WO2021212517A1 - Procédé et système de positionnement et support d'enregistrement - Google Patents

Procédé et système de positionnement et support d'enregistrement Download PDF

Info

Publication number
WO2021212517A1
WO2021212517A1 PCT/CN2020/086867 CN2020086867W WO2021212517A1 WO 2021212517 A1 WO2021212517 A1 WO 2021212517A1 CN 2020086867 W CN2020086867 W CN 2020086867W WO 2021212517 A1 WO2021212517 A1 WO 2021212517A1
Authority
WO
WIPO (PCT)
Prior art keywords
positioning
signal
noise ratio
quality data
gnss
Prior art date
Application number
PCT/CN2020/086867
Other languages
English (en)
Chinese (zh)
Inventor
刘新俊
高翔
Original Assignee
深圳市大疆创新科技有限公司
Priority date (The priority date is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the date listed.)
Filing date
Publication date
Application filed by 深圳市大疆创新科技有限公司 filed Critical 深圳市大疆创新科技有限公司
Priority to PCT/CN2020/086867 priority Critical patent/WO2021212517A1/fr
Priority to CN202080005322.9A priority patent/CN112771411A/zh
Publication of WO2021212517A1 publication Critical patent/WO2021212517A1/fr

Links

Images

Classifications

    • GPHYSICS
    • G01MEASURING; TESTING
    • G01SRADIO 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
    • G01S19/00Satellite radio beacon positioning systems; Determining position, velocity or attitude using signals transmitted by such systems
    • G01S19/38Determining a navigation solution using signals transmitted by a satellite radio beacon positioning system
    • G01S19/39Determining 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
    • G01S19/42Determining position
    • GPHYSICS
    • G01MEASURING; TESTING
    • G01SRADIO 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
    • G01S19/00Satellite radio beacon positioning systems; Determining position, velocity or attitude using signals transmitted by such systems
    • G01S19/01Satellite radio beacon positioning systems transmitting time-stamped messages, e.g. GPS [Global Positioning System], GLONASS [Global Orbiting Navigation Satellite System] or GALILEO
    • G01S19/13Receivers
    • G01S19/35Constructional details or hardware or software details of the signal processing chain
    • G01S19/37Hardware or software details of the signal processing chain

