CN113791435A - GNSS signal abnormal value detection method and device, electronic equipment and storage medium - Google Patents
GNSS signal abnormal value detection method and device, electronic equipment and storage medium Download PDFInfo
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- CN113791435A CN113791435A CN202111366021.1A CN202111366021A CN113791435A CN 113791435 A CN113791435 A CN 113791435A CN 202111366021 A CN202111366021 A CN 202111366021A CN 113791435 A CN113791435 A CN 113791435A
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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
- G01S19/01—Satellite radio beacon positioning systems transmitting time-stamped messages, e.g. GPS [Global Positioning System], GLONASS [Global Orbiting Navigation Satellite System] or GALILEO
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- G01S19/35—Constructional details or hardware or software details of the signal processing chain
- G01S19/37—Hardware or software details of the signal processing chain
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- G06F—ELECTRIC DIGITAL DATA PROCESSING
- G06F16/00—Information retrieval; Database structures therefor; File system structures therefor
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Abstract
The application discloses a method and a device for detecting abnormal values of GNSS signals, electronic equipment and a storage medium, wherein the method comprises the following steps: obtaining current positioning information of a self-vehicle; according to the current positioning information of the self-vehicle, acquiring a local high-precision map within a preset range and other vehicle positioning information corresponding to the self-vehicle; determining an effective position area of the GNSS signal according to the current positioning information of the self-vehicle, the local high-precision map and other vehicle positioning information corresponding to the self-vehicle; and detecting a GNSS signal abnormal value according to the effective position area of the GNSS signal. According to the GNSS signal abnormal value detection method, on the basis of traditional chi-square detection, the GNSS signal abnormal value can be further detected by using the data of the high-precision map and the data sensed by the visual recognition equipment, so that the GNSS signal abnormal value can be corrected or eliminated according to the detection result, and the rationality and the reliability of the positioning track are improved.
Description
Technical Field
The present disclosure relates to the field of vehicle positioning technologies, and in particular, to a method and an apparatus for detecting an abnormal value of a GNSS signal, an electronic device, and a storage medium.
Background
In a traditional combined Navigation algorithm, a kalman filter is used to fuse signal data of an IMU (Inertial Measurement Unit) with high frequency and signal data of a GNSS (Global Navigation Satellite System) with low frequency, the signal data of the IMU is used as a track deduction in a prediction stage, the signal data of the GNSS is used as an observed value to correct and update in an update stage, and abnormal chi-square detection is used to process the observed value when the observed value is fused, so as to ensure the stability of the filter.
However, chi-square detection has a good detection effect on abnormal GNSS signals with sudden changes, but cannot process abnormal GNSS signals with slow changes, so when abnormal GNSS signals with slow changes are encountered, the filter is biased by the signals, and the final positioning track deviates from a correct course.
Disclosure of Invention
The embodiment of the application provides a method and a device for detecting an abnormal value of a GNSS signal, electronic equipment and a storage medium, so that the abnormal value of the GNSS signal can be effectively detected, and the accuracy and the reliability of a positioning result can be improved.
The embodiment of the application adopts the following technical scheme:
in a first aspect, an embodiment of the present application provides a method for detecting an abnormal value of a GNSS signal, where the method includes:
obtaining current positioning information of a self-vehicle;
according to the current positioning information of the self-vehicle, acquiring a local high-precision map within a preset range and other vehicle positioning information corresponding to the self-vehicle;
determining an effective position area of the GNSS signal according to the current positioning information of the self-vehicle, the local high-precision map and other vehicle positioning information corresponding to the self-vehicle;
and detecting a GNSS signal abnormal value according to the effective position area of the GNSS signal.
Optionally, the current positioning information of the own vehicle includes a current position of the own vehicle, and the obtaining of the local high-precision map within the preset range according to the current positioning information of the own vehicle includes:
taking the current position of the self-vehicle as a starting point, and acquiring lane line information of a high-precision map within a preset range corresponding to the current position of the self-vehicle;
and constructing the local high-precision map according to the lane line information of the high-precision map in the preset range.
