量，其中，目标参数修正量用于更新所述卫星滤波参数；
终端设备根据第一时刻所对应的协方差矩阵、第一增益矩阵以及第一雅克比矩阵，确定目标协方差矩阵；
终端设备根据目标协方差矩阵，确定目标车辆在第一时刻所对应的第一参数修正量。
本实施例中，介绍了一种基于伪距观测值和多普勒观测值共同确定第一参数修正量的方式。与前述实施例类似，在构建终端设备(例如，车载终端)的位置和速度滤波器时，将位置信息、速度信息、时钟偏差以及时钟偏差变化率设置为卫星滤波参数，并且需要对卫星滤波参数进行初始化，初始位置信息可由网络定位结果或者卫星定位设备输出结果给定，初始速度信息可由卫星定位设备输出的速度给定或者设置为零。
结合上述介绍，假设在t k时刻滤波参数为X(t k)，则下一时刻(即当前时刻或第一时刻)t k+1滤波参数为：
X(t k+1)＝F·X(t k)；
其中，X(t k+1)表示在第一时刻所对应的卫星滤波参数，X(t k)表示在前一个时刻所对应的卫星滤波参数，F表示系统的状态转移矩阵。
此外，假设在t k时刻滤波参数的协方差矩阵P(t k)，则下一时刻(即当前时刻或第一时刻)t k+1滤波参数的协方差矩阵为：
P(t k+1)＝F·P(t k)·F T+Q(t k+1)；
其中，P(t k+1)表示在第一时刻所对应的协方差矩阵，P(t k)表示在前一个时刻所对应的协方差矩阵，F表示系统的状态转移矩阵，Q(t k+1)表示在第一时刻所对应的系统噪声矩阵。可以理解的是，第一时刻的系统噪声矩阵计算方式与前述实施例类似，故此处不做赘述。
结合上述介绍，在计算目标车辆在第一时刻的第一参数修正量时，需要获取伪距观测值，假设在第一时刻t k+1下，终端设备接收到卫星定位设备反馈的N个卫星信号的伪距观测值，其中包括m个北斗卫星，n个GPS卫星，p个GLONASS卫星以及q个GALILEO卫星，则伪距观测值为：
Figure PCTCN2022076131-appb-000038
其中，ρ BDS,1表示第1个北斗卫星的伪距观测值，ρ BDS,m表示第m个北斗卫星的伪距观测值，ρ GPS,1表示第1个GPS卫星的伪距观测值，ρ GPS,n表示第n个GPS卫星的伪距观测值，ρ GLO,1第1个GLONASS卫星的伪距观测值，ρ GLO,p表示第p个GLONASS卫星的伪距观测值，ρ GAL,1 第1个GALILEO卫星的伪距观测值，ρ GAL,q表示第q个GLONASS卫星的伪距观测值。
需要说明的是，m、n、p和q可以是大于或等于0的整数，且m+n+p+q之和等于N，N为大于或等于1的整数。
此时，终端设备根据卫星滤波参数以及第一时刻所对应的伪距观测值，确定第一预测残差向量，即采用如下方式计算第一预测残差向量：
Figure PCTCN2022076131-appb-000039
i＝1,2,……,N；
其中，δz表示第一预测残差向量，t k+1表示第一时刻，r(t k+1)表示目标车辆在第一时刻的位置信息(该位置信息来源于卫星滤波参数)，r i表示第i个卫星的卫星位置(例如，r GPS,1表示第1个GPS卫星的卫星位置，r GPS,n表示第n个GPS卫星的卫星位置)，c表示真空值光速值，dt i表示第i个卫星的时钟偏差，上述参数可由卫星实时导航星历计算得到的，即通过第一时刻的广播星历信息计算得到的。η i,i＝1,2,……,N表示误差改正数(包括电离层、对流层以及S地球自转改正)，上述参数可由经验模型计算得到的。
基于此，终端设备可以根据第一时刻所对应的协方差矩阵、第一雅克比矩阵、伪距测量误差矩阵、第一增益矩阵以及第一预测残差向量，确定目标车辆在第一时刻所对应的目标参数修正量，即，目标参数修正量的计算方式为：
Figure PCTCN2022076131-appb-000040
其中，δX(t k+1)表示目标车辆在第一时刻所对应的目标参数修正量，P(t k+1)表示第一 时刻所对应的协方差矩阵，H表示第一雅克比矩阵，R ρ(t k+1)表示第一时刻所对应的伪距测量误差矩阵(可直接由卫星定位设备获取到)，δz表示第一预测残差向量，K(t k+1)表示第一时刻所对应的第一增益矩阵。
具体地，第一雅克比矩阵是基于N个单位观测向量确定的，每个单位观测向量用于表示卫星与目标车辆之间连线的方向向量，采用如下方式计算第一雅克比矩阵：
Figure PCTCN2022076131-appb-000041
Figure PCTCN2022076131-appb-000042
Figure PCTCN2022076131-appb-000043
Figure PCTCN2022076131-appb-000044
其中，H表示第一雅克比矩阵，e i表示第i个卫星至目标车辆的单位观测向量，即为卫星和终端设备这两个空间点连线的方向向量，σ ρi表示测量噪声的方差值，CN0表示第i个卫星的载噪比，r(t k+1)表示目标车辆在第一时刻的位置信息，x(t k+1)表示目标车辆在第一时刻的x轴坐标，y(t k+1)表示目标车辆在第一时刻的y轴坐标，z(t k+1)表示目标车辆在第一时刻的z轴坐标。进一步地，e i的计算方式如下：
Figure PCTCN2022076131-appb-000045
其中，r i表示第i个卫星的卫星位置，r(t k+1)表示目标车辆在第一时刻的位置信息。
在得到目标参数修正量δX(t k+1)之后，对卫星滤波参数X(t k+1)进行更新，得到目标车辆在第一时刻的已更新卫星滤波参数，即采用如下方式得到已更新卫星滤波参数：
Figure PCTCN2022076131-appb-000046
其中，
Figure PCTCN2022076131-appb-000047
表示目标车辆在第一时刻的已更新卫星滤波参数，X(t k+1)表示卫星滤波参数，δX(t k+1)表示目标车辆在第一时刻所对应的目标参数修正量。
此外，还可以采用如下方式更新滤波参数的协方差矩阵：
Figure PCTCN2022076131-appb-000048
其中，
Figure PCTCN2022076131-appb-000049
表示第一时刻所对应的目标协方差矩阵，I 11×11表示11×11的矩阵，H表示第一雅克比矩阵，P(t k+1)表示第一时刻所对应的协方差矩阵，K(t k+1)表示第一时刻所对应的第一增益矩阵。
由此可见，终端设备根据目标参数修正量以及卫星滤波参数，确定已更新卫星滤波参数，然后根据目标协方差矩阵、第二雅克比矩阵、多普勒测量误差矩阵、第二增益矩阵以及第二预测残差向量，确定目标车辆在第一时刻所对应的第一参数修正量。最后，采用第一参数修正量对已更新卫星滤波参数进行更新，得到目标车辆在第一时刻的定位信息。
其次，本申请实施例中，提供了一种基于伪距观测值和多普勒观测值共同确定第一参数修正量的方式，通过上述方式，利用伪距观测值和多普勒观测值对卫星滤波参数进行修正，基于卫星星历确定的伪距观测值和多普勒观测值具有较高的可靠性，因此，通过辅助卫星定位能够强化弱卫星信号场景下卫星定位的可靠性，从而提升车辆定位信息的准确度。
可选地，在上述图3对应的实施例的基础上，本申请实施例提供的另一个可选实施例中，终端设备根据目标协方差矩阵，确定目标车辆在第一时刻所对应的第一参数修正量，具体可以包括：
终端设备获取N个单位观测向量所对应的第二雅克比矩阵，其中，N个单位观测向量所包括的每个单位观测向量表示卫星与目标车辆之间连线的方向向量；
终端设备获取第一时刻所对应的多普勒测量误差矩阵；
终端设备获取第一时刻所对应的第二增益矩阵；