Definitions

  • This application relates to the technical field of target positioning, and in particular to a positioning method, system and storage medium.
  • the UAV positioning system uses the Global Navigation Satellite System (GNSS) positioning results and the visual positioning results
  • GNSS Global Navigation Satellite System
  • weights need to be selected to ensure that the final positioning results are correct.
  • the evaluation scheme usually adopted is: first evaluate the GNSS positioning quality; when the GNSS positioning quality meets certain conditions, use it to verify the visual positioning results. There is a big difference between the two When, the visual positioning result is not used.
  • GNSS can generally be used for positioning outdoors, but the GNSS positioning accuracy is greatly affected by the convergence of the board and the scene, and is affected by multipath.
  • the positioning accuracy at the bottom of a narrow strip, near buildings, and deep well environments is poor or even abnormal.
  • the existing methods for evaluating the quality of GNSS positioning believe that the quality of GNSS positioning is very high. When using it to verify the visual positioning results, they choose not to use the visual positioning results and largely use the GNSS positioning results with poor actual positioning accuracy.
  • the drone exploded abnormally.
  • this application provides a positioning method, a positioning system, and a storage medium.
  • this application provides a positioning method, the method is suitable for a movable platform, and the method includes:
  • a positioning mode is determined, and the movable platform is controlled to move according to the determined positioning mode.
  • the present application provides a positioning system, the system is suitable for a mobile platform, and the system includes: a memory and a processor;
  • the memory is used to store a computer program
  • the processor is used to execute the computer program and when executing the computer program, implement the following steps:
  • a positioning mode is determined, and the movable platform is controlled to move according to the determined positioning mode.
  • the present application provides a computer-readable storage medium, the computer-readable storage medium stores a computer program, and when the computer program is executed by a processor, the processor implements the positioning method as described above.
  • the embodiments of the present application provide a positioning method, a positioning system, and a storage medium.
  • the positioning quality data corresponding to the positioning parameters is obtained by analyzing the GNSS positioning result data of the global navigation satellite system through positioning parameters;
  • the GNSS positioning result data is used to obtain the positioning quality data corresponding to the signal-to-noise ratio;
  • the final positioning of the GNSS positioning result data is determined according to the positioning quality data corresponding to the positioning parameters and the positioning quality data corresponding to the signal-to-noise ratio
  • Quality data Determine the positioning mode according to the final positioning quality data of the GNSS positioning result data, and control the movable platform to move according to the determined positioning mode.
  • the positioning quality of GNSS is also greatly affected by the current scene of the mobile platform, and is affected by multipath.
  • the positioning accuracy of GNSS in a narrow space Very poor or even abnormal, and the signal-to-noise ratio based on satellite signals in a long and narrow space changes significantly, so according to the positioning quality data corresponding to the positioning parameters obtained through the positioning parameter analysis and the signal-to-noise ratio based on the signal-to-noise ratio analysis of the satellite signals
  • Corresponding positioning quality data can obtain more detailed, more comprehensive and accurate final positioning quality data of GNSS positioning result data, which can be accurately analyzed in normal scenes and at the bottom of narrow areas, near buildings, deep well environments and other special scenes.
  • FIG. 1 is a schematic flowchart of an embodiment of a positioning method according to the present application
  • FIG. 2 is a schematic flowchart of another embodiment of the positioning method according to the present application.
  • Fig. 3 is a schematic structural diagram of an embodiment of the positioning system of the present application.
  • UAVs can generally use GNSS for positioning outdoors, but the GNSS positioning accuracy is greatly affected by the scene.
  • the positioning accuracy at the bottom of a narrow strip, near buildings, and deep well environments is poor or even abnormal.
  • the existing methods for evaluating the quality of GNSS positioning believe that the quality of GNSS positioning is very high.
  • the drone exploded abnormally.
  • the embodiment of the application analyzes the global navigation satellite system GNSS positioning result data through positioning parameters to obtain positioning quality data corresponding to the positioning parameters; analyzes the GNSS positioning result data based on the signal-to-noise ratio of satellite signals to obtain the corresponding signal-to-noise ratio
  • the positioning quality data; the final positioning quality data of the GNSS positioning result data is determined according to the positioning quality data corresponding to the positioning parameters and the positioning quality data corresponding to the signal-to-noise ratio; the final positioning according to the GNSS positioning result data Quality data, determine the positioning mode, and control the movable platform to move according to the determined positioning mode.
  • the positioning quality of GNSS is also greatly affected by the current scene of the mobile platform, and is affected by multipath.
  • the positioning accuracy of GNSS in a narrow space Very poor or even abnormal, and the signal-to-noise ratio based on satellite signals in a long and narrow space changes significantly, so according to the positioning quality data corresponding to the positioning parameters obtained through the positioning parameter analysis and the signal-to-noise ratio based on the signal-to-noise ratio analysis of the satellite signals
  • Corresponding positioning quality data can obtain more detailed, more comprehensive and accurate final positioning quality data of GNSS positioning result data, which can be accurately analyzed in normal scenes and at the bottom of narrow areas, near buildings, deep well environments and other special scenes.
  • Fig. 1 is a schematic flowchart of an embodiment of a positioning method according to the present application.
  • the method is applicable to a movable platform.
  • the movable platform may refer to various platforms that can move automatically or move under controlled conditions, for example: UAVs, vehicles, unmanned vehicles, ground robots, unmanned ships, etc.
  • the method includes: step S101, step S102, step S103, and step S104.
  • Step S101 Analyze global navigation satellite system GNSS positioning result data through positioning parameters to obtain positioning quality data corresponding to the positioning parameters.
  • the global navigation satellite system is based on the time-coded reception and processing of satellite signals to achieve positioning.
  • GNSS positioning is a very complicated process, and it is susceptible to interference from the outside world and its own errors.