Optionally, the determining the effective location area of the GNSS signal according to the current location information of the own vehicle, the local high-precision map, and the other vehicle location information corresponding to the own vehicle includes:
projecting other vehicle positioning information corresponding to the own vehicle into the local high-precision map;
projecting other vehicle positioning information and lane line information in the local high-precision map by taking the current position of the own vehicle as an origin to obtain a 2D grid map;
determining a valid location area of the GNSS signals from the 2D grid map.
Optionally, the determining the valid location area of the GNSS signals from the 2D grid map comprises:
determining a vehicle area and a road edge area in the 2D grid map as invalid position areas according to vehicle position information and road line information at the road edge in the 2D grid map;
and taking the residual area outside the invalid position area in the 2D grid map as the valid position area of the GNSS signal.
Optionally, the detecting GNSS signal outliers from the valid location area of the GNSS signal comprises:
determining whether a current GNSS signal is within the valid location area;
if so, determining that the current GNSS signal is a normal GNSS signal and directly updating the Kalman filter by using the current GNSS signal;
if not, determining that the current GNSS signal is an abnormal GNSS signal, and not updating the Kalman filter, or after transversely translating the current GNSS signal to the position of the center line of the current lane, temporarily updating the error range of the GNSS signal by the transverse translation distance, and then updating the Kalman filter.
Optionally, if the current GNSS signal is an abnormal GNSS signal, the method further includes:
determining whether a plurality of GNSS signals can be continuously detected within a preset time period and are all in the effective position area;
and if so, determining that the GNSS signal is recovered to be normal.
Optionally, the preset range is determined by:
acquiring the current vehicle speed and/or the frequency of the GNSS signal;
and determining the preset range according to the current vehicle speed and/or the frequency of the GNSS signal.
In a second aspect, an embodiment of the present application further provides an apparatus for detecting an abnormal value of a GNSS signal, where the apparatus includes:
a first acquisition unit configured to acquire current positioning information of a host vehicle;
the second acquisition unit is used for acquiring a local high-precision map within a preset range and other vehicle positioning information corresponding to the self vehicle according to the current positioning information of the self vehicle;
the first determining unit is used for determining an effective position area of the GNSS signal according to the current positioning information of the self-vehicle, the local high-precision map and other vehicle positioning information corresponding to the self-vehicle;
and the detection unit is used for detecting the abnormal value of the GNSS signal according to the effective position area of the GNSS signal.
In a third aspect, an embodiment of the present application further provides an electronic device, including:
a processor; and
a memory arranged to store computer executable instructions that, when executed, cause the processor to perform any of the methods described above.
In a fourth aspect, embodiments of the present application further provide a computer-readable storage medium storing one or more programs that, when executed by an electronic device including a plurality of application programs, cause the electronic device to perform any of the methods described above.
The embodiment of the application adopts at least one technical scheme which can achieve the following beneficial effects: according to the detection method of the GNSS signal abnormal value, the current positioning information of the own vehicle is firstly obtained; then, according to the current positioning information of the own vehicle, a local high-precision map within a preset range and other vehicle positioning information corresponding to the own vehicle are obtained; then determining an effective position area of the GNSS signal according to the current positioning information of the self-vehicle, a local high-precision map and other vehicle positioning information corresponding to the self-vehicle; and finally, detecting the abnormal value of the GNSS signal according to the effective position area of the GNSS signal. According to the GNSS signal abnormal value detection method, on the basis of traditional chi-square detection, the GNSS signal abnormal value can be further detected by using the data of the high-precision map and the data sensed by the visual recognition equipment, so that the GNSS signal abnormal value can be corrected or eliminated according to the detection result, and the rationality and the reliability of the positioning track are improved.
Drawings
The accompanying drawings, which are included to provide a further understanding of the application and are incorporated in and constitute a part of this application, illustrate embodiment(s) of the application and together with the description serve to explain the application and not to limit the application. In the drawings:
FIG. 1 is a flowchart illustrating a method for detecting outliers of GNSS signals according to an embodiment of the present invention;
FIG. 2 is a schematic diagram illustrating an apparatus for detecting an abnormal GNSS signal value according to an embodiment of the present invention;
fig. 3 is a schematic structural diagram of an electronic device in an embodiment of the present application.