终端设备根据卫星滤波参数以及第一时刻所对应的多普勒观测值，确定第二预测残差向量；
终端设备根据目标协方差矩阵、第二雅克比矩阵、多普勒测量误差矩阵、第二增益矩阵以及第二预测残差向量，确定目标车辆在第一时刻所对应的第一参数修正量；
终端设备采用第一参数修正量对卫星滤波参数进行更新，得到目标车辆在第一时刻的定位信息，具体可以包括：
终端设备根据目标参数修正量以及卫星滤波参数，确定已更新卫星滤波参数，其中，已更新卫星滤波参数包括目标车辆在第一时刻所对应的已更新速度信息以及已更新位置信息；
终端设备采用第一参数修正量对已更新卫星滤波参数进行更新，得到目标车辆在第一时刻的定位信息。
本实施例中，本实施例中，介绍了一种基于伪距观测值和多普勒观测值共同确定第一参数修正量的方式。结合上述介绍，在计算目标车辆在第一时刻的第一参数修正量时，需要获取多普勒观测值，假设在第一时刻t k+1下，终端设备接收到卫星定位设备反馈的N个卫星信号的多普勒观测值，则伪距观测值表示为
Figure PCTCN2022076131-appb-000050
此时，终端设备根据卫星滤波参数以及第一时刻所对应的多普勒观测值，确定第二预测残差向量，即采用如下方式计算第二预测残差向量：
Figure PCTCN2022076131-appb-000051
其中，
Figure PCTCN2022076131-appb-000052
表示第二预测残差向量，t k+1表示第一时刻，
Figure PCTCN2022076131-appb-000053
表示伪距观测值，v i表示第i个卫星的速度，v(t k+1)表示目标车辆在第一时刻的速度信息(该速度信息来源于卫星滤波参数)，r i表示第i个卫星的卫星位置(例如，r GPS,1表示第1个GPS卫星的卫星位置，r GPS,n表示第n个GPS卫星的卫星位置)，c表示真空值光速值，dtr表示卫星定位设备的时钟偏差变化率，
Figure PCTCN2022076131-appb-000054
表示第i个卫星的时钟偏差变化率。上述参数可由卫星实时导航星历计算得到的，即通过第一时刻的广播星历信息计算得到的。
基于此，终端设备可以根据第一时刻所对应的协方差矩阵、第二雅克比矩阵、多普勒测量误差矩阵、第二增益矩阵以及第二预测残差向量，确定目标车辆在第一时刻所对应的第一参数修正量，即，第一参数修正量的计算方式为：
Figure PCTCN2022076131-appb-000055
其中，
Figure PCTCN2022076131-appb-000056
表示目标车辆在第一时刻所对应的第一参数修正量，
Figure PCTCN2022076131-appb-000057
表示第一时刻所对应的协方差矩阵，M表示第二雅克比矩阵，
Figure PCTCN2022076131-appb-000058
表示第一时刻所对应的多普勒测量误差矩阵(可直接由卫星定位设备获取到)，
Figure PCTCN2022076131-appb-000059
表示第二预测残差向量，
Figure PCTCN2022076131-appb-000060
表示第一时刻所对应的第二增益矩阵。
具体地，第二雅克比矩阵是基于N个单位观测向量确定的，每个单位观测向量用于表示卫星与目标车辆之间连线的方向向量，采用如下方式计算第二雅克比矩阵：
Figure PCTCN2022076131-appb-000061
Figure PCTCN2022076131-appb-000062
Figure PCTCN2022076131-appb-000063
Figure PCTCN2022076131-appb-000064
其中，M表示第二雅克比矩阵，e i表示第i个卫星至目标车辆的单位观测向量，即为卫星和终端设备这两个空间点连线的方向向量，
Figure PCTCN2022076131-appb-000065
表示测量噪声的方差值，CN0表示第i个卫星的载噪比，v(t k+1)表示目标车辆在第一时刻的速度信息，v x(t k+1)表示目标车辆在第一时刻x轴方向上的速度信息，v y(t k+1)表示目标车辆在第一时刻y轴方向上的速度信息，v z(t k+1)表示目标车辆在第一时刻z方向上的速度信息。进一步地，e i的计算方式如下：
Figure PCTCN2022076131-appb-000066
其中，r i表示第i个卫星的卫星位置，r(t k+1)表示目标车辆在第一时刻的位置信息。
需要说明的是，如果卫星滤波参数包括目标车辆在第一时刻所对应的速度信息，而不包括位置信息，则可以将卫星滤波参数中的位置信息设置为0。可以理解的是，m、n、p和q可以是大于或等于0的整数，且m+n+p+q之和等于N，N为大于或等于1的整数。
在得到第一参数修正量
Figure PCTCN2022076131-appb-000067
之后，对已更新卫星滤波参数
Figure PCTCN2022076131-appb-000068
进行更新，得到目标车辆在第一时刻的定位信息，即采用如下方式更新得到定位信息：
Figure PCTCN2022076131-appb-000069
其中，
Figure PCTCN2022076131-appb-000070
表示目标车辆在第一时刻的定位信息，
Figure PCTCN2022076131-appb-000071
表示已更新卫星滤波参数
Figure PCTCN2022076131-appb-000072
表示目标车辆在第一时刻所对应的第一参数修正量。
此外，还可以采用如下方式更新滤波参数的协方差矩阵：
Figure PCTCN2022076131-appb-000073
其中，
Figure PCTCN2022076131-appb-000074
表示第一时刻更新后的协方差矩阵，I 11×11表示11×11的矩阵，M表示第二雅克比矩阵，
Figure PCTCN2022076131-appb-000075
表示第一时刻所对应的目标协方差矩阵，
Figure PCTCN2022076131-appb-000076
表示第一时刻所对应的第二增益矩阵。
需要说明的是，参数修正量(例如，第一参数修正量)用于修正目标车辆的位置信息和速度信息，而协方差矩阵表示目标车辆的位置信息和速度信息的准确度。
再次，本申请实施例中，提供了一种基于伪距观测值和多普勒观测值共同确定第一参数修正量的方式，通过上述方式，利用伪距观测值和多普勒观测值对卫星滤波参数进行修正，基于卫星星历确定的伪距观测值和多普勒观测值具有较高的可靠性，因此，通过辅助卫星定位能够强化弱卫星信号场景下卫星定位的可靠性，从而提升车辆定位信息的准确度。
可选地，在上述图3对应的实施例的基础上，本申请实施例提供的另一个可选实施例中，终端设备采用第二参数修正量对第一时刻的定位信息进行更新，得到目标车辆在第二时刻的定位信息，具体可以包括：
终端设备采用第二参数修正量对第一时刻的定位信息进行更新，得到待处理定位信息；
终端设备根据第一时刻的定位信息以及第一权重值，确定第一定位信息；
终端设备根据待处理定位信息以及第二权重值，确定第二定位信息；
终端设备根据第一定位信息以及第二定位信息，确定目标车辆在第二时刻的定位信息。
本实施例中，介绍了一种更新定位信息的方式。终端设备可采用第二参数修正量对第一时刻的定位信息进行更新，例如，将第二参数修正量与第一时刻的定位信息进行相加后，可得到目标车辆在第二时刻的待处理定位信息。
