Gyroscope data verification method, electronic equipment, vehicle and storage medium

Abstract

The embodiment of the invention provides a gyroscope data verification method, electronic equipment, a vehicle and a storage medium, and the method comprises the following steps: obtaining gyroscope data of the vehicle, and calculating at least one of a frame loss rate, a frame repetition rate and a deviation coefficient of the gyroscope data; calculating the credibility of the gyroscope data based on at least one of the frame loss rate, the re-frame rate and the deviation coefficient; and under the condition that the credibility is smaller than a preset credibility threshold value, determining that the gyroscope data is credible. According to the embodiment of the invention, multiple credibility parameters of the gyroscope data can be determined, and whether the gyroscope data is credible is judged based on the multiple credibility parameters, so that the accuracy of the gyroscope data is guaranteed, and the vehicle positioning accuracy is improved.

Description

Technical Field

[0001] The present application relates to the field of positioning technology, and in particular to a gyroscope data verification method, electronic equipment, vehicle, and storage medium. Background Art

[0002] When a vehicle is driving and using the onboard navigation map software for navigation, the navigation map software performs a comprehensive calculation based on multiple signals, including GPS (Global Positioning System) signals, gyroscope signals, and pulse vehicle speed signals, to obtain relevant positioning information such as the vehicle's current driving position, direction, and slope. Among them, the gyroscope signal is a key input signal. In scenarios where GPS signals cannot be received, such as when the vehicle is in an indoor parking lot, underground parking lot, or tunnel, only the gyroscope signal can be used for positioning. However, due to factors such as gyroscope failure and environmental interference, the gyroscope signal may fail or be inaccurate, resulting in inaccurate vehicle positioning and affecting vehicle navigation. Summary of the Invention

[0003] In view of the above, it is necessary to provide a gyroscope data verification method, electronic equipment, vehicle and storage medium to solve the above-mentioned problem that due to gyroscope failure, environmental interference and other factors, the gyroscope signal may fail or be inaccurate, resulting in inaccurate vehicle positioning and affecting vehicle navigation.

[0004] In a first aspect, an embodiment of the present application provides a gyroscope data verification method, which is applied to a vehicle. The method includes: obtaining gyroscope data of the vehicle, determining at least one of the frame loss rate, reframe rate and deviation coefficient of the gyroscope data; determining the credibility of the gyroscope data based on at least one of the frame loss rate, reframe rate and deviation coefficient; and determining that the gyroscope data is credible when the credibility is less than a preset credibility threshold.

[0005] In one possible implementation, obtaining the vehicle's gyroscope data includes: controlling the vehicle's gyroscope sensor to detect a gyroscope signal at preset time intervals to obtain the gyroscope data, wherein the gyroscope data includes vehicle posture data and a timestamp, and the vehicle posture data includes at least the acceleration and / or angle corresponding to at least one coordinate axis among the x-axis, y-axis, and z-axis.

[0006] In a possible implementation, determining the frame loss rate of the gyroscope data includes determining the frame loss rate of the gyroscope data based on timestamps of a set of preset frames of gyroscope data.

[0007] In one possible implementation, the determining the frame loss rate of the gyroscope data based on the timestamps of a set of preset number of gyroscope data includes: determining the total duration corresponding to any set of preset number of gyroscope data based on the timestamps of the first frame of gyroscope data and the timestamp of the last frame of gyroscope data in any set of preset number of frames of gyroscope data; calculating the ideal number of frames of the gyroscope data within the total duration based on the total duration and the preset frame interval duration of the gyroscope data; and determining the frame loss rate of the gyroscope data based on the preset number of frames and the ideal number of frames.

[0008] In a possible implementation, determining the reframe rate of the gyroscope data includes: determining the reframe rate of the gyroscope data based on a set of preset frame numbers of the gyroscope data.