Detailed Description
In order to make the objects, technical solutions and advantages of the present application more apparent, the technical solutions of the present application will be described in detail and completely with reference to the following specific embodiments of the present application and the accompanying drawings. It should be apparent that the described embodiments are only some of the embodiments of the present application, and not all of the embodiments. All other embodiments, which can be derived by a person skilled in the art from the embodiments given herein without making any creative effort, shall fall within the protection scope of the present application.
The technical solutions provided by the embodiments of the present application are described in detail below with reference to the accompanying drawings.
An embodiment of the present invention provides a method for detecting an abnormal value of a GNSS signal, as shown in fig. 1, which provides a flowchart of the method for detecting an abnormal value of a GNSS signal in an embodiment of the present invention, and the method at least includes the following steps S110 to S140:
and step S110, acquiring the current positioning information of the self-vehicle.
In the embodiment of the application, when the GNSS signal abnormal value is detected, the current positioning information of the own vehicle needs to be acquired first, and in a combined navigation scenario, the current positioning information may be the current positioning information of the own vehicle derived by the IMU inertia measurement unit in a prediction stage, and specifically may include the current position and the motion direction of the own vehicle.
And step S120, acquiring a local high-precision map within a preset range and other vehicle positioning information corresponding to the self vehicle according to the current positioning information of the self vehicle.
After the current positioning information of the own vehicle is obtained, a local high-precision map within a certain range corresponding to the own vehicle and positioning information of other vehicles around the own vehicle, which is identified by the visual identification device of the own vehicle, need to be obtained by taking the current positioning information of the own vehicle as a reference, and the positioning information of other vehicles may specifically include the current position and the moving direction of other vehicles.
Step S130, determining an effective position area of the GNSS signal according to the current positioning information of the self-vehicle, the local high-precision map and the positioning information of other vehicles corresponding to the self-vehicle.
And then, according to the current positioning information of the self-vehicle, the local high-precision map corresponding to the self-vehicle and the positioning information of other vehicles around the self-vehicle, a position area in which the GNSS signals of the self-vehicle possibly appear, namely an effective position area, can be further determined.
Step S140 is to detect an abnormal GNSS signal value according to the valid location area of the GNSS signal.
After the valid location area is determined, the valid location area may be used to detect whether the current positioning abnormality is abnormal, for example, if the current GNSS signal is not located in the valid location area, it is indicated that the GNSS signal is present at a location where it is not possible to present, and therefore, the current GNSS signal may be considered as an abnormal GNSS signal value, so as to implement detection of the abnormal signal.
According to the GNSS signal abnormal value detection method, on the basis of traditional chi-square detection, the GNSS signal abnormal value can be further detected by using the data of the high-precision map and the data sensed by the visual recognition equipment, so that the GNSS signal abnormal value can be corrected or eliminated according to the detection result, and the rationality and the reliability of the positioning track are improved.
In one embodiment of the present application, the preset range is determined by: acquiring the current vehicle speed and/or the frequency of the GNSS signal; and determining the preset range according to the current vehicle speed and/or the frequency of the GNSS signal.
When the preset range is determined, the high-precision map corresponding to the road area within the set distance in front of the current road where the vehicle is located can be extracted as the local high-precision map by taking the current position of the vehicle as the starting point. The shape of the preset range may be a circular region configured with the own vehicle as an origin, or may be a rectangular region or the like.
The size of the preset range can be flexibly set according to the requirements of an actual scene, for example, in a high-speed scene, the preset range can be set to be larger, the preset range can be specifically judged according to the current speed of the vehicle, and if the speed of the vehicle within a certain time exceeds a certain speed threshold, the vehicle is considered to be in a high-speed driving scene. For another example, in a scene with many vehicles, the preset range may be set to be smaller.
In an embodiment of the present application, the current location information of the vehicle includes a current location of the vehicle, and the obtaining a local high-precision map within a preset range according to the current location information of the vehicle includes: taking the current position of the self-vehicle as a starting point, and acquiring lane line information of a high-precision map within a preset range corresponding to the current position of the self-vehicle; and constructing the local high-precision map according to the lane line information of the high-precision map in the preset range.