具体地，终端设备还可以采用第一权重值对第一时刻的定位信息进行计算，假设第一权重值为0.1，那么将第一时刻的定位信息(包括速度信息以及位置信息)与第一权重值相乘，得到对应的第一定位信息。类似地，终端设备还可以采用第二权重值对第二时刻的待处理定位信息进行计算，假设第二权重值为0.9，那么将第一时刻的待处理定位信息(包括速度信息以及位置信息)与第二权重值相乘，得到对应的第二定位信息。将据第一定位信息和第二定位信息相加之后，得到定目标车辆在第二时刻的定位信息。
需要说明的是，第一权重值和第二权重值可以根据实际情况进行调整，此处仅为一个示意，不应理解为对本申请的限定。
其次，本申请实施例中，提供了一种更新定位信息的方式，通过上述方式，将基于多普勒观测值和伪距观测值计算得到的定位信息，与基于约束矩阵计算的定位信息，按照一定比例分配相应的权重值，以此调整定位信息的置信情况，从而提升方案的可靠性。
可选地，在上述图3对应的实施例的基础上，本申请实施例提供的另一个可选实施例中，卫星滤波参数包括目标车辆在第一时刻所对应的位置信息以及速度信息；
终端设备获取目标车辆在第二时刻的运动状态之前，还可以包括：
终端设备获取卫星滤波参数所对应的位置置信因子以及速度置信因子，其中，位置置信因子表示目标车辆的位置精度，速度置信因子表示目标车辆的速度精度；
终端设备获取可见卫星数量；
若位置置信因子、速度置信因子以及可见卫星数量满足车辆约束条件，则终端设备确定执行获取目标车辆在第二时刻的运动状态的步骤。
本实施例中，介绍了一种基于位置置信因子、速度置信因子以及可见卫星数量判定是否执行定位约束的方式。终端设备可以获取目标车辆在某个时刻所对应的位置信息以及速度信息，并且进一步获取位置信息的位置置信因子和速度信息的速度置信因子。此外，终端设备还可以探测到可见卫星数量。
位置置信因子和速度置信因子可根据场景来确定，假设位置置信因子和速度置信因子的取值范围为0至1，数值越大，表示置信度越高。位置置信因子和速度置信因子与目标车辆所在的场景相关，例如，在车道级导航中，位置置信因子和速度置信因子均为0.3，在地图导航中，位置置信因子和速度置信因子均为0.5。需要说明的是，上述场景仅为一个示意， 在实际应用中，还可以基于其他场景灵活定义位置置信因子和速度置信因子。
具体地，如果位置置信因子大于或等于第一阈值，速度置信因子大于或等于第二阈值，可见卫星数量大于或等于第三阈值，则满足车辆约束条件。反之，如果位置置信因子小于第一阈值，或者，速度置信因子小于第二阈值，又或者，可见卫星数量小于第三阈值，则不满足车辆约束条件。
可以理解的是，第一阈值可以设置为0.5，第二阈值可以设置为0.6，第三阈值可以设置为6，其中，第一阈值、第二阈值和第三阈值可根据实际情况灵活设置，此处仅为一个示意，不应理解为对本申请的限定。
其次，本申请实施例中，提供了一种基于位置置信因子、速度置信因子以及可见卫星数量判定是否执行定位约束的方式，通过上述方式，为定位约束提供了一定的限制，一方面能够提升定位约束的准确性，另一方面，对于不满足车辆约束条件的情况而言，无需进行后续计算，从而节省计算资源。
可选地，在上述图3对应的实施例的基础上，本申请实施例提供的另一个可选实施例中，终端设备获取目标车辆在第二时刻的运动状态，具体可以包括：
终端设备通过图像采集装置获取第一车载图像；
终端设备通过图像采集装置获取第二车载图像，其中，第二车载图像与第一车载图像为相邻两帧图像；
终端设备对第一车载图像以及第二车载图像进行特征点匹配；
终端设备根据特征点匹配结果确定目标车辆在第二时刻的运动状态。
本实施例中，介绍了基于车载图像判断车辆行驶状态的方式。终端设备通过图像采集装置拍摄连续的车载影像，然后对车载影像中相邻两帧车载图像进行特征点匹配，根据匹配图像特征点在图像坐标系中的位置坐标变化，判断车辆是否静止，或是否处于直线运动状态。
具体地，为了便于介绍，请参阅图8，图8为本申请实施例中基于车载图像判定车辆运动状态的一个示意图，如图8的(A)所示，在第一车载图像中具有8个特征点，如图8的(B)所示，在第二车载图像中具有8个特征点，若第一车载图像中的8个特征点与第二车载图像中的8个特征点没有发生偏移，或偏移量小于预设值(例如，10个像素)，则认为目标车辆处于静止状态。图8所示的情况可理解为目标车辆正处于静止状态。
请参阅图9，图9为本申请实施例中基于车载图像判定车辆运动状态的另一个示意图，如图9的(A)所示，在第一车载图像中具有8个特征点，如图9的(B)所示，在第二车载图像中具有8个特征点，若第一车载图像中的8个特征点与第二车载图像中的8个特征点发生偏移，且偏移方向为聚合或者发散，则认为目标车辆处于直线运动状态。图9所示的情况可理解为目标车辆正处于直线运动状态。
其次，本申请实施例中，提供了基于车载图像判断车辆行驶状态的方式，通过上述方式，能够确定目标车辆当前的行驶状态，便于进行后续处理，从而提升方案的可行性和可操作性。
可选地，在上述图3对应的实施例的基础上，本申请实施例提供的另一个可选实施例中， 终端设备获取目标车辆在第二时刻的运动状态，具体可以包括：
终端设备根据目标车辆所对应的方向盘摆位信息，确定目标车辆在第二时刻的运动状态；
或者，
终端设备基于路网匹配结果确定目标车辆在第二时刻的运动状态。
本实施例中，介绍了基于方向盘摆位信息和路网匹配结果判断车辆行驶状态的方式。下面将分别进行说明。
一、基于方向盘摆位信息判断车辆行驶状态；
具体地，为了便于介绍，请参阅图10，图10为本申请实施例中基于方向盘摆位信息判定车辆运动状态的一个示意图，如图10的(A)所示，目标车辆的方向盘摆正时，方向盘摆位信息为0度，如果发生偏转，则按照角度变化改变方向盘摆位信息，例如，向左转了5度，则方向盘摆位信息为-5度，又例如，向右转了5度，则方向盘摆位信息为5度。如图10的(B)所示，此时方向盘摆位信息为0度，由此确定目标车辆正处于静止状态或直线运动状态。
请参阅图11，图11为本申请实施例中基于方向盘摆位信息判定车辆运动状态的另一个示意图，如图11的(A)所示，目标车辆的方向盘摆正时，方向盘摆位信息为0度。假设方向盘向左转了5度，即如图11的(B)所示的情况，此时方向盘摆位信息为-5度，由此确定目标车辆正处于非静止状态，也处于非直线运动状态。
可以理解的是，结合油门情况或者里程计等，可以进一步确定是直线运动状态还是静止状态。
二、基于路网匹配结果判断车辆行驶状态；
具体地，路网匹配可理解为地图匹配，首先获取目标车辆的行驶轨迹，然后基于位置服务(Location Based Services，LBS)确定目标车辆所在的位置，进而根据地图数据进行匹配，得到路网匹配结果。
可以理解的是，LBS是无线运营公司为用户提供的一种与位置有关的服务，基于LBS，是利用各类型的定位技术来获取定位设备当前的所在位置，通过移动互联网向定位设备提供信息资源和基础服务。LBS服务中融合了移动通讯、互联网络、空间定位、位置信息以及大数据等多种信息技术，利用移动互联网络服务平台进行数据更新和交互，使用户可以通过空间定位来获取相应的服务。
其次，本申请实施例中，提供了基于方向盘摆位信息和路网匹配结果判断车辆行驶状态的方式，通过上述方式，能够确定目标车辆当前的行驶状态，便于进行后续处理，从而提升方案的可行性和可操作性。
可选地，在上述图3对应的实施例的基础上，本申请实施例提供的另一个可选实施例中，获取目标车辆在第二时刻的运动状态之后，还可以包括：
若目标车辆在第二时刻的运动状态为静止状态，则终端设备确定目标车辆在第二时刻的运动状态满足定位修正条件；