[0009] In one possible implementation, the reframe number of gyroscope data based on a set of preset frame numbers determines the reframe rate of the gyroscope data, including: determining the frame number of two adjacent gyroscope data in any set of preset frame numbers of gyroscope data in which the vehicle posture data is the same and the timestamps are different as the reframe number; and determining the reframe rate of the gyroscope data based on the reframe number and the preset frame number.

[0010] In one possible implementation, determining the deviation coefficient of the gyroscope data includes: determining the deviation coefficient of the gyroscope data based on abnormal data included in a set of preset frames of gyroscope data, wherein the abnormal data indicates that the vehicle posture data does not meet the standard deviation.

[0011] In one possible implementation, the abnormal data included in the gyroscope data of a set of preset frame numbers is used to determine the deviation coefficient of the gyroscope data, including: calculating the standard deviation of the vehicle posture data of each axis in any set of preset frame numbers of gyroscope data; determining the scalar value of the vehicle posture data of each axis based on the vehicle posture data of each axis and the average vehicle posture data; if the scalar value of the vehicle posture data of each axis is greater than a preset multiple of the standard deviation, determining that the vehicle posture data of each axis is the abnormal data, and determining the serial number corresponding to the abnormal data; merging the serial numbers of the abnormal data of different axes to obtain the total number of the abnormal data; adjusting the preset multiple, repeating the above steps to obtain the total number of the abnormal data, until the total number of the abnormal data meets the preset condition, and determining the deviation coefficient based on the total number of the abnormal data that meets the preset condition and the preset frame number.

[0012] In one possible implementation, determining the credibility of the gyroscope data based on at least one of the frame loss rate, the reframe rate, and the deviation coefficient includes: summing or weighted summing at least one of the frame loss rate, the reframe rate, and the deviation coefficient to obtain the credibility.

[0013] In a second aspect, an embodiment of the present application provides an electronic device, comprising a memory and a processor: wherein the memory is used to store program instructions; the processor is used to read and execute the program instructions stored in the memory, and when the program instructions are executed by the processor, the electronic device executes the above-mentioned gyroscope data verification method.

[0014] In a third aspect, an embodiment of the present application provides a vehicle, which includes the above-mentioned electronic device.

[0015] In a fourth aspect, an embodiment of the present application provides a computer storage medium, wherein the computer storage medium stores program instructions. When the program instructions are executed on an electronic device, the processor of the electronic device executes the above-mentioned gyroscope data verification method.

[0016] The gyroscope data verification method, electronic device, vehicle, and storage medium provided in the embodiments of the present application can determine multiple credibility parameters of gyroscope data, and comprehensively judge whether the gyroscope data is credible based on multiple credibility parameters, thereby ensuring the accuracy of the gyroscope data, improving the vehicle positioning accuracy, and ensuring normal vehicle navigation. BRIEF DESCRIPTION OF THE DRAWINGS

[0017] In order to more clearly illustrate the embodiments of the present application or the technical solutions in the prior art, the following briefly introduces the drawings required for use in the embodiments or the description of the prior art. Obviously, the drawings described below are merely embodiments of the present application. For ordinary technicians in this field, other drawings can be obtained based on the provided drawings without any creative work.

[0018] Figure 1 This is a flowchart of a gyroscope data verification method provided in one embodiment of the present application.

[0019] Figure 2 This is a flowchart of determining the frame loss rate provided by an embodiment of the present application.

[0020] Figure 3 This is a flowchart of determining the reframe rate provided by an embodiment of the present application.

[0021] Figure 4 This is a flow chart for determining a deviation coefficient provided by an embodiment of the present application.

[0022] Figure 52 is a schematic structural diagram of a gyroscope data verification device provided in one embodiment of the present application.

[0023] Figure 6 This is a schematic diagram of the hardware structure of an electronic device provided in one embodiment of the present application.