According to the embodiment of the application, when the local high-precision map within the preset range is obtained based on the current positioning information of the own vehicle, the current position of the own vehicle can be taken as a starting point, then the lane line data of the high-precision map of the whole road with the current position as the starting point and the set distance in front of the current road as an end point are extracted, and then the local high-precision map of the area where the own vehicle is located is established by utilizing the lane line data.
In an embodiment of the present application, the determining the valid location area of the GNSS signal according to the current positioning information of the own vehicle, the local high-precision map, and the other vehicle positioning information corresponding to the own vehicle includes: projecting other vehicle positioning information corresponding to the own vehicle into the local high-precision map; projecting other vehicle positioning information and lane line information in the local high-precision map by taking the current position of the own vehicle as an origin to obtain a 2D grid map; determining a valid location area of the GNSS signals from the 2D grid map.
According to the embodiment of the application, when the effective position area of the GNSS signal is determined according to the current positioning information of the own vehicle, the local high-precision map corresponding to the own vehicle and the positioning information of the other vehicle, the positioning information of the other vehicle can be projected to the extracted local high-precision map, then, the northeast China (ENU) coordinate system is used, the own vehicle is used as an original point, the data in the local high-precision map comprises the positioning information of the other vehicle and the lane line information, and therefore the 2D grid map is built.
On the 2D grid map, each other vehicle positioning information and each lane line information correspond to a plane area, which indicates that these areas are occupied by other vehicles or other target objects, and of course, other obstacle information may be included, so that an area where GNSS signals of the vehicle may appear, that is, an effective location area, may be determined based on these information.
In one embodiment of the present application, the determining the valid location area of the GNSS signals from the 2D grid map comprises: determining a vehicle area and a road edge area in the 2D grid map as invalid position areas according to vehicle position information and road line information at the road edge in the 2D grid map; and taking the residual area outside the invalid position area in the 2D grid map as the valid position area of the GNSS signal.
After projection, the 2D grid map may include information of all corresponding target objects around the host vehicle, such as other vehicles or other obstacles, indicating that the areas of the 2D grid map where these target objects are located are occupied, and therefore, the currently acquired GNSS signals as observations may not be present in these areas, and should not be present outside the corresponding road areas in the 2D grid map. For example, ahead of the preceding vehicle at high speed, on the surrounding vehicle at slow speed, outside the road boundary, and so on.
Based on this, the embodiment of the application may determine the vehicle region in the 2D grid map according to the vehicle position information in the 2D grid map, determine the road edge region in the 2D grid map according to the lane line information at the road edge in the 2D grid map, and take these two regions as invalid position regions, that is, regions where GNSS signals are unlikely to occur and should not occur, so the remaining regions in the 2D grid map other than these regions may be taken as valid position regions of GNSS signals, that is, regions where GNSS signals are likely to occur.
In one embodiment of the present application, the detecting GNSS signal outliers from the valid location area of the GNSS signal comprises: determining whether a current GNSS signal is within the valid location area; if so, determining that the current GNSS signal is a normal GNSS signal and directly updating the Kalman filter by using the current GNSS signal; if not, determining that the current GNSS signal is an abnormal GNSS signal, and not updating the Kalman filter, or after transversely translating the current GNSS signal to the position of the center line of the current lane, temporarily updating the error range of the GNSS signal by the transverse translation distance, and then updating the Kalman filter.
The embodiment of the present application may specifically adopt a combined navigation mode of GNSS and IMU, and therefore, the GNSS signal in the above embodiment may specifically refer to a GNSS signal, and when detecting an abnormal value of the GNSS signal according to an effective location area, it may be determined whether the location of the GNSS signal falls within the effective location area, and if the location of the GNSS signal falls within the effective location area, it is determined that the current GNSS signal is normal, and the GNSS signal may be used as an observation value to update the kalman filter.