  • the system has potential loopholes and problems, from information generation, uplink to satellite to signal transmission, to the receiver receiving and processing information.
  • the types of potential vulnerabilities and problems of global satellite navigation systems include system errors and navigation errors; system errors refer to those problems caused by GNSS ground and space systems, depending on the location of the satellite signal transmission; navigation errors are caused by environmental impact or receiver failure of.
  • System errors include satellite ephemeris error, satellite clock error, Selective Availability (SA, Selective Availability) interference error, hardware drift error, inter-frequency offset, orbital deviation, signal format abnormality, status information abnormality, reference coordinate error, etc. .
  • Navigation errors include multipath effects, pseudoranges and carrier phases, frequency deviations, ionospheric refraction errors, ionospheric correction errors, tropospheric refraction errors, signal reception errors, navigation information reading errors, receiver calculation errors, system errors, satellites Ephemeris error, satellite clock error, SA interference error, etc. The accumulation of these errors affects the positioning quality of GNSS.
  • the positioning parameter may refer to a parameter used to analyze the positioning quality of the GNSS positioning result data.
  • Positioning parameters include but are not limited to: number of searched satellites (number of searched satellites), positioning accuracy factor (such as geometric accuracy factor, relative positioning accuracy factor, spatial position accuracy factor, etc.), positioning position and speed consistency difference ( The consistency difference between positioning position and speed obtained by different positioning methods), positioning algorithm, specific navigation system, etc.
  • the positioning parameter may include at least one of the number of searched stars, the positioning accuracy factor, and the consistency difference between the positioning position and the speed.
  • step S101 analyzes global navigation satellite system GNSS positioning result data through positioning parameters to obtain positioning quality data corresponding to the positioning parameters, which may be analyzed through more than one positioning parameter to obtain the positioning The positioning quality data corresponding to the parameter.
  • step S101 analyzes global navigation satellite system GNSS positioning result data through positioning parameters to obtain positioning quality data corresponding to the positioning parameters. Specifically, it may be: analyzing the GNSS positioning result data through multiple positioning parameters to obtain Positioning quality data corresponding to the multiple positioning parameters.
  • Step S102 Analyze the GNSS positioning result data based on the signal-to-noise ratio of the satellite signal to obtain positioning quality data corresponding to the signal-to-noise ratio.
  • the signal-to-noise ratio refers to the ratio of signal to noise.
  • the signal-to-noise ratio based on the satellite signal in this embodiment may be based on factors that affect the signal-to-noise ratio of the satellite signal.
  • the signal-to-noise ratio of the satellite signal may be the signal-to-noise ratio and signal strength of the received satellite signal.
  • the signal-to-noise ratio of the satellite signal is usually more related to the current scenario of the mobile platform: in the open space, the signal-to-noise ratio of the satellite signal is usually larger, and the signal-to-noise ratio of the satellite signal in the long and narrow space changes significantly. Become smaller.
  • Analyzing the GNSS positioning result data based on the signal-to-noise ratio of the satellite signal can analyze and obtain positioning quality data corresponding to the signal-to-noise ratio in special scenarios such as the bottom of a narrow strip, near a building, and a deep well type environment.
  • step S101 and step S102.
  • Step S103 Determine the final positioning quality data of the GNSS positioning result data according to the positioning quality data corresponding to the positioning parameters and the positioning quality data corresponding to the signal-to-noise ratio.
  • step S103 is based on the positioning quality data corresponding to the positioning parameters.
  • the positioning quality data corresponding to the signal-to-noise ratio determines the final positioning quality data of the GNSS positioning result data, which may specifically be: positioning quality data corresponding to the signal-to-noise ratio and positioning corresponding to the multiple positioning parameters.
  • the quality data, the weight of the positioning quality data corresponding to the signal-to-noise ratio, and the weight of the positioning quality data corresponding to the multiple positioning parameters determine the final positioning quality data of the GNSS positioning result data.
  • the weight can be determined by experimental actual scene data.
  • the final positioning quality data of the GNSS positioning result data may be positioning quality data corresponding to the signal-to-noise ratio, positioning quality data corresponding to the multiple positioning parameters, and positioning quality data corresponding to the signal-to-noise ratio.
  • the weight and the weight of the positioning quality data corresponding to the multiple positioning parameters are multiplied by the result.
  • the positioning quality data corresponding to the multiple positioning parameters includes: positioning quality data corresponding to positioning parameter 1, positioning quality data corresponding to positioning parameter 2, positioning quality data 3 corresponding to positioning parameter 3, and the corresponding weights are respectively : Weight 1, weight 2, and weight 3;
  • the final positioning quality data of the GNSS positioning result data is equal to: positioning quality data corresponding to the signal-to-noise ratio * weight of positioning quality data corresponding to the signal-to-noise ratio * positioning quality data 1 * weight 1 *Positioning quality data 2*Weight 2*Positioning quality data 3*Weight 3.
  • the final positioning quality data of the GNSS positioning result data can also be obtained in other ways, and details are not described herein again.
  • the final positioning quality data of the GNSS positioning result data is determined based on the positioning quality data corresponding to the positioning parameters and the positioning quality data corresponding to the signal-to-noise ratio, this makes the final positioning quality data of the GNSS positioning result data better. Detailed, more comprehensive and more accurate.
  • Step S104 Determine a positioning mode according to the final positioning quality data of the GNSS positioning result data, and control the movable platform to move according to the determined positioning mode.
  • the embodiment of the application analyzes the global navigation satellite system GNSS positioning result data through positioning parameters to obtain positioning quality data corresponding to the positioning parameters; analyzes the GNSS positioning result data based on the signal-to-noise ratio of satellite signals to obtain the corresponding signal-to-noise ratio
  • the positioning quality data; the final positioning quality data of the GNSS positioning result data is determined according to the positioning quality data corresponding to the positioning parameters and the positioning quality data corresponding to the signal-to-noise ratio; the final positioning according to the GNSS positioning result data Quality data, determine the positioning mode, and control the movable platform to move according to the determined positioning mode.