[0024] Figure 7 It is a schematic diagram of the hardware structure of a vehicle provided in one embodiment of the present application. DETAILED DESCRIPTION

[0025] The terms "first" and "second" involved in the embodiments of the present application are for descriptive purposes only and are not to be understood as indicating or implying relative importance or implicitly indicating the number of technical features indicated. Thus, the features defined as "first" and "second" may explicitly or implicitly include one or more features. In the description of the embodiments of the present application, words such as "exemplary" or "for example" are used to indicate examples, illustrations or explanations. Any embodiment or design described as "exemplary" or "for example" in the embodiments of the present application should not be interpreted as being more preferred or more advantageous than other embodiments or design schemes. Specifically, the use of words such as "exemplary" or "for example" is intended to present related concepts in a concrete way.

[0026] Unless otherwise defined, all technical and scientific terms used herein have the same meaning as commonly understood by those skilled in the art to which this application belongs. The terms used in the specification of this application are for the purpose of describing specific embodiments only and are not intended to limit this application. It should be understood that, unless otherwise specified in this application, " / " means or. For example, A / B can mean A or B. "And / or" in this application is merely a way to describe the association relationship of associated objects, indicating that three relationships can exist. For example, A and / or B can mean: A exists alone, A and B exist at the same time, and B exists alone. "At least one" means one or more. "Multiple" means two or more than two. For example, at least one of a, b or c can mean: a, b, c, a and b, a and c, b and c, a, b and c. In the absence of conflict, the following embodiments and features in the embodiments can be combined with each other.

[0027] When the vehicle is driving and using the onboard navigation map software for navigation, the navigation map software performs comprehensive calculations based on multiple signals such as the GPS (Global Positioning System) signal, the gyroscope signal, and the pulse vehicle speed signal to obtain relevant positioning information such as the vehicle's current driving position, direction, and slope. Among them, the gyroscope signal is a key input signal. In scenarios where the GPS signal cannot be received, such as when the vehicle is located in an indoor parking lot, an underground parking lot, or a tunnel, only the gyroscope signal can be used for positioning. However, due to factors such as gyroscope failure and environmental interference, the gyroscope signal may fail or be inaccurate. In related technologies, the vehicle cannot determine the credibility of the gyroscope signal. As a result, in the event that the gyroscope signal may fail or be inaccurate, the vehicle positioning data determined based on the gyroscope signal may be erroneous, affecting vehicle navigation.

[0028] To solve the above problems, an embodiment of the present application provides a gyroscope data verification method, which can determine multiple credibility parameters of gyroscope data, and comprehensively judge whether the gyroscope data is credible based on multiple credibility parameters, thereby ensuring the accuracy of gyroscope data, improving vehicle positioning accuracy, and ensuring normal vehicle navigation.

[0029] See Figure 1 FIG. 1 is a flow chart of a gyroscope data verification method according to an embodiment of the present application. The gyroscope data verification method is applied to an electronic device and includes: S101, obtaining gyroscope data of a vehicle, and determining at least one of a frame loss rate, a repeated frame rate, and a deviation coefficient of the gyroscope data.

[0030] In one embodiment of the present application, an electronic device is disposed in a vehicle and is communicatively connected to various sensors of the vehicle via a CAN bus. The electronic device can control the vehicle's gyroscope sensor via the CAN bus to detect gyroscope signals at preset time intervals, obtain multiple gyroscope data, and obtain a set of gyroscope data from the multiple gyroscope data. For example, the preset time interval is 20 milliseconds, 30 milliseconds, 50 milliseconds, or other time intervals. For example, the gyroscope sensor can be a three-axis gyroscope or a six-axis gyroscope. Each gyroscope data includes vehicle posture data and a timestamp. The vehicle posture data is vector data, including at least one of the acceleration and angle of the x-axis, y-axis, and z-axis. The x-axis, y-axis, and z-axis are the coordinate axes of the vehicle coordinate system, and the vehicle coordinate system can be the same as the earth coordinate system. The timestamp can be Beijing time or the timing time after the gyroscope sensor is powered on, in μs or ms.

[0031] In one embodiment of the present application, the frame loss rate of the gyroscope data is determined based on the timestamps of a set of preset frames of gyroscope data. Figure 2FIG. 1 is a flowchart of determining a frame loss rate according to an embodiment of the present application.