If the GNSS signal is abnormal, the current GNSS signal abnormal value is judged to be abnormal, and two measures can be adopted to process the GNSS signal abnormal value, wherein one measure is to directly refuse the signal updating at the time to avoid the instability of the output result of the filter, and the other measure is to transversely translate the current GNSS signal to the central line position of the current lane where the own vehicle is located, temporarily update the error range of the GNSS signal according to the transverse translation distance, and then update the Kalman filter to avoid the own vehicle deviating from the lane where the own vehicle is located.
In an embodiment of the present application, if the current GNSS signal is an abnormal GNSS signal, the method further includes: determining whether a plurality of GNSS signals can be continuously detected within a preset time period and are all in the effective position area; and if so, determining that the GNSS signal is recovered to be normal.
The above embodiments may continue until the GNSS signals are detected to be normal. Specifically, in the embodiment of the application, when detecting whether the GNSS signal is recovered to be normal, it may be determined according to the GNSS signal detected within a period of time, and if the GNSS signal detected within the period of time falls within the effective position area, that is, the GNSS signals acquired within the period of time are all normal GNSS signals, so that the GNSS signal may be considered to be recovered to be normal, and may be updated as an observation value. Of course, the GNSS signals or the number of consecutive detections in a specific detection time period may be flexibly set by those skilled in the art according to actual requirements, and is not specifically limited herein.
According to the method and the device, the effective position area of the GNSS signals is determined through the lane line data of the high-precision map and the object information sensed by the visual recognition device, and the effective position area is used for correcting and eliminating the GNSS signals, so that the positioning track can be prevented from deviating from a lane or entering an unreasonable area, and the rationality of the positioning track is further improved.
The embodiment of the present application further provides an apparatus 200 for detecting an abnormal value of a GNSS signal, as shown in fig. 2, which provides a schematic structural diagram of the apparatus for detecting an abnormal value of a GNSS signal in the embodiment of the present application, where the apparatus 200 includes: a first obtaining unit 210, a second obtaining unit 220, a first determining unit 230, and a detecting unit 240, wherein:
a first obtaining unit 210 for obtaining current location information of a host vehicle;
a second obtaining unit 220, configured to obtain, according to the current positioning information of the own vehicle, a local high-precision map within a preset range and other vehicle positioning information corresponding to the own vehicle;
a first determining unit 230, configured to determine an effective location area of a GNSS signal according to current location information of the own vehicle, the local high-precision map, and other vehicle location information corresponding to the own vehicle;
a detecting unit 240, configured to detect a GNSS signal outlier according to the valid location area of the GNSS signal.
In an embodiment of the application, the current positioning information of the own vehicle includes a current location of the own vehicle, and the second obtaining unit 220 is specifically configured to: taking the current position of the self-vehicle as a starting point, and acquiring lane line information of a high-precision map within a preset range corresponding to the current position of the self-vehicle; and constructing the local high-precision map according to the lane line information of the high-precision map in the preset range.
In an embodiment of the application, the current location information of the own vehicle includes a current location of the own vehicle, and the first determining unit 230 is specifically configured to: projecting other vehicle positioning information corresponding to the own vehicle into the local high-precision map; projecting other vehicle positioning information and lane line information in the local high-precision map by taking the current position of the own vehicle as an origin to obtain a 2D grid map; determining a valid location area of the GNSS signals from the 2D grid map.
In an embodiment of the present application, the first determining unit 230 is specifically configured to: determining a vehicle area and a road edge area in the 2D grid map as invalid position areas according to vehicle position information and road line information at the road edge in the 2D grid map; and taking the residual area outside the invalid position area in the 2D grid map as the valid position area of the GNSS signal.
In an embodiment of the present application, the detecting unit 240 is specifically configured to: determining whether a current GNSS signal is within the valid location area; if so, determining that the current GNSS signal is a normal GNSS signal and directly updating the Kalman filter by using the current GNSS signal; if not, determining that the current GNSS signal is an abnormal GNSS signal, and not updating the Kalman filter, or after transversely translating the current GNSS signal to the position of the center line of the current lane, temporarily updating the error range of the GNSS signal by the transverse translation distance, and then updating the Kalman filter.
In an embodiment of the present application, if the current GNSS signal is an abnormal GNSS signal, the apparatus further includes: a second determination unit, configured to determine whether a plurality of GNSS signals can be continuously detected within a preset time period to be within the valid position area; and the third determination unit is used for determining that the GNSS signals are recovered to be normal if the GNSS signals are recovered to be normal.