  • the positioning quality of GNSS is also greatly affected by the current scene of the mobile platform, and is affected by multipath.
  • the positioning accuracy of GNSS in a narrow space Very poor or even abnormal, and the signal-to-noise ratio based on satellite signals in a long and narrow space changes significantly, so according to the positioning quality data corresponding to the positioning parameters obtained through the positioning parameter analysis and the signal-to-noise ratio based on the signal-to-noise ratio analysis of the satellite signals
  • Corresponding positioning quality data can obtain more detailed, more comprehensive and accurate final positioning quality data of GNSS positioning result data, which can be accurately analyzed in normal scenes and at the bottom of narrow areas, near buildings, deep well environments and other special scenes.
  • step S102 The specific details of step S102 are described in detail below.
  • step S102 analyzes the GNSS positioning result data based on the signal-to-noise ratio of the satellite signal to obtain the positioning quality data corresponding to the signal-to-noise ratio, which may specifically be: using the highest signal of the currently searched satellite signal
  • the noise ratio analyzes the GNSS positioning result data to obtain first positioning quality data corresponding to the signal-to-noise ratio.
  • the highest signal-to-noise ratio of the satellite signals currently searched for the same type of satellite signal receiver should be the same, but in special scenarios such as the bottom of a narrow strip, near buildings, and deep well environments Even if the number of satellites searched is relatively normal, the highest signal-to-noise ratio of the satellite signals currently searched will be lower than the normal scene due to the obvious multipath of the environment and the limitations of the satellite search.
  • This method is relatively simple and rough.
  • step S102 analyzes the GNSS positioning result data based on the signal-to-noise ratio of the satellite signal to obtain positioning quality data corresponding to the signal-to-noise ratio, which may specifically be: analyzing the GNSS positioning by using the first difference value From the result data, the second positioning quality data corresponding to the signal-to-noise ratio is obtained, and the first difference is the average signal-to-noise ratio of the highest four positioning satellites and the highest signal-to-noise ratio of the currently searched satellite signals Difference.
  • the average signal-to-noise ratio of the highest four positioning satellites may be the average signal-to-noise ratio of the highest four satellites used for positioning. There are multiple satellites that have been searched. Sort these satellites according to the strength of the satellite signals from strong to weak. The top four satellites are used for positioning. The satellite signals of these four satellites are averaged to get the highest four. The average signal-to-noise ratio of the positioning satellites.
  • the average signal-to-noise ratio of the highest four positioning satellites of the same type of satellite signal receiver should be the same, but in special scenarios such as the bottom of a narrow strip, near buildings, and deep well environments, Even if the number of satellites searched is relatively normal, the average signal-to-noise ratio of the highest four positioning satellites will be lower than the normal scene due to the obvious multipath of the environment and the limitations of the satellite search.
  • the first difference is the difference between the average signal-to-noise ratio of the highest four positioning satellites and the highest signal-to-noise ratio of the currently searched satellite signal.
  • the first difference of the same type of satellite signal receiver should be the same, but in special scenarios such as the bottom of a narrow strip, near a building, or a deep well environment, even if the number of satellites searched is relative There is no abnormality in the normal scene, but due to the obvious multipath of the environment and the limitations of star search, its first difference will be lower than that of the normal scene.
  • the first difference is relatively stable, and this method is more Simple. Relative to using a single signal-to-noise ratio for analysis, the second positioning quality data is relatively stable.
  • step S102 analyzes the GNSS positioning result data based on the signal-to-noise ratio of the satellite signal to obtain positioning quality data corresponding to the signal-to-noise ratio, which may specifically be: analyzing the GNSS positioning by using a second difference value From the result data, the third positioning quality data corresponding to the signal-to-noise ratio is obtained, and the second difference is the difference between the average signal-to-noise ratio of all positioning satellites and the highest signal-to-noise ratio of the currently searched satellite signal .
  • the average signal-to-noise ratio of all positioning satellites may be the average signal-to-noise ratio of all satellites used for positioning. There are currently multiple satellites that have been searched. Sort these satellites according to the strength of the satellite signal from strong to weak, determine the top satellite for positioning, and average the satellite signals of all satellites used for positioning. Obtain the average signal-to-noise ratio of all positioning satellites.
  • the average signal-to-noise ratio of all positioning satellites of the same type of satellite signal receiver should be the same.
  • the number of satellites is not abnormal compared to the normal scene, but due to the obvious multipath of the environment and the limitations of satellite search, the average signal-to-noise ratio of all its positioning satellites will be lower than that of the normal scene.
  • the second difference is the difference between the average signal-to-noise ratio of all positioning satellites and the highest signal-to-noise ratio of the currently searched satellite signal.
  • the second difference of the same type of satellite signal receiver should be the same, but in special scenarios such as the bottom of a narrow strip, near a building, a deep well environment, etc., even if the number of satellites searched is relative There is no abnormality in the normal scene, but due to the obvious multipath of the environment and the limitations of star search, its second difference will be lower than the normal scene.
  • This embodiment uses the average signal-to-noise ratio of all positioning satellites, it can reduce the fluctuations in the signal-to-noise ratio of a certain satellite or several satellites caused by accidental factors to a certain extent, and the second difference is relatively stable. , This method is relatively simple. Relative to using a single signal-to-noise ratio for analysis, the third positioning quality data is relatively stable.
  • step S102 analyzes the GNSS positioning result data based on the signal-to-noise ratio of the satellite signal to obtain the positioning quality data corresponding to the signal-to-noise ratio. Specifically, it may be: using the highest satellite signal currently searched for. At least two of the signal-to-noise ratio, the first difference value and the second difference value are analyzed, and the GNSS positioning result data is analyzed to obtain fourth positioning quality data corresponding to the signal-to-noise ratio.