终端设备获取运动状态所对应的约束矩阵，具体可以包括：
终端设备构建静止状态所对应的约束矩阵；
终端设备根据运动状态所对应的约束矩阵，确定目标车辆在第二时刻所对应的第二参数修正量，具体可以包括：
终端设备获取第二时刻所对应的协方差矩阵；
终端设备获取第一测量误差方差矩阵；
终端设备获取第二时刻所对应的速度矩阵；
终端设备获取第二时刻所对应的第三增益矩阵；
终端设备根据第二时刻所对应的协方差矩阵、静止状态所对应的约束矩阵、第一测量误差方差矩阵、第二时刻所对应的速度矩阵以及第三增益矩阵，确定目标车辆在第二时刻所对应的第二参数修正量。
本实施例中，介绍了一种构建车辆静止状态约束辅助卫星定位的方式。假设当前时刻为第二时刻，第二时刻表示为t p+1，第二时刻的前一个时刻即为t p。如果t p时刻和t p+1时刻的时间间隔内目标车辆处于静止状态，则此时可获取第二时刻所对应的第一时刻的定位信息X(t p+1)，以及第二时刻所对应的协方差矩阵P(t p+1)。
具体地，采用如下方式计算第二参数修正量：
Figure PCTCN2022076131-appb-000077
其中，δX 0(t p+1)表示目标车辆在第二时刻所对应的第二参数修正量，P(t p+1)表示第二时刻所对应的协方差矩阵，V表示静止状态所对应的约束矩阵，R 0(t p+1)表示第二时刻所对应的第一测量误差方差矩阵，K 0(t p+1)表示第二时刻所对应的第三增益矩阵，δz 0表示第二时刻所对应的速度矩阵。
基于此，第二时刻所对应的速度矩阵具体表示为：
Figure PCTCN2022076131-appb-000078
其中，δz 0表示第二时刻所对应的速度矩阵，v x(t p+1)表示目标车辆在第二时刻x轴方向上的速度信息，v y(t p+1)表示目标车辆在第二时刻y轴方向上的速度信息，v z(t p+1)表示目标车辆在第二时刻z方向上的速度信息。
基于此，静止状态所对应的约束矩阵具体表示为：
Figure PCTCN2022076131-appb-000079
其中，V表示静止状态所对应的约束矩阵。
基于此，第二时刻所对应的第一测量误差方差矩阵具体表示为：
Figure PCTCN2022076131-appb-000080
其中，R 0(t p+1)表示第二时刻所对应的第一测量误差方差矩阵。
结合上述介绍，终端设备采用第二参数修正量对第一时刻的定位信息进行更新，得到目标车辆在第二时刻的定位信息，即采用如下方式计算目标车辆在第二时刻的定位信息：
Figure PCTCN2022076131-appb-000081
其中，
Figure PCTCN2022076131-appb-000082
表示目标车辆在第二时刻的定位信息，X(t p+1)表示目标车辆在第二时刻的第一时刻的定位信息，δX 0(t p+1)表示第二参数修正量。
还可以采用如下方式更新滤波参数的协方差矩阵：
Figure PCTCN2022076131-appb-000083
其中，
Figure PCTCN2022076131-appb-000084
表示第二时刻更新后的协方差矩阵，I 11×11表示11×11的矩阵，V表示静止状态所对应的约束矩阵，P(t p+1)表示第二时刻所对应的协方差矩阵，K 0(t p+1)表示第二时刻所对应的第三增益矩阵。
至此，车辆静止状态约束更新完成，并得到更新后的定位信息
Figure PCTCN2022076131-appb-000085
以及更新后的
Figure PCTCN2022076131-appb-000086
进一步地，本申请实施例中，提供了一种构建车辆静止状态约束辅助卫星定位的方式，通过上述方式，构建一个合理的约束能够提升车辆静止的情况下的定位准确度。
可选地，在上述图3对应的实施例的基础上，本申请实施例提供的另一个可选实施例中，终端设备获取目标车辆在第二时刻的运动状态之后，还可以包括：
若目标车辆在第二时刻的运动状态为直线行驶状态，则终端设备确定目标车辆在第二时刻的运动状态满足定位修正条件；
终端设备获取运动状态所对应的约束矩阵，具体可以包括：
终端设备构建直线行驶状态所对应的约束矩阵；
终端设备根据运动状态所对应的约束矩阵，确定目标车辆在第二时刻所对应的第二参数修正量，具体可以包括：
终端设备获取第二时刻所对应的协方差矩阵；
终端设备获取第二测量误差方差矩阵；
终端设备获取运动方向差值，其中，运动方向差值为目标车辆在第二时刻的运动方向，与目标车辆在第三时刻的运动方向之间的差值，第三时刻为第二时刻的前一个时刻；
终端设备获取第二时刻所对应的第四增益矩阵；
终端设备根据第二时刻所对应的协方差矩阵、直线行驶状态所对应的约束矩阵、第二测量误差方差矩阵、运动方向差值以及第四增益矩阵，确定目标车辆在第二时刻所对应的第二参数修正量。
本实施例中，介绍了一种构建车辆直线运动状态约束辅助卫星定位的方式。假设当前时刻为第二时刻，第二时刻表示为t p+1，第二时刻的前一个时刻即为t p。如果t p时刻和t p+1时刻的时间间隔内目标车辆处于静止状态，则此时可获取第二时刻所对应的第一时刻的定位信息X(t p+1)，以及第二时刻所对应的协方差矩阵P(t p+1)，且在t p时刻，目标车辆的速度为：
Figure PCTCN2022076131-appb-000087
其中，v(t p)表示目标车辆在t p时刻的速度，v x(t p)表示目标车辆在t p时刻x轴方向上的速度信息，v y(t p)表示目标车辆在t p时刻y轴方向上的速度信息，v z(t p)表示目标车辆在t p时刻z方向上的速度信息。
由此，可得到在t p时刻目标车辆的运动方向
Figure PCTCN2022076131-appb-000088
满足下列关系式：
Figure PCTCN2022076131-appb-000089
其中，
Figure PCTCN2022076131-appb-000090
表示t p时刻目标车辆的运动方向，λ表示终端设备的经度，φ表示终端设备的纬度。
在t p+1时刻，车辆的运动速度表示为：
Figure PCTCN2022076131-appb-000091
其中，v(t p+1)表示目标车辆在(t p+1)时刻(即第二时刻)的速度，v x(t p+1)表示目标车辆在(t p+1)时刻(即第二时刻)x轴方向上的速度信息，v y(t p+1)表示目标车辆在(t p+1)时刻(即第二时刻)y轴方向上的速度信息，v z(t p+1)表示目标车辆在在(t p+1)时刻(即第二时刻)z方向上的速度信息。
在(t p+1)时刻(即第二时刻)，目标车辆的运动方向
Figure PCTCN2022076131-appb-000092
同样满足下列关系式，即：
Figure PCTCN2022076131-appb-000093
其中，
Figure PCTCN2022076131-appb-000094
表示在(t p+1)时刻(即第二时刻)目标车辆的运动方向，λ表示终端设备的经度，φ表示终端设备的纬度。
由于车辆做直线运动，因此，理论上满足如下车辆直线运动约束方程：
Figure PCTCN2022076131-appb-000095
具体地，采用如下方式计算第二参数修正量：
Figure PCTCN2022076131-appb-000096