[0032] S201 : Determine a total duration corresponding to the set of preset number of gyroscope data based on a timestamp of a first frame of gyroscope data and a timestamp of a last frame of gyroscope data in the set of preset number of gyroscope data.

[0033] In one embodiment of the present application, the timestamp of the first frame of gyroscope data is the starting time of the preset number of gyroscope data frames, and the timestamp of the last frame of gyroscope data is the ending time of the preset number of gyroscope data frames. The total duration corresponding to the preset number of gyroscope data frames is obtained by calculating the difference between the timestamp of the last frame of gyroscope data and the timestamp of the first frame of gyroscope data.

[0034] S202 , calculating an ideal number of frames of the gyroscope data within the total time length based on the total time length and a preset frame interval length of the gyroscope data.

[0035] In one embodiment of the present application, the preset frame interval duration of the gyroscope data can be a preset value input by an external device, or can be determined by calculating the average frame interval duration of all historical gyroscope data. Ideal number of frames = total duration / preset frame interval duration + 1.

[0036] S203 : Determine a frame loss rate of the gyroscope data based on a preset frame number and an ideal frame number.

[0037] In one embodiment of the present application, the frame loss rate a=1-preset number of frames / ideal number of frames. The frame loss rate a can also be calculated using formula (1), which is: (1), In the calculation formula (1), n ​​is the preset number of frames, is the preset frame interval duration, and T is the actual frame interval duration.

[0038] In one embodiment of the present application, the reframe rate of the gyroscope data is determined based on the number of reframes of a set of preset frames of gyroscope data. Figure 3 FIG. 1 is a flowchart of determining a reframe rate according to an embodiment of the present application.

[0039] S301 : Determine, in the set of gyroscope data of a preset number of frames, frames in which two adjacent gyroscope data have the same vehicle posture data but different time stamps as duplicate frames.

[0040] In one embodiment of the present application, it is determined whether the vehicle posture data of every two adjacent, that is, two consecutive, gyroscope data in the group of preset frame numbers are the same, and whether the timestamps are the same. If it is determined that the vehicle posture data of two adjacent gyroscope data are the same and the timestamps are different, then the two adjacent gyroscope data are determined to be repeated frames, and the number of repeated frames is increased by one until the judgment of all two adjacent gyroscope data is completed to obtain the number of repeated frames of the gyroscope data of the group of preset frame numbers. Wherein, if the x-axis acceleration, y-axis acceleration and z-axis acceleration of two adjacent gyroscope data are the same, then the vehicle posture data of the two adjacent gyroscope data are determined to be the same. If the x-axis acceleration, y-axis acceleration and / or z-axis acceleration of two adjacent gyroscope data are different, then the vehicle posture data of the two adjacent gyroscope data are determined to be different.

[0041] S302 : Determine a reframe rate of the gyroscope data based on the reframe number and the preset frame number.

[0042] In one embodiment of the present application, the reframe rate b=the number of reframes r / the preset number of frames n.

[0043] In another embodiment of the present application, the reframe number and the preset frame number are subjected to a power operation to obtain the reframe rate of the gyroscope data. The calculation formula (2) for performing a power operation on the reframe number and the preset frame number is: (2), In calculation formula (2), r is the number of repeated frames, n is the preset number of frames, and j is a preset positive integer.

[0044] In another embodiment of the present application, the gyroscope has a situation where the measurement interval and reporting timing are inconsistent. Based on this situation and the different types and brands of gyroscopes, power operations are performed to reduce the impact of repeated frames caused by the reporting timing.

[0045] In one embodiment of the present application, the deviation coefficient of the gyroscope data is determined based on abnormal data included in a set of preset frames of gyroscope data, where the abnormal data indicates that the vehicle posture data does not meet the standard deviation. Figure 4 As shown, it is a flow chart of determining the deviation coefficient provided by an embodiment of the present application.

[0046] S401, calculating the standard deviation of each axis vehicle posture data in a set of gyroscope data of a preset number of frames.