  • the first difference value is the highest four The difference between the average signal-to-noise ratio of the positioning satellites and the highest signal-to-noise ratio of the currently searched satellite signal
  • the second difference is the average signal-to-noise ratio of all positioning satellites and the current searched The difference between the highest signal-to-noise ratio of the received satellite signals.
  • step S102 analyzes the GNSS positioning result data based on the signal-to-noise ratio of the satellite signal to obtain the positioning quality data corresponding to the signal-to-noise ratio.
  • the highest signal-to-noise ratio and the first difference of the currently searched satellite signal can be used.
  • the second difference value analyze the GNSS positioning result data to obtain fourth positioning quality data corresponding to the signal-to-noise ratio. In this way, the fourth positioning quality data can be made more stable and comprehensive.
  • step S104 The specific details of step S104 are described in detail below.
  • step S104 determines a positioning mode according to the final positioning quality data of the GNSS positioning result data, and controls the movable platform to move according to the determined positioning mode, which may include: sub-step S1041 Sub-step S1042 and sub-step S1043.
  • Sub-step S1041 Determine whether the final positioning quality data of the GNSS positioning result data is greater than or equal to the positioning quality threshold.
  • Sub-step S1042 When the final positioning quality data of the GNSS positioning result data is greater than or equal to the positioning quality threshold, determine that the positioning mode is GNSS positioning, and control the movable platform to move according to the GNSS positioning positioning mode.
  • Sub-step S1043 When the final positioning quality data of the GNSS positioning result data is less than the positioning quality threshold, determine that the positioning mode is to use other systems for positioning, and control the movable platform to move according to the positioning mode of other systems for positioning.
  • the positioning quality threshold may be determined according to actual applications, and specifically may be determined by the mobile platform's quality requirements for positioning, the quality requirements for GNSS positioning, and so on.
  • the final positioning quality data of the GNSS positioning result data is less than the positioning quality threshold
  • other systems can be used for positioning, which can ensure that the movable platform is at the bottom of a narrow zone, near a building, in a deep well environment and other special scenarios. Normal movement can avoid abnormal movement of the movable platform.
  • the positioning quality threshold can also be divided into multiple levels, and different positioning methods are used for the positioning quality thresholds at different levels. For example: when the final positioning quality data of the GNSS positioning result data is greater than or equal to the first-level positioning quality threshold, it is determined that the positioning mode is GNSS positioning; when the final positioning quality data of the GNSS positioning result data is less than the first-level positioning quality threshold When the positioning quality threshold is greater than or equal to the second-level positioning quality threshold, it is determined that the positioning method is to use GNSS and other systems for positioning; when the final positioning quality data of the GNSS positioning result data is less than the second-level positioning quality threshold, Determine the positioning method to use other systems for positioning.
  • the movable platform includes an unmanned aerial vehicle.
  • the other system includes a visual positioning system.
  • the positioning accuracy of the visual positioning system is very high, the results produced are reliable, the stability is strong, and the positioning speed is very fast, especially suitable for positioning in special scenes such as the bottom of a narrow zone, near buildings, and deep well environments.
  • the visual positioning system is a positioning system in which binocular vision and an inertial measurement unit IMU are tightly coupled. Binocular vision and inertial measurement unit IMU's perception methods are complementary. In this way, the positioning system with binocular vision and IMU tightly coupled has more advantages in positioning accuracy and robustness, thereby ensuring the reliability of positioning results .
  • the embodiment of the present application also provides another positioning method, which is suitable for a movable platform, and the movable platform includes a positioning parameter analysis module, a signal-to-noise ratio analysis module, a positioning quality analysis module, and a control module.
  • the content of the positioning method in this embodiment is basically the same as the content of the above-mentioned positioning method.
  • the above-mentioned method section which will not be repeated here. include:
  • the positioning parameter analysis module analyzes global navigation satellite system GNSS positioning result data through positioning parameters to obtain positioning quality data corresponding to the positioning parameters.
  • the signal-to-noise ratio analysis module analyzes the GNSS positioning result data based on the signal-to-noise ratio of the satellite signal to obtain positioning quality data corresponding to the signal-to-noise ratio.
  • the positioning quality analysis module determines the final positioning quality data of the GNSS positioning result data according to the positioning quality data corresponding to the positioning parameters and the positioning quality data corresponding to the signal-to-noise ratio.
  • the control module determines the positioning mode according to the final positioning quality data of the GNSS positioning result data, and controls the movable platform to move according to the determined positioning mode.
  • the signal-to-noise ratio analysis module uses the highest signal-to-noise ratio of the currently searched satellite signal to analyze the GNSS positioning result data to obtain the first positioning quality data corresponding to the signal-to-noise ratio.
  • the signal-to-noise ratio analysis module analyzes the GNSS positioning result data by using the first difference value to obtain the second positioning quality data corresponding to the signal-to-noise ratio, and the first difference value is the average of the highest four positioning satellites The difference between the signal-to-noise ratio and the highest signal-to-noise ratio of the currently searched satellite signal.
  • the signal-to-noise ratio analysis module analyzes the GNSS positioning result data by using a second difference value to obtain third positioning quality data corresponding to the signal-to-noise ratio, and the second difference value is the average signal-to-noise value of all positioning satellites The difference between the ratio and the highest signal-to-noise ratio of the currently searched satellite signal.
  • the signal-to-noise ratio analysis module uses at least two of the highest signal-to-noise ratio, the first difference and the second difference of the currently searched satellite signals to analyze the GNSS positioning result data to obtain the signal
  • the fourth positioning quality data corresponding to the noise ratio the first difference is the difference between the average signal-to-noise ratio of the highest four positioning satellites and the highest signal-to-noise ratio of the currently searched satellite signals