其中，δX L(t p+1)表示目标车辆在第二时刻所对应的第二参数修正量，P(t p+1)表示第二时刻所对应的协方差矩阵，G表示直线行驶状态所对应的约束矩阵，R L(t p+1)表示第二时刻所对应的第二测量误差方差矩阵，K L(t p+1)表示第二时刻所对应的第四增益矩阵，δz L表示运动方向差值。
基于此，运动方向差值具体表示为：
Figure PCTCN2022076131-appb-000097
基于此，直线行驶状态所对应的约束矩阵具体表示为：
G＝[0 0 0 J vx J vy J vz 0 0 0 0 0]；
Figure PCTCN2022076131-appb-000098
Figure PCTCN2022076131-appb-000099
Figure PCTCN2022076131-appb-000100
其中，J vx表示x方向上的速度约束，J vy表示y方向上的速度约束，J vz表示z方向上的速度约束。
基于此，第二时刻所对应的第二测量误差方差矩阵具体表示为：
Figure PCTCN2022076131-appb-000101
其中，R L(t p+1)表示第二时刻所对应的第二测量误差方差矩阵。
结合上述介绍，终端设备采用第二参数修正量对第一时刻的定位信息进行更新，得到目标车辆在第二时刻的定位信息，即采用如下方式计算目标车辆在第二时刻的定位信息：
Figure PCTCN2022076131-appb-000102
其中，
Figure PCTCN2022076131-appb-000103
表示目标车辆在第二时刻的定位信息，X(t p+1)表示目标车辆在第二时刻的第一时刻的定位信息，δX L(t p+1)表示第二参数修正量。
还可以采用如下方式更新滤波参数的协方差矩阵：
Figure PCTCN2022076131-appb-000104
其中，
Figure PCTCN2022076131-appb-000105
表示第二时刻更新后的协方差矩阵，I 11×11表示11×11的矩阵，G表示直线行驶状态所对应的约束矩阵，P(t p+1)表示第二时刻所对应的协方差矩阵，K L(t p+1)表示第二时刻所对应的第四增益矩阵。
至此，车辆直线行驶状态约束更新完成，并得到更新后的定位信息
Figure PCTCN2022076131-appb-000106
以及更新后的
Figure PCTCN2022076131-appb-000107
进一步地，本申请实施例中，提供了一种构建车辆直线运动状态约束辅助卫星定位的方式，通过上述方式，构建一个合理的约束能够提升车辆直线运动的情况下的定位准确度。
下面对本申请中的车辆定位装置进行详细描述，请参阅图12，图12为本申请实施例中车辆定位装置的一个实施例示意图，车辆定位装置30包括：
获取模块301，用于获取卫星滤波参数以及待处理数据，其中，卫星滤波参数包括时钟偏差以及时钟偏差变化率，且卫星滤波参数还包括目标车辆在第一时刻所对应的位置信息以及速度信息中至少一项，待处理数据包括目标车辆在第一时刻所对应的伪距观测值以及多普勒观测值中至少一项；
确定模块302，用于根据卫星滤波参数以及待处理数据，确定目标车辆在第一时刻所对应的第一参数修正量；
更新模块303，用于采用第一参数修正量对卫星滤波参数进行更新，得到目标车辆在第一时刻的定位信息；
获取模块301，还用于获取目标车辆在第二时刻的运动状态，其中，第二时刻为出现在第一时刻之后的一个时刻；
获取模块301，还用于若目标车辆在第二时刻的运动状态满足定位修正条件，则获取运动状态所对应的约束矩阵，其中，约束矩阵表示在运动状态下满足的定位信息变化量；
确定模块302，用于根据运动状态所对应的约束矩阵，确定目标车辆在第二时刻所对应的第二参数修正量；
更新模块303，用于采用第二参数修正量对第一时刻的定位信息进行更新，得到目标车辆在第二时刻的定位信息。
可选地，在上述图12所对应的实施例的基础上，本申请实施例提供的车辆定位装置30的另一实施例中，
获取模块301，具体用于向服务器发送星历下发请求，以使服务器响应于星历下发请求，获取第一时刻所对应的广播星历信息，其中，广播星历信息包括N个卫星所对应的星历参数，N为大于或等于1的整数；
接收服务器发送的第一时刻所对应的广播星历信息；
根据第一时刻所对应的广播星历信息确定在第一时刻所对应的卫星滤波参数；
通过卫星定位设备获取第一时刻所对应的待处理数据。
可选地，在上述图12所对应的实施例的基础上，本申请实施例提供的车辆定位装置30的另一实施例中，卫星滤波参数包括目标车辆在第一时刻所对应的位置信息，待处理数据包括目标车辆在第一时刻所对应的伪距观测值；
确定模块302，具体用于获取第一时刻所对应的协方差矩阵；
获取N个单位观测向量所对应的第一雅克比矩阵，其中，N个单位观测向量所包括的每个单位观测向量表示卫星与目标车辆之间连线的方向向量；
获取第一时刻所对应的伪距测量误差矩阵；
获取第一时刻所对应的第一增益矩阵；
根据卫星滤波参数以及第一时刻所对应的伪距观测值，确定第一预测残差向量；
根据第一时刻所对应的协方差矩阵、第一雅克比矩阵、伪距测量误差矩阵、第一增益矩阵以及第一预测残差向量，确定目标车辆在第一时刻所对应的第一参数修正量。
可选地，在上述图12所对应的实施例的基础上，本申请实施例提供的车辆定位装置30的另一实施例中，卫星滤波参数包括目标车辆在第一时刻所对应的速度信息，待处理数据包括目标车辆在第一时刻所对应的多普勒观测值；
确定模块302，具体用于获取第一时刻所对应的协方差矩阵；
获取N个单位观测向量所对应的第二雅克比矩阵，其中，N个单位观测向量所包括的每个单位观测向量表示卫星与目标车辆之间连线的方向向量；
获取第一时刻所对应的多普勒测量误差矩阵；
获取第一时刻所对应的第二增益矩阵；
根据卫星滤波参数以及第一时刻所对应的多普勒观测值，确定第二预测残差向量；
根据第一时刻所对应的协方差矩阵、第二雅克比矩阵、多普勒测量误差矩阵、第二增 益矩阵以及第二预测残差向量，确定目标车辆在第一时刻所对应的第一参数修正量。
可选地，在上述图12所对应的实施例的基础上，本申请实施例提供的车辆定位装置30的另一实施例中，卫星滤波参数包括目标车辆在第一时刻所对应的速度信息以及位置信息，待处理数据包括目标车辆在第一时刻所对应的伪距观测值以及多普勒观测值；
确定模块302，具体用于获取第一时刻所对应的协方差矩阵；
获取N个单位观测向量所对应的第一雅克比矩阵，其中，N个单位观测向量所包括的每个单位观测向量表示卫星与目标车辆之间连线的方向向量；
获取第一时刻所对应的伪距测量误差矩阵；
获取第一时刻所对应的第一增益矩阵；
根据卫星滤波参数以及第一时刻所对应的伪距观测值，确定第一预测残差向量；
根据第一时刻所对应的协方差矩阵、第一雅克比矩阵、伪距测量误差矩阵、第一增益矩阵以及第一预测残差向量，确定目标车辆在第一时刻所对应的目标参数修正量，其中，目标参数修正量用于更新卫星滤波参数；
根据第一时刻所对应的协方差矩阵、第一增益矩阵以及第一雅克比矩阵，确定目标协方差矩阵；
根据目标协方差矩阵，确定目标车辆在第一时刻所对应的第一参数修正量。
可选地，在上述图12所对应的实施例的基础上，本申请实施例提供的车辆定位装置30的另一实施例中，
确定模块302，具体用于获取N个单位观测向量所对应的第二雅克比矩阵，其中，N个单位观测向量所包括的每个单位观测向量表示卫星与目标车辆之间连线的方向向量；
获取第一时刻所对应的多普勒测量误差矩阵；
获取第一时刻所对应的第二增益矩阵；
根据卫星滤波参数以及第一时刻所对应的多普勒观测值，确定第二预测残差向量；