In one embodiment of the present application, the preset range is determined by: acquiring the current vehicle speed and/or the frequency of the GNSS signal; and determining the preset range according to the current vehicle speed and/or the frequency of the GNSS signal.
It can be understood that the above apparatus for detecting an abnormal value of a GNSS signal can implement the steps of the method for detecting an abnormal value of a GNSS signal provided in the foregoing embodiment, and the related explanations regarding the method for detecting an abnormal value of a GNSS signal are applicable to the apparatus for detecting an abnormal value of a GNSS signal, and are not described herein again.
Fig. 3 is a schematic structural diagram of an electronic device according to an embodiment of the present application. Referring to fig. 3, at a hardware level, the electronic device includes a processor, and optionally further includes an internal bus, a network interface, and a memory. The Memory may include a Memory, such as a Random-Access Memory (RAM), and may further include a non-volatile Memory, such as at least 1 disk Memory. Of course, the electronic device may also include hardware required for other services.
The processor, the network interface, and the memory may be connected to each other via an internal bus, which may be an ISA (Industry Standard Architecture) bus, a PCI (Peripheral Component Interconnect) bus, an EISA (Extended Industry Standard Architecture) bus, or the like. The bus may be divided into an address bus, a data bus, a control bus, etc. For ease of illustration, only one double-headed arrow is shown in FIG. 3, but this does not indicate only one bus or one type of bus.
And the memory is used for storing programs. In particular, the program may include program code comprising computer operating instructions. The memory may include both memory and non-volatile storage and provides instructions and data to the processor.
The processor reads the corresponding computer program from the nonvolatile memory into the memory and then runs the computer program to form the detection device of the abnormal value of the GNSS signal on the logic level. The processor is used for executing the program stored in the memory and is specifically used for executing the following operations:
obtaining current positioning information of a self-vehicle;
according to the current positioning information of the self-vehicle, acquiring a local high-precision map within a preset range and other vehicle positioning information corresponding to the self-vehicle;
determining an effective position area of the GNSS signal according to the current positioning information of the self-vehicle, the local high-precision map and other vehicle positioning information corresponding to the self-vehicle;
and detecting a GNSS signal abnormal value according to the effective position area of the GNSS signal.
The method executed by the apparatus for detecting GNSS signal outliers disclosed in the embodiment of fig. 1 of the present application may be applied to or implemented by a processor. The processor may be an integrated circuit chip having signal processing capabilities. In implementation, the steps of the above method may be performed by integrated logic circuits of hardware in a processor or instructions in the form of software. The Processor may be a general-purpose Processor, including a Central Processing Unit (CPU), a Network Processor (NP), and the like; but also Digital Signal Processors (DSPs), Application Specific Integrated Circuits (ASICs), Field Programmable Gate Arrays (FPGAs) or other Programmable logic devices, discrete Gate or transistor logic devices, discrete hardware components. The various methods, steps, and logic blocks disclosed in the embodiments of the present application may be implemented or performed. A general purpose processor may be a microprocessor or the processor may be any conventional processor or the like. The steps of the method disclosed in connection with the embodiments of the present application may be directly implemented by a hardware decoding processor, or implemented by a combination of hardware and software modules in the decoding processor. The software module may be located in ram, flash memory, rom, prom, or eprom, registers, etc. storage media as is well known in the art. The storage medium is located in a memory, and a processor reads information in the memory and completes the steps of the method in combination with hardware of the processor.
The electronic device may further execute the method executed by the apparatus for detecting an abnormal value of a GNSS signal in fig. 1, and implement the functions of the apparatus for detecting an abnormal value of a GNSS signal in the embodiment shown in fig. 1, which are not described herein again.