[0047] In one embodiment of the present application, the standard deviation of the vehicle posture data of each axis in the set of gyroscope data of the preset number of frames is calculated. The calculation formula (3) is: (3), In the calculation formula (3), n is the preset number of frames, is the one-axis vehicle posture data, such as x-axis acceleration and y-axis acceleration, It is the average value of the vehicle posture data of the axis in the set of gyroscope data of the preset number of frames, for example, the average value of the x-axis acceleration and the average value of the y-axis acceleration.

[0048] S402 : Determine a scalar value of the vehicle posture data per axle based on the vehicle posture data per axle and the average vehicle posture data.

[0049] In one embodiment of the present application, the calculation formula (4) for determining the scalar value m of the vehicle posture data per axis is: (4), In the calculation formula (4), is the one-axis vehicle posture data, such as x-axis acceleration and y-axis acceleration, It is the average value of the vehicle posture data of the axis in the set of gyroscope data of the preset number of frames, for example, the average value of the x-axis acceleration and the average value of the y-axis acceleration.

[0050] S403: If the scalar value of the vehicle posture data of each axis is greater than a preset multiple of the standard deviation, the vehicle posture data of each axis is determined to be abnormal data, and a sequence number corresponding to the abnormal data is determined.

[0051] In one embodiment of the present application, if , k is a preset multiple, and the value of k is a positive integer. If it is the standard deviation, it is determined that the deviation of the vehicle posture data of this axis is large and does not meet the standard deviation, that is, the vehicle posture data of this axis is abnormal data, and the serial number ik of the gyroscope data corresponding to the vehicle posture data of this axis in the set of preset number of gyroscope data is recorded.

[0052] S404: Combine the sequence numbers of abnormal data of different axes to obtain the total number of abnormal data.

[0053] In one embodiment of the present application, the method in S402-S403 is used to perform abnormality judgment on the vehicle posture data of each axis in each gyroscope data, and multiple serial numbers ik are obtained. The serial numbers ik of the abnormal data of different axes are merged, and the repeated serial numbers ik are used as one serial number. The total number of abnormal data can be obtained by counting the number of serial numbers.

[0054] S405: Determine whether the total number of abnormal data meets the preset condition. If the total number of abnormal data meets the preset condition, the process proceeds to S406; if the total number of abnormal data does not meet the preset condition, the process proceeds to S407.

[0055] In one embodiment of the present application, the preset condition is that the total number of the current abnormal data is the same as the total number of the previous abnormal data and is less than half of the preset number of frames. In other words, if the total number of the abnormal data is the same as the total number of the previous abnormal data and is less than half of the preset number of frames, then the total number of the abnormal data is determined to meet the preset condition. If the total number of the abnormal data is different from the total number of the previous abnormal data and / or is greater than or equal to half of the preset number of frames, then the total number of the abnormal data is determined to not meet the preset condition.

[0056] S406 , determining a deviation coefficient based on the total number of abnormal data that meets a preset condition and a preset number of frames.

[0057] In one embodiment of the present application, the total number of abnormal data that meets the preset conditions is divided by the preset number of frames to obtain the deviation coefficient c.

[0058] S407: Adjust the preset multiple, and then the process returns to S403 to re-determine the total number of abnormal data.

[0059] In one embodiment of the present application, the preset multiple can be adjusted by increasing the preset multiple. For example, the initial value of the preset multiple is 1, and the preset multiple is increased in sequence each time it is adjusted.

[0060] S102: Determine the reliability of the gyroscope data based on at least one of a frame loss rate, a frame repetition rate, and a deviation coefficient.