根据目标协方差矩阵、第二雅克比矩阵、多普勒测量误差矩阵、第二增益矩阵以及第二预测残差向量，确定目标车辆在第一时刻所对应的第一参数修正量；
采用第一参数修正量对卫星滤波参数进行更新，得到目标车辆在第一时刻的定位信息，包括：
根据目标参数修正量以及卫星滤波参数，确定已更新卫星滤波参数，其中，已更新卫星滤波参数包括目标车辆在第一时刻所对应的已更新速度信息以及已更新位置信息；
采用第一参数修正量对已更新卫星滤波参数进行更新，得到目标车辆在第一时刻的定位信息。
可选地，在上述图12所对应的实施例的基础上，本申请实施例提供的车辆定位装置30的另一实施例中，
更新模块303，具体用于采用第二参数修正量对第一时刻的定位信息进行更新，得到待处理定位信息；
根据第一时刻的定位信息以及第一权重值，确定第一定位信息；
根据待处理定位信息以及第二权重值，确定第二定位信息；
根据第一定位信息以及第二定位信息，确定目标车辆在第二时刻的定位信息。
可选地，在上述图12所对应的实施例的基础上，本申请实施例提供的车辆定位装置30的另一实施例中，卫星滤波参数包括目标车辆在第一时刻所对应的位置信息以及速度信息；
获取模块301，还用于获取目标车辆在第二时刻的运动状态之前，获取卫星滤波参数所对应的位置置信因子以及速度置信因子，其中，位置置信因子表示目标车辆的位置精度，速度置信因子表示目标车辆的速度精度；
获取模块301，还用于获取可见卫星数量；
确定模块302，还用于若位置置信因子、速度置信因子以及可见卫星数量满足车辆约束条件，则确定执行获取目标车辆在第二时刻的运动状态的步骤。
可选地，在上述图12所对应的实施例的基础上，本申请实施例提供的车辆定位装置30的另一实施例中，
获取模块301，具体用于通过图像采集装置获取第一车载图像；
通过图像采集装置获取第二车载图像，其中，第二车载图像与第一车载图像为相邻两帧图像；
对第一车载图像以及第二车载图像进行特征点匹配；
根据特征点匹配结果确定目标车辆在第二时刻的运动状态。
可选地，在上述图12所对应的实施例的基础上，本申请实施例提供的车辆定位装置30的另一实施例中，
获取模块301，具体用于根据目标车辆所对应的方向盘摆位信息，确定目标车辆在第二时刻的运动状态；
或者，
基于路网匹配结果确定目标车辆在第二时刻的运动状态。
可选地，在上述图12所对应的实施例的基础上，本申请实施例提供的车辆定位装置30的另一实施例中，
确定模块302，还用于获取模块301获取目标车辆在第二时刻的运动状态之后，若目标车辆在第二时刻的运动状态为静止状态，则确定目标车辆在第二时刻的运动状态满足定位修正条件；
获取模块301，具体用于构建静止状态所对应的约束矩阵；
确定模块302，具体用于获取第二时刻所对应的协方差矩阵；
获取第一测量误差方差矩阵；
获取第二时刻所对应的速度矩阵；
获取第二时刻所对应的第三增益矩阵；
根据第二时刻所对应的协方差矩阵、静止状态所对应的约束矩阵、第一测量误差方差矩阵、第二时刻所对应的速度矩阵以及第三增益矩阵，确定目标车辆在第二时刻所对应的第二参数修正量。
可选地，在上述图12所对应的实施例的基础上，本申请实施例提供的车辆定位装置30的另一实施例中，
确定模块302，还用于获取模块301获取目标车辆在第二时刻的运动状态之后，若目标车辆在第二时刻的运动状态为直线行驶状态，则确定目标车辆在第二时刻的运动状态满足定位修正条件；
获取模块301，具体用于构建直线行驶状态所对应的约束矩阵；
确定模块302，具体用于获取第二时刻所对应的协方差矩阵；
获取第二测量误差方差矩阵；
获取运动方向差值，其中，运动方向差值为目标车辆在第二时刻的运动方向，与目标车辆在第三时刻的运动方向之间的差值，第三时刻为第二时刻的前一个时刻；
获取第二时刻所对应的第四增益矩阵；
根据第二时刻所对应的协方差矩阵、直线行驶状态所对应的约束矩阵、第二测量误差方差矩阵、运动方向差值以及第四增益矩阵，确定目标车辆在第二时刻所对应的第二参数修正量。
本申请实施例还提供了另一种车辆定位装置，如图13所示，为了便于说明，仅示出了与本申请实施例相关的部分，具体技术细节未揭示的，请参照本申请实施例方法部分。在本申请实施例中，以终端设备为车载终端为例进行说明：
图13示出的是与本申请实施例提供的终端设备相关的车载终端的部分结构的框图。参考图13，车载终端包括：射频(radio frequency，RF)电路410、存储器420、输入单元430、显示单元440、传感器450、音频电路460、无线保真(WiFi)模块370、处理器480、以及电源490等部件。本领域技术人员可以理解，图13中示出的车载终端结构并不构成对车载终端的限定，可以包括比图示更多或更少的部件，或者组合某些部件，或者不同的部件布置。
下面结合图13对车载终端的各个构成部件进行具体的介绍：
RF电路410可用于收发信息或通话过程中，信号的接收和发送，特别地，将基站的下行信息接收后，给处理器480处理；另外，将设计上行的数据发送给基站。通常，RF电路410包括但不限于天线、至少一个放大器、收发信机、耦合器、低噪声放大器(low noise amplifier，LNA)、双工器等。此外，RF电路410还可以通过无线通信与网络和其他设备通信。上述无线通信可以使用任一通信标准或协议，包括但不限于GSM、GPRS、CDMA、宽带码分多址(wideband code division multiple access,WCDMA)、长期演进(long term evolution，LTE)、电子邮件、短消息服务(short messaging service，SMS)等。
存储器420可用于存储软件程序以及模块，处理器480通过运行存储在存储器420的软件程序以及模块，从而执行车载终端的各种功能应用以及数据处理。存储器420可主要包括存储程序区和存储数据区，其中，存储程序区可存储操作系统、至少一个功能所需的应用程序(比如声音播放功能、图像播放功能等)等；存储数据区可存储根据车载终端的使用所创建的数据(比如音频数据、电话本等)等。此外，存储器420可以包括高速随机存取存储器，还可以包括非易失性存储器，例如至少一个磁盘存储器件、闪存器件、或其他易失性固态存储器件。
输入单元430可用于接收输入的数字或字符信息，以及产生与车载终端的用户设置以及功能控制有关的键信号输入。具体地，输入单元430可包括触控面板431以及其他输入设备 432。触控面板431，也称为触摸屏，可收集用户在其上或附近的触摸操作(比如用户使用手指、触笔等任何适合的物体或附件在触控面板431上或在触控面板431附近的操作)，并根据预先设定的程式驱动相应的连接装置。
显示单元440可用于显示由用户输入的信息或提供给用户的信息以及车载终端的各种菜单。显示单元440可包括显示面板441。
车载终端还可包括至少一种传感器450，比如光传感器、运动传感器以及其他传感器。具体地，光传感器可包括环境光传感器及接近传感器。
音频电路460、扬声器461，传声器462可提供用户与车载终端之间的音频接口。
WiFi属于短距离无线传输技术，车载终端通过WiFi模块370可以帮助用户收发电子邮件、浏览网页和访问流式媒体等，它为用户提供了无线的宽带互联网访问。
处理器480是车载终端的控制中心，利用各种接口和线路连接整个车载终端的各个部分，通过运行或执行存储在存储器420内的软件程序和/或模块，以及调用存储在存储器420内的数据，执行车载终端的各种功能和处理数据。
上述实施例中由终端设备所执行的步骤可以基于该图13所示的终端设备结构。