An embodiment of the present application further provides a computer-readable storage medium storing one or more programs, where the one or more programs include instructions, which when executed by an electronic device including a plurality of application programs, enable the electronic device to perform the method performed by the apparatus for detecting an abnormal value of a GNSS signal in the embodiment shown in fig. 1, and are specifically configured to perform:
obtaining current positioning information of a self-vehicle;
according to the current positioning information of the self-vehicle, acquiring a local high-precision map within a preset range and other vehicle positioning information corresponding to the self-vehicle;
determining an effective position area of the GNSS signal according to the current positioning information of the self-vehicle, the local high-precision map and other vehicle positioning information corresponding to the self-vehicle;
and detecting a GNSS signal abnormal value according to the effective position area of the GNSS signal.
As will be appreciated by one skilled in the art, embodiments of the present invention may be provided as a method, system, or computer program product. Accordingly, the present invention may take the form of an entirely hardware embodiment, an entirely software embodiment or an embodiment combining software and hardware aspects. Furthermore, the present invention may take the form of a computer program product embodied on one or more computer-usable storage media (including, but not limited to, disk storage, CD-ROM, optical storage, and the like) having computer-usable program code embodied therein.
The present invention is described with reference to flowchart illustrations and/or block diagrams of methods, apparatus (systems), and computer program products according to embodiments of the invention. It will be understood that each flow and/or block of the flow diagrams and/or block diagrams, and combinations of flows and/or blocks in the flow diagrams and/or block diagrams, can be implemented by computer program instructions. These computer program instructions may be provided to a processor of a general purpose computer, special purpose computer, embedded processor, or other programmable data processing apparatus to produce a machine, such that the instructions, which execute via the processor of the computer or other programmable data processing apparatus, create means for implementing the functions specified in the flowchart flow or flows and/or block diagram block or blocks.
These computer program instructions may also be stored in a computer-readable memory that can direct a computer or other programmable data processing apparatus to function in a particular manner, such that the instructions stored in the computer-readable memory produce an article of manufacture including instruction means which implement the function specified in the flowchart flow or flows and/or block diagram block or blocks.
These computer program instructions may also be loaded onto a computer or other programmable data processing apparatus to cause a series of operational steps to be performed on the computer or other programmable apparatus to produce a computer implemented process such that the instructions which execute on the computer or other programmable apparatus provide steps for implementing the functions specified in the flowchart flow or flows and/or block diagram block or blocks.
In a typical configuration, a computing device includes one or more processors (CPUs), input/output interfaces, network interfaces, and memory.
The memory may include forms of volatile memory in a computer readable medium, Random Access Memory (RAM) and/or non-volatile memory, such as Read Only Memory (ROM) or flash memory (flash RAM). Memory is an example of a computer-readable medium.
Computer-readable media, including both non-transitory and non-transitory, removable and non-removable media, may implement information storage by any method or technology. The information may be computer readable instructions, data structures, modules of a program, or other data. Examples of computer storage media include, but are not limited to, phase change memory (PRAM), Static Random Access Memory (SRAM), Dynamic Random Access Memory (DRAM), other types of Random Access Memory (RAM), Read Only Memory (ROM), Electrically Erasable Programmable Read Only Memory (EEPROM), flash memory or other memory technology, compact disc read only memory (CD-ROM), Digital Versatile Discs (DVD) or other optical storage, magnetic cassettes, magnetic tape magnetic disk storage or other magnetic storage devices, or any other non-transmission medium that can be used to store information that can be accessed by a computing device. As defined herein, a computer readable medium does not include a transitory computer readable medium such as a modulated data signal and a carrier wave.
It should also be noted that the terms "comprises," "comprising," or any other variation thereof, are intended to cover a non-exclusive inclusion, such that a process, method, article, or apparatus that comprises a list of elements does not include only those elements but may include other elements not expressly listed or inherent to such process, method, article, or apparatus. Without further limitation, an element defined by the phrase "comprising an … …" does not exclude the presence of other like elements in a process, method, article, or apparatus that comprises the element.
As will be appreciated by one skilled in the art, embodiments of the present application may be provided as a method, system, or computer program product. Accordingly, the present application may take the form of an entirely hardware embodiment, an entirely software embodiment or an embodiment combining software and hardware aspects. Furthermore, the present application may take the form of a computer program product embodied on one or more computer-usable storage media (including, but not limited to, disk storage, CD-ROM, optical storage, and the like) having computer-usable program code embodied therein.