  • the The second difference is the difference between the average signal-to-noise ratio of all positioning satellites and the highest signal-to-noise ratio of the currently searched satellite signal.
  • the positioning parameter analysis module analyzes the GNSS positioning result data through a plurality of positioning parameters to obtain positioning quality data corresponding to the plurality of positioning parameters.
  • the positioning quality analysis module is based on the positioning quality data corresponding to the signal-to-noise ratio, the positioning quality data corresponding to the multiple positioning parameters, the weight of the positioning quality data corresponding to the signal-to-noise ratio, and the multiple positioning
  • the weight of the positioning quality data corresponding to the parameter determines the final positioning quality data of the GNSS positioning result data.
  • the positioning parameter includes at least one of the number of searched stars, the positioning accuracy factor, and the consistency difference between the positioning position and the speed.
  • the control module determines that the positioning method is GNSS positioning, and controls the movable platform to perform positioning in accordance with the GNSS positioning method Movement; when the final positioning quality data of the GNSS positioning result data is less than the positioning quality threshold, the positioning mode is determined to use other systems for positioning, and the movable platform is controlled to move according to the positioning mode of other systems.
  • the movable platform includes an unmanned aerial vehicle.
  • the other system includes a visual positioning system.
  • the visual positioning system is a positioning system in which binocular vision and an inertial measurement unit IMU are tightly coupled. Binocular vision and inertial measurement unit IMU's perception methods are complementary. In this way, the positioning system with binocular vision and IMU tightly coupled has more advantages in positioning accuracy and robustness, thereby ensuring the reliability of positioning results .
  • FIG 3 is a schematic structural diagram of an embodiment of the positioning system of the present application. It should be noted that the system of this embodiment can implement the steps in the above positioning method. For detailed descriptions of related content, please refer to the above method section. I won't repeat it again.
  • the system 100 is suitable for a mobile platform.
  • the system 100 includes: a memory 1 and a processor 2; the memory 1 and the processor 2 are connected by a bus.
  • the processor 2 may be a micro control unit, a central processing unit, or a digital signal processor, and so on.
  • the memory 1 can be a Flash chip, a read-only memory, a magnetic disk, an optical disk, a U disk or a mobile hard disk, etc.
  • the memory 1 is used to store a computer program; the processor 2 is used to execute the computer program and when the computer program is executed, the following steps are implemented:
  • the processor executes the computer program, the following steps are implemented: use the highest signal-to-noise ratio of the currently searched satellite signal to analyze the GNSS positioning result data to obtain the first positioning corresponding to the signal-to-noise ratio Quality data.
  • the processor executes the computer program, the following steps are implemented: use the first difference to analyze the GNSS positioning result data to obtain the second positioning quality data corresponding to the signal-to-noise ratio, and the first difference
  • the value is the difference between the average signal-to-noise ratio of the highest four positioning satellites and the highest signal-to-noise ratio of the currently searched satellite signals.
  • the processor when the processor executes the computer program, it implements the following steps: analyze the GNSS positioning result data using a second difference value to obtain third positioning quality data corresponding to the signal-to-noise ratio, and the second difference
  • the value is the difference between the average signal-to-noise ratio of all positioning satellites and the highest signal-to-noise ratio of the currently searched satellite signal.
  • the processor executes the computer program, the following steps are implemented: using at least two of the highest signal-to-noise ratio, the first difference, and the second difference of the currently searched satellite signals to analyze the GNSS positioning result data to obtain fourth positioning quality data corresponding to the signal-to-noise ratio, and the first difference is the average signal-to-noise ratio of the highest four positioning satellites and the highest signal-to-noise ratio of the currently searched satellite signal
  • the second difference is the difference between the average signal-to-noise ratio of all positioning satellites and the highest signal-to-noise ratio of the currently searched satellite signal.
  • the processor executes the computer program, the following steps are implemented: analyzing the GNSS positioning result data through a plurality of positioning parameters to obtain positioning quality data corresponding to the plurality of positioning parameters.
  • the processor executes the computer program, the following steps are implemented: according to the positioning quality data corresponding to the signal-to-noise ratio, the positioning quality data corresponding to the multiple positioning parameters, and the positioning corresponding to the signal-to-noise ratio
  • the weight of the quality data and the weight of the positioning quality data corresponding to the multiple positioning parameters determine the final positioning quality data of the GNSS positioning result data.
  • the positioning parameter includes at least one of the number of searched stars, the positioning accuracy factor, and the consistency difference between the positioning position and the speed.
  • the processor executes the computer program, the following steps are implemented: when the final positioning quality data of the GNSS positioning result data is greater than or equal to the positioning quality threshold, determining that the positioning mode is to use GNSS for positioning, and controlling all The movable platform moves according to the GNSS positioning method; when the final positioning quality data of the GNSS positioning result data is less than the positioning quality threshold, the positioning method is determined to be positioning by other systems, and the movable platform is controlled to follow Other systems perform positioning in the positioning mode to move.
  • the movable platform includes an unmanned aerial vehicle.
  • the other system includes a visual positioning system.
  • the visual positioning system is a positioning system in which binocular vision and inertial measurement unit IMU are tightly coupled.
  • the present application also provides a computer-readable storage medium, the computer-readable storage medium stores a computer program, and when the computer program is executed by a processor, the processor implements the positioning method as described in any one of the preceding items.
  • the relevant content please refer to the above method content section, which will not be repeated here.
  • the computer-readable storage medium may be an internal storage unit of the aforementioned system, such as a hard disk or a memory.
  • the computer-readable storage medium may also be an external storage device of the aforementioned system, such as an equipped plug-in hard disk, a smart memory card, a secure digital card, a flash memory card, and so on.