本申请实施例中还提供一种计算机可读存储介质，该计算机可读存储介质中存储有计算机程序，当其在计算机上运行时，使得计算机执行如前述各个实施例描述的方法。
本申请实施例中还提供一种包括程序的计算机程序产品，当其在计算机上运行时，使得计算机执行前述各个实施例描述的方法。
所属领域的技术人员可以清楚地了解到，为描述的方便和简洁，上述描述的系统，装置和单元的具体工作过程，可以参考前述方法实施例中的对应过程，在此不再赘述。
在本申请所提供的几个实施例中，应该理解到，所揭露的系统，装置和方法，可以通过其它的方式实现。例如，以上所描述的装置实施例仅仅是示意性的，例如，所述单元的划分，仅仅为一种逻辑功能划分，实际实现时可以有另外的划分方式，例如多个单元或组件可以结合或者可以集成到另一个系统，或一些特征可以忽略，或不执行。另一点，所显示或讨论的相互之间的耦合或直接耦合或通信连接可以是通过一些接口，装置或单元的间接耦合或通信连接，可以是电性，机械或其它的形式。
所述作为分离部件说明的单元可以是或者也可以不是物理上分开的，作为单元显示的部件可以是或者也可以不是物理单元，即可以位于一个地方，或者也可以分布到多个网络单元上。可以根据实际的需要选择其中的部分或者全部单元来实现本实施例方案的目的。
另外，在本申请各个实施例中的各功能单元可以集成在一个处理单元中，也可以是各个单元单独物理存在，也可以两个或两个以上单元集成在一个单元中。上述集成的单元既可以采用硬件的形式实现，也可以采用软件功能单元的形式实现。
所述集成的单元如果以软件功能单元的形式实现并作为独立的产品销售或使用时，可以存储在一个计算机可读取存储介质中。基于这样的理解，本申请的技术方案本质上或者说对现有技术做出贡献的部分或者该技术方案的全部或部分可以以软件产品的形式体现出来，该计算机软件产品存储在一个存储介质中，包括若干指令用以使得一台计算机设备(可以是个人计算机，服务器，或者网络设备等)执行本申请各个实施例所述方法的全部或部 分步骤。而前述的存储介质包括：U盘、移动硬盘、只读存储器(read-only memory，ROM)、随机存取存储器(random access memory，RAM)、磁碟或者光盘等各种可以存储程序代码的介质。
以上所述，以上实施例仅用以说明本申请的技术方案，而非对其限制；尽管参照前述实施例对本申请进行了详细的说明，本领域的普通技术人员应当理解：其依然可以对前述各实施例所记载的技术方案进行修改，或者对其中部分技术特征进行等同替换；而这些修改或者替换，并不使相应技术方案的本质脱离本申请各实施例技术方案的精神和范围。

Claims (16)

  1. 一种车辆定位的方法，所述方法由终端设备执行，所述方法包括：
    获取卫星滤波参数以及待处理数据，其中，所述卫星滤波参数包括时钟偏差以及时钟偏差变化率，且所述卫星滤波参数还包括目标车辆在第一时刻所对应的位置信息以及速度信息中至少一项，所述待处理数据包括所述目标车辆在所述第一时刻所对应的伪距观测值以及多普勒观测值中至少一项；
    根据所述卫星滤波参数以及所述待处理数据，确定所述目标车辆在所述第一时刻所对应的第一参数修正量；
    采用所述第一参数修正量对所述卫星滤波参数进行更新，得到所述目标车辆在所述第一时刻的定位信息；
    获取所述目标车辆在第二时刻的运动状态，其中，所述第二时刻为出现在所述第一时刻之后的一个时刻；
    若所述目标车辆在所述第二时刻的运动状态满足定位修正条件，则获取所述运动状态所对应的约束矩阵，其中，所述约束矩阵表示在所述运动状态下满足的定位信息变化量；
    根据所述运动状态所对应的约束矩阵，确定所述目标车辆在所述第二时刻所对应的第二参数修正量；
    采用所述第二参数修正量对所述第一时刻的定位信息进行更新，得到所述目标车辆在所述第二时刻的定位信息。
  2. 根据权利要求1所述的方法，所述获取卫星滤波参数以及待处理数据，包括：
    向服务器发送星历下发请求，以使所述服务器响应于所述星历下发请求，获取第一时刻所对应的广播星历信息，其中，所述广播星历信息包括N个卫星所对应的星历参数，所述N为大于或等于1的整数；
    接收所述服务器发送的所述第一时刻所对应的广播星历信息；
    根据所述第一时刻所对应的广播星历信息确定在所述第一时刻所对应的所述卫星滤波参数；
    通过卫星定位设备获取所述第一时刻所对应的所述待处理数据。
  3. 根据权利要求1所述的方法，所述卫星滤波参数包括所述目标车辆在所述第一时刻所对应的位置信息，所述待处理数据包括所述目标车辆在所述第一时刻所对应的伪距观测值；
    所述根据所述卫星滤波参数以及所述待处理数据，确定所述目标车辆在所述第一时刻所对应的第一参数修正量，包括：
    获取所述第一时刻所对应的协方差矩阵；
    获取N个单位观测向量所对应的第一雅克比矩阵，其中，所述N个单位观测向量所包括的每个单位观测向量表示卫星与所述目标车辆之间连线的方向向量；
    获取所述第一时刻所对应的伪距测量误差矩阵；
    获取所述第一时刻所对应的第一增益矩阵；
    根据所述卫星滤波参数以及所述第一时刻所对应的伪距观测值，确定第一预测残差向 量；
    根据所述第一时刻所对应的协方差矩阵、所述第一雅克比矩阵、所述伪距测量误差矩阵、所述第一增益矩阵以及所述第一预测残差向量，确定所述目标车辆在所述第一时刻所对应的第一参数修正量。
  4. 根据权利要求1所述的方法，所述卫星滤波参数包括所述目标车辆在所述第一时刻所对应的速度信息，所述待处理数据包括所述目标车辆在所述第一时刻所对应的多普勒观测值；
    所述根据所述卫星滤波参数以及所述待处理数据，确定所述目标车辆在所述第一时刻所对应的第一参数修正量，包括：
    获取所述第一时刻所对应的协方差矩阵；
    获取N个单位观测向量所对应的第二雅克比矩阵，其中，所述N个单位观测向量所包括的每个单位观测向量表示卫星与所述目标车辆之间连线的方向向量；
    获取所述第一时刻所对应的多普勒测量误差矩阵；
    获取所述第一时刻所对应的第二增益矩阵；
    根据所述卫星滤波参数以及所述第一时刻所对应的多普勒观测值，确定第二预测残差向量；
    根据所述第一时刻所对应的协方差矩阵、所述第二雅克比矩阵、所述多普勒测量误差矩阵、所述第二增益矩阵以及所述第二预测残差向量，确定所述目标车辆在所述第一时刻所对应的第一参数修正量。
  5. 根据权利要求1所述的方法，所述卫星滤波参数包括所述目标车辆在所述第一时刻所对应的速度信息以及位置信息，所述待处理数据包括所述目标车辆在所述第一时刻所对应的伪距观测值以及多普勒观测值；
    所述根据所述卫星滤波参数以及所述待处理数据，确定所述目标车辆在所述第一时刻所对应的第一参数修正量，包括：
    获取所述第一时刻所对应的协方差矩阵；
    获取N个单位观测向量所对应的第一雅克比矩阵，其中，所述N个单位观测向量所包括的每个单位观测向量表示卫星与所述目标车辆之间连线的方向向量；
    获取所述第一时刻所对应的伪距测量误差矩阵；
    获取所述第一时刻所对应的第一增益矩阵；
    根据所述卫星滤波参数以及所述第一时刻所对应的伪距观测值，确定第一预测残差向量；
    根据所述第一时刻所对应的协方差矩阵、所述第一雅克比矩阵、所述伪距测量误差矩阵、所述第一增益矩阵以及所述第一预测残差向量，确定所述目标车辆在所述第一时刻所对应的目标参数修正量，其中，所述目标参数修正量用于更新所述卫星滤波参数；