[0061] In one embodiment of the present application, a weighted sum is performed on at least one of the frame loss rate, the repeated frame rate, and the deviation coefficient to obtain the credibility. The calculation formula (5) for weighted summation of at least one of the frame loss rate, repeated frame rate, and deviation coefficient is: (5), In the calculation formula (5), is the reliability, a is the frame loss rate, b is the repeated frame rate, c is the deviation coefficient, 、 、 are the weighted coefficients of frame loss rate, repeated frame rate, and deviation coefficient, respectively. 、 、 In different R&D projects, dynamic adjustments can be made based on different brands or specifications of gyroscopes, or the influence of frame loss rate, repeated frame rate, and deviation coefficient on the credibility of gyroscope data can be pre-set. + =1.

[0062] In another embodiment of the present application, at least one of the frame loss rate, the frame repetition rate, and the deviation coefficient may be summed, or the average of the frame loss rate, the frame repetition rate, and the deviation coefficient may be calculated to obtain the credibility.

[0063] S103: Determine whether the credibility is less than a preset credibility threshold. If the credibility is less than the preset credibility threshold, the process proceeds to S104; if the credibility is greater than or equal to the preset credibility threshold, the process proceeds to S105.

[0064] S104: Determine whether the gyroscope data is credible.

[0065] S105: Determine that the gyroscope data is unreliable.

[0066] In one embodiment of the present application, after S105, the method may further include: outputting a preset prompt to remind the user that the current positioning data is unreliable. The preset prompt includes at least one of a voice prompt and a pop-up prompt displayed on the vehicle display screen.

[0067] In an embodiment of the present application, after S105 , the method may further include: marking untrustworthy gyroscope data, so that the cause of the abnormality can be analyzed based on the marked untrustworthy gyroscope data.

[0068] The above-mentioned embodiments of the present application can determine multiple credibility parameters of gyroscope data, and comprehensively judge whether the gyroscope data is credible based on multiple credibility parameters, thereby ensuring the accuracy of gyroscope data, improving vehicle positioning accuracy, and ensuring normal vehicle navigation.

[0069] See Figure 5 FIG2 is a schematic diagram of the structure of a gyroscope data verification device according to an embodiment of the present application. In one embodiment of the present application, the gyroscope data verification device 200 may include multiple functional modules composed of computer program segments. The computer program segments in the gyroscope data verification device 200 may be stored in a memory of the vehicle and executed by at least one processor to perform the gyroscope data verification function.

[0070] In one embodiment of the present application, the gyroscope data verification device 200 can be divided into multiple functional modules according to the functions it performs. The functional modules of the gyroscope data verification device 200 may include: a first determination module 201, a second determination module 202, and a third determination module 203. A module in this embodiment of the present application refers to a series of computer program segments that can be executed by at least one processor and can perform fixed functions, and is stored in a memory.

[0071] The first determination module 201 is used to obtain gyroscope data of the vehicle and determine at least one of a frame loss rate, a frame repetition rate, and a deviation coefficient of the gyroscope data.

[0072] The second determination module 202 is configured to determine the reliability of the gyroscope data based on at least one of a frame loss rate, a frame repetition rate, and a deviation coefficient.

[0073] The third determining module 203 is configured to determine that the gyroscope data is credible when the credibility is less than a preset credibility threshold.

[0074] The embodiment of the present application also provides an electronic device 10, which can be a mobile phone, a tablet computer, a desktop computer, a laptop computer, a handheld computer, a notebook computer, an ultra-mobile personal computer (UMPC), a netbook, a cellular phone, a personal digital assistant (PDA), an augmented reality (AR) device, a virtual reality (VR) device, an artificial intelligence (AI) device, a wearable device, an in-vehicle device, a smart home device and / or a smart city device. The embodiment of the present application does not impose any special restrictions on the specific type of the electronic device 10.

[0075] See Figure 6 The figure shows a hardware structure diagram of an electronic device provided in an embodiment of the present application. The voice data processing method provided in the embodiment of the present application is applied to an electronic device 10, which includes, but is not limited to, a processor 110 and a memory 120 connected via a communication bus 130. Figure 6 This is merely an example of the electronic device and does not constitute a corresponding limitation. In other embodiments, the electronic device may include more components than those shown in the figure.