Abstract

Un procédé et un système de positionnement, ainsi qu'un support d'enregistrement, le procédé consistant : à analyser des données de résultat de positionnement de système mondial de navigation par satellite (GNSS) au moyen de paramètres de positionnement afin d'obtenir des données de qualité de positionnement correspondant aux paramètres de positionnement (S101) ; à analyser des données de résultat de positionnement GNSS en fonction du rapport signal sur bruit d'un signal satellite afin d'obtenir des données de qualité de positionnement correspondant au rapport signal sur bruit (S102) ; en fonction des données de qualité de positionnement correspondant aux paramètres de positionnement et des données de qualité de positionnement correspondant au rapport signal sur bruit, à déterminer des données de qualité de positionnement final des données de résultat de positionnement GNSS (S103) ; et à déterminer un mode de positionnement en fonction des données de qualité de positionnement finales des données de résultat de positionnement GNSS, et à commander le déplacement d'une plateforme mobile en fonction du mode de positionnement déterminé (S104).
PCT/CN2020/086867 2020-04-24 2020-04-24 Procédé et système de positionnement et support d'enregistrement WO2021212517A1 (fr)

Priority Applications (2)

Application Number Priority Date Filing Date Title
PCT/CN2020/086867 WO2021212517A1 (fr) 2020-04-24 2020-04-24 Procédé et système de positionnement et support d'enregistrement
CN202080005322.9A CN112771411A (zh) 2020-04-24 2020-04-24 定位方法、系统及存储介质

Applications Claiming Priority (1)

Application Number Priority Date Filing Date Title
PCT/CN2020/086867 WO2021212517A1 (fr) 2020-04-24 2020-04-24 Procédé et système de positionnement et support d'enregistrement

Publications (1)

Publication Number Publication Date
WO2021212517A1 true WO2021212517A1 (fr) 2021-10-28

Family

ID=75699551

Family Applications (1)

Application Number Title Priority Date Filing Date
PCT/CN2020/086867 WO2021212517A1 (fr) 2020-04-24 2020-04-24 Procédé et système de positionnement et support d'enregistrement

Country Status (2)

Country Link
CN (1) CN112771411A (fr)
WO (1) WO2021212517A1 (fr)

Cited By (2)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN114338911A (zh) * 2021-12-14 2022-04-12 青岛海信移动通信技术股份有限公司 适用于终端设备的定位方法和终端设备
WO2024046341A1 (fr) * 2022-08-30 2024-03-07 广州导远电子科技有限公司 Procédé et système de détection d'intégrité pour données de navigation intégrées

Families Citing this family (1)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN114079858A (zh) * 2021-10-25 2022-02-22 摩拜(北京)信息技术有限公司 电子设备的定位方法、装置及存储介质

Citations (7)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
US20080071476A1 (en) * 2006-09-19 2008-03-20 Takayuki Hoshizaki Vehicle dynamics conditioning method on MEMS based integrated INS/GPS vehicle navigation system
CN101403620A (zh) * 2008-09-10 2009-04-08 深圳市同洲电子股份有限公司 导航装置及方法
CN101762805A (zh) * 2008-07-02 2010-06-30 凹凸电子(武汉)有限公司 组合导航系统以及导航方法
CN102103210A (zh) * 2009-12-17 2011-06-22 中国石油大学(北京) 一种卫星导航系统性能评估系统
CN106896391A (zh) * 2017-03-14 2017-06-27 北京京东尚科信息技术有限公司 无人机的定位方法及装置
CN107655474A (zh) * 2017-10-11 2018-02-02 上海展扬通信技术有限公司 一种基于智能终端的导航方法及导航系统
CN108759835A (zh) * 2018-05-04 2018-11-06 华东交通大学 一种定位方法、装置、可读存储介质及移动终端