    根据所述第一时刻所对应的协方差矩阵、所述第一增益矩阵以及所述第一雅克比矩阵，确定目标协方差矩阵；
    根据所述目标协方差矩阵，确定所述目标车辆在所述第一时刻所对应的第一参数修正 量。
  6. 根据权利要求5所述的方法，所述根据所述目标协方差矩阵，确定所述目标车辆在所述第一时刻所对应的第一参数修正量，包括：
    获取N个单位观测向量所对应的第二雅克比矩阵，其中，所述N个单位观测向量所包括的每个单位观测向量表示卫星与所述目标车辆之间连线的方向向量；
    获取所述第一时刻所对应的多普勒测量误差矩阵；
    获取所述第一时刻所对应的第二增益矩阵；
    根据所述卫星滤波参数以及所述第一时刻所对应的多普勒观测值，确定第二预测残差向量；
    根据所述目标协方差矩阵、所述第二雅克比矩阵、所述多普勒测量误差矩阵、所述第二增益矩阵以及所述第二预测残差向量，确定所述目标车辆在所述第一时刻所对应的第一参数修正量；
    所述采用所述第一参数修正量对所述卫星滤波参数进行更新，得到所述目标车辆在所述第一时刻的定位信息，包括：
    根据所述目标参数修正量以及所述卫星滤波参数，确定已更新卫星滤波参数，其中，所述已更新卫星滤波参数包括所述目标车辆在所述第一时刻所对应的已更新速度信息以及已更新位置信息；
    采用所述第一参数修正量对所述已更新卫星滤波参数进行更新，得到所述目标车辆在所述第一时刻的定位信息。
  7. 根据权利要求1所述的方法，所述采用所述第二参数修正量对所述第一时刻的定位信息进行更新，得到所述目标车辆在所述第二时刻的定位信息，包括：
    采用所述第二参数修正量对所述第一时刻的定位信息进行更新，得到待处理定位信息；
    根据所述第一时刻的定位信息以及第一权重值，确定第一定位信息；
    根据所述待处理定位信息以及第二权重值，确定第二定位信息；
    根据所述第一定位信息以及所述第二定位信息，确定所述目标车辆在所述第二时刻的定位信息。
  8. 根据权利要求1所述的方法，所述卫星滤波参数包括目标车辆在第一时刻所对应的位置信息以及速度信息；
    所述获取所述目标车辆在第二时刻的运动状态之前，所述方法还包括：
    获取所述卫星滤波参数所对应的位置置信因子以及速度置信因子，其中，所述位置置信因子表示所述目标车辆的位置精度，所述速度置信因子表示所述目标车辆的速度精度；
    获取可见卫星数量；
    若所述位置置信因子、所述速度置信因子以及所述可见卫星数量满足车辆约束条件，则确定执行所述获取所述目标车辆在第二时刻的运动状态的步骤。
  9. 根据权利要求1所述的方法，所述获取所述目标车辆在第二时刻的运动状态，包括：
    通过图像采集装置获取第一车载图像；
    通过所述图像采集装置获取第二车载图像，其中，所述第二车载图像与所述第一车载 图像为相邻两帧图像；
    对所述第一车载图像以及所述第二车载图像进行特征点匹配；
    根据特征点匹配结果确定所述目标车辆在所述第二时刻的运动状态。
  10. 根据权利要求1所述的方法，所述获取所述目标车辆在第二时刻的运动状态，包括：
    根据所述目标车辆所对应的方向盘摆位信息，确定所述目标车辆在所述第二时刻的运动状态；
    或者，
    基于路网匹配结果确定所述目标车辆在所述第二时刻的运动状态。
  11. 根据权利要求1至10中任一项所述的方法，所述获取所述目标车辆在第二时刻的运动状态之后，所述方法还包括：
    若所述目标车辆在所述第二时刻的运动状态为静止状态，则确定所述目标车辆在所述第二时刻的运动状态满足定位修正条件；
    所述获取所述运动状态所对应的约束矩阵，包括：
    构建所述静止状态所对应的约束矩阵；
    所述根据所述运动状态所对应的约束矩阵，确定所述目标车辆在所述第二时刻所对应的第二参数修正量，包括：
    获取所述第二时刻所对应的协方差矩阵；
    获取第一测量误差方差矩阵；
    获取所述第二时刻所对应的速度矩阵；
    获取所述第二时刻所对应的第三增益矩阵；
    根据所述第二时刻所对应的协方差矩阵、所述静止状态所对应的约束矩阵、所述第一测量误差方差矩阵、所述第二时刻所对应的速度矩阵以及所述第三增益矩阵，确定所述目标车辆在所述第二时刻所对应的第二参数修正量。
  12. 根据权利要求1至10中任一项所述的方法，所述获取所述目标车辆在第二时刻的运动状态之后，所述方法还包括：
    若所述目标车辆在所述第二时刻的运动状态为直线行驶状态，则确定所述目标车辆在所述第二时刻的运动状态满足定位修正条件；
    所述获取所述运动状态所对应的约束矩阵，包括：
    构建所述直线行驶状态所对应的约束矩阵；
    所述根据所述运动状态所对应的约束矩阵，确定所述目标车辆在所述第二时刻所对应的第二参数修正量，包括：
    获取所述第二时刻所对应的协方差矩阵；
    获取第二测量误差方差矩阵；
    获取运动方向差值，其中，所述运动方向差值为所述目标车辆在所述第二时刻的运动方向，与所述目标车辆在第三时刻的运动方向之间的差值，所述第三时刻为所述第二时刻的前一个时刻；
    获取所述第二时刻所对应的第四增益矩阵；
    根据所述第二时刻所对应的协方差矩阵、所述直线行驶状态所对应的约束矩阵、所述第二测量误差方差矩阵、所述运动方向差值以及所述第四增益矩阵，确定所述目标车辆在所述第二时刻所对应的第二参数修正量。
  13. 一种车辆定位装置，包括：
    获取模块，用于获取卫星滤波参数以及待处理数据，其中，所述卫星滤波参数包括时钟偏差以及时钟偏差变化率，且所述卫星滤波参数还包括目标车辆在第一时刻所对应的位置信息以及速度信息中至少一项，所述待处理数据包括所述目标车辆在所述第一时刻所对应的伪距观测值以及多普勒观测值中至少一项；
    确定模块，用于根据所述卫星滤波参数以及所述待处理数据，确定所述目标车辆在所述第一时刻所对应的第一参数修正量；
    更新模块，用于采用所述第一参数修正量对所述卫星滤波参数进行更新，得到所述目标车辆在所述第一时刻的定位信息；
    所述获取模块，还用于获取所述目标车辆在第二时刻的运动状态，其中，所述第二时刻为出现在所述第一时刻之后的一个时刻；
    所述获取模块，还用于若所述目标车辆在所述第二时刻的运动状态满足定位修正条件，则获取所述运动状态所对应的约束矩阵，其中，所述约束矩阵表示在所述运动状态下满足的定位信息变化量；
    所述确定模块，用于根据所述运动状态所对应的约束矩阵，确定所述目标车辆在所述第二时刻所对应的第二参数修正量；
    所述更新模块，用于采用所述第二参数修正量对所述第一时刻的定位信息进行更新，得到所述目标车辆在所述第二时刻的定位信息。
  14. 一种终端设备，包括：存储器、处理器以及总线系统；
    其中，所述存储器用于存储程序；
    所述处理器用于执行所述存储器中的程序，所述处理器用于根据程序代码中的指令执行权利要求1至12中任一项所述的方法；
    所述总线系统用于连接所述存储器以及所述处理器，以使所述存储器以及所述处理器进行通信。
  15. 一种计算机可读存储介质，所述存储介质用于存储计算机程序，所述计算机程序用于执行如权利要求1至12中任一项所述的方法。
  16. 一种包括指令的计算机程序产品，当其在计算机上运行时，使得所述计算机执行权利要求1至12中任一项所述的方法。
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