The above description is only an example of the present application and is not intended to limit the present application. Various modifications and changes may occur to those skilled in the art. Any modification, equivalent replacement, improvement, etc. made within the spirit and principle of the present application should be included in the scope of the claims of the present application.
Claims (10)
1. A method for detecting GNSS signal outliers, wherein the method comprises:
obtaining current positioning information of a self-vehicle;
according to the current positioning information of the self-vehicle, acquiring a local high-precision map within a preset range and other vehicle positioning information corresponding to the self-vehicle;
determining an effective position area of the GNSS signal according to the current positioning information of the self-vehicle, the local high-precision map and other vehicle positioning information corresponding to the self-vehicle;
and detecting a GNSS signal abnormal value according to the effective position area of the GNSS signal.
2. The method of claim 1, wherein the current location information of the vehicle comprises a current position of the vehicle, and the obtaining the local high-precision map within a preset range according to the current location information of the vehicle comprises:
taking the current position of the self-vehicle as a starting point, and acquiring lane line information of a high-precision map within a preset range corresponding to the current position of the self-vehicle;
and constructing the local high-precision map according to the lane line information of the high-precision map in the preset range.
3. The method of claim 1, wherein the current positioning information of the self-vehicle comprises a current position of the self-vehicle, and the determining the effective position area of the GNSS signal according to the current positioning information of the self-vehicle, the local high-precision map and the corresponding other-vehicle positioning information of the self-vehicle comprises:
projecting other vehicle positioning information corresponding to the own vehicle into the local high-precision map;
projecting other vehicle positioning information and lane line information in the local high-precision map by taking the current position of the own vehicle as an origin to obtain a 2D grid map;
determining a valid location area of the GNSS signals from the 2D grid map.
4. The method of claim 3, wherein said determining a valid location area of said GNSS signals from said 2D grid map comprises:
determining a vehicle area and a road edge area in the 2D grid map as invalid position areas according to vehicle position information and road line information at the road edge in the 2D grid map;
and taking the residual area outside the invalid position area in the 2D grid map as the valid position area of the GNSS signal.
5. The method of claim 1, wherein said detecting GNSS signal outliers from the valid location area of the GNSS signals comprises:
determining whether a current GNSS signal is within the valid location area;
if so, determining that the current GNSS signal is a normal GNSS signal and directly updating the Kalman filter by using the current GNSS signal;
if not, determining that the current GNSS signal is an abnormal GNSS signal, and not updating the Kalman filter, or after transversely translating the current GNSS signal to the position of the center line of the current lane, temporarily updating the error range of the GNSS signal by the transverse translation distance, and then updating the Kalman filter.
6. The method of claim 5, wherein if the current GNSS signal is an abnormal GNSS signal, the method further comprises:
determining whether a plurality of GNSS signals can be continuously detected within a preset time period and are all in the effective position area;
and if so, determining that the GNSS signal is recovered to be normal.
7. The method of any one of claims 1 to 6, wherein the predetermined range is determined by:
acquiring the current vehicle speed and/or the frequency of the GNSS signal;
and determining the preset range according to the current vehicle speed and/or the frequency of the GNSS signal.
8. An apparatus for detecting an abnormal value of a GNSS signal, wherein the apparatus comprises:
a first acquisition unit configured to acquire current positioning information of a host vehicle;
the second acquisition unit is used for acquiring a local high-precision map within a preset range and other vehicle positioning information corresponding to the self vehicle according to the current positioning information of the self vehicle;
the first determining unit is used for determining an effective position area of the GNSS signal according to the current positioning information of the self-vehicle, the local high-precision map and other vehicle positioning information corresponding to the self-vehicle;
and the detection unit is used for detecting the abnormal value of the GNSS signal according to the effective position area of the GNSS signal.
9. An electronic device, comprising:
a processor; and
a memory arranged to store computer executable instructions which, when executed, cause the processor to perform the method of any of claims 1 to 7.
10. A computer readable storage medium storing one or more programs which, when executed by an electronic device comprising a plurality of application programs, cause the electronic device to perform the method of any of claims 1-7.
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