Family Cites Families (6)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
RU2385469C1 (ru) * 2008-08-25 2010-03-27 ЗАО "ВНИИРА-Навигатор" Способ посадки летательных аппаратов с использованием спутниковой навигационной системы
WO2014054044A1 (fr) * 2012-10-04 2014-04-10 Ramot At Tel-Aviv University Ltd. Procédé et système d'estimation de position
WO2017066915A1 (fr) * 2015-10-20 2017-04-27 深圳市大疆创新科技有限公司 Procédé et dispositif de mesure de positionnement en navigation satellitaire et véhicule aérien sans pilote
CN205643716U (zh) * 2016-05-14 2016-10-12 四川中卫北斗科技有限公司 一种导航信号接收机
CN109470256A (zh) * 2017-09-07 2019-03-15 高德信息技术有限公司 一种定位方法及装置
CN110832418A (zh) * 2018-11-29 2020-02-21 深圳市大疆创新科技有限公司 无人飞行器控制方法、控制装置及无人飞行器

Patent Citations (7)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
US20080071476A1 (en) * 2006-09-19 2008-03-20 Takayuki Hoshizaki Vehicle dynamics conditioning method on MEMS based integrated INS/GPS vehicle navigation system
CN101762805A (zh) * 2008-07-02 2010-06-30 凹凸电子(武汉)有限公司 组合导航系统以及导航方法
CN101403620A (zh) * 2008-09-10 2009-04-08 深圳市同洲电子股份有限公司 导航装置及方法
CN102103210A (zh) * 2009-12-17 2011-06-22 中国石油大学(北京) 一种卫星导航系统性能评估系统
CN106896391A (zh) * 2017-03-14 2017-06-27 北京京东尚科信息技术有限公司 无人机的定位方法及装置
CN107655474A (zh) * 2017-10-11 2018-02-02 上海展扬通信技术有限公司 一种基于智能终端的导航方法及导航系统
CN108759835A (zh) * 2018-05-04 2018-11-06 华东交通大学 一种定位方法、装置、可读存储介质及移动终端

Cited By (3)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN114338911A (zh) * 2021-12-14 2022-04-12 青岛海信移动通信技术股份有限公司 适用于终端设备的定位方法和终端设备
CN114338911B (zh) * 2021-12-14 2023-08-08 青岛海信移动通信技术有限公司 适用于终端设备的定位方法和终端设备
WO2024046341A1 (fr) * 2022-08-30 2024-03-07 广州导远电子科技有限公司 Procédé et système de détection d'intégrité pour données de navigation intégrées

Also Published As

Publication number Publication date
CN112771411A (zh) 2021-05-07

Similar Documents

Publication Publication Date Title
WO2021212517A1 (fr) Procédé et système de positionnement et support d'enregistrement
JP6086901B2 (ja) 複数のrtkエンジンを有するgnss測量受信機
US10551475B2 (en) Method of detecting abnormality in unmanned aircraft control system and abnormality detector
Bhatti et al. Integrity of an integrated GPS/INS system in the presence of slowly growing errors. Part I: A critical review
CN112782728B (zh) 一种基于惯性辅助的天线阵欺骗干扰信号检测方法
JP6714339B2 (ja) 衛星シグマを平均し、除外した衛星測定値を差分補正および完全性監視に再入するためのシステムおよび方法
CN109581445B (zh) 一种基于北斗星座的araim子集选择方法及系统
US11061143B2 (en) Global navigation satellite system, navigation terminal, navigation method and program
GB2462926A (en) GPS multipath reduction
EP2806289A1 (fr) Module, dispositif et procédé de positionnement
US20150309181A1 (en) Method for providing a gnss signal
CN108549062B (zh) 一种用于海面搜索雷达的系统平台及多模型目标跟踪方法
CN110824423B (zh) 一种多无人车协同导航定位方法及系统
Das et al. An experimental study on relative and absolute pose graph fusion for vehicle localization
US20140180580A1 (en) Module, device and method for positioning
US20220244407A1 (en) Method for Generating a Three-Dimensional Environment Model Using GNSS Measurements
CN115561782B (zh) 一种基于奇偶矢量投影的组合导航中卫星故障检测方法
Bhamidipati et al. Robust gps-vision localization via integrity-driven landmark attention
EP2813864A2 (fr) Récepteurs et procédés de navigation multimode
CN113917506A (zh) 模糊度固定方法、装置、电子设备及自动驾驶设备
CN113848570A (zh) 基于非高斯分布的自适应实时多径消除及抗差定位方法
KR102270339B1 (ko) 고안전성 rtk-gnss의 초기 준비시간 단축 방법 및 시스템
CN117607910B (zh) 一种基于矢量跟踪新息矢量的欺骗检测方法及系统
RU198994U1 (ru) Устройство определения факта искажения навигационного поля и идентификации помехового воздействия на приемник роботизированного беспилотного летательного аппарата
KR102572546B1 (ko) 단일 주파수 수신기에서 다중 채널에서 발생하는 신호의 차이를 감지하는 장치 및 방법

Legal Events

Date Code Title Description
121 Ep: the epo has been informed by wipo that ep was designated in this application

Ref document number: 20932816

Country of ref document: EP

Kind code of ref document: A1

NENP Non-entry into the national phase

Ref country code: DE

122 Ep: pct application non-entry in european phase

Ref document number: 20932816

Country of ref document: EP

Kind code of ref document: A1