[0076] Memory 120 may include one or more random access memories (RAMs) and one or more non-volatile memories (NVMs). RAM can be directly read and written by processor 110 and can be used to store executable programs (e.g., machine instructions) for the operating system or other running programs, as well as user and application data. RAM may include static random access memory (SRAM), dynamic random access memory (DRAM), synchronous dynamic random access memory (SDRAM), double data rate synchronous dynamic random access memory (DDR SDRAM), etc.

[0077] The non-volatile memory can also store executable programs and user and application data, etc., and can be pre-loaded into the random access memory for direct reading and writing by the processor 110. The non-volatile memory can include disk storage devices and flash memory.

[0078] The memory 120 is used to store one or more computer programs. The one or more computer programs are configured to be executed by the processor 110. The one or more computer programs include multiple instructions. When the multiple instructions are executed by the processor 110, the voice data processing method executed on the electronic device 10 can be implemented.

[0079] In other embodiments, the electronic device 10 further includes an external memory interface for connecting to an external memory to expand the storage capacity of the electronic device 10 .

[0080] The processor 110 may include one or more processing units. For example, the processor 110 may include an application processor (AP), a modem processor, a graphics processing unit (GPU), an image signal processor (ISP), a controller, a video codec, a digital signal processor (DSP), a baseband processor, and / or a neural network processing unit (NPU). Different processing units may be independent devices or integrated into one or more processors.

[0081] The processor 110 provides computing and control capabilities. For example, the processor 110 is configured to execute a computer program stored in the memory 120 to implement the above-mentioned voice data processing method.

[0082] The communication bus 130 is at least used to provide a channel for communication between the memory 120 and the processor 110 in the electronic device 10 .

[0083] It should be understood that the structures illustrated in the embodiments of the present application do not constitute a specific limitation on the electronic device 10. In other embodiments of the present application, the electronic device 10 may include more or fewer components than shown, or may combine or separate certain components, or arrange the components differently. The illustrated components may be implemented in hardware, software, or a combination of software and hardware.

[0084] The present application also provides a vehicle 1, see Figure 7 FIG. 1 is a schematic diagram of the hardware structure of a vehicle provided in an embodiment of the present application. The vehicle 1 includes Figure 6 The electronic device 10 shown, for example, may be an on-board device on the vehicle 1 .

[0085] An embodiment of the present application also provides a computer storage medium, in which computer instructions are stored. When the computer instructions are executed on the electronic device 10, the electronic device 10 executes the above-mentioned related method steps to implement the gyroscope data verification method in the above-mentioned embodiment.

[0086] An embodiment of the present application further provides a computer program product. When the computer program product is run on a computer, the computer is caused to execute the above-mentioned related steps to implement the gyroscope data verification method in the above-mentioned embodiment.

[0087] In addition, an embodiment of the present application also provides a device, which can specifically be a chip, component or module, and the device may include a connected processor and memory; wherein the memory is used to store computer-executable instructions, and when the device is running, the processor can execute the computer-executable instructions stored in the memory to enable the chip to execute the gyroscope data verification method in the above-mentioned method embodiments.

[0088] Among them, the vehicle, computer storage medium, computer program product or chip provided in the embodiments of the present application are all used to execute the corresponding methods provided above. Therefore, the beneficial effects that can be achieved can refer to the beneficial effects in the corresponding methods provided above, and will not be repeated here.

[0089] Through the description of the above implementation methods, technical personnel in the relevant field can clearly understand that for the convenience and simplicity of description, only the division of the above-mentioned functional modules is used as an example. In actual applications, the above-mentioned functions can be assigned to different functional modules as needed, that is, the internal structure of the device can be divided into different functional modules to complete all or part of the functions described above.

[0090] In the several embodiments provided in this application, it should be understood that the disclosed devices and methods can be implemented in other ways. For example, the device embodiments described above are merely schematic. For example, the division of modules or units is only a logical function division. In actual implementation, there may be other division methods, such as multiple units or components can be combined or integrated into another device, or some features can be ignored or not executed. Another point is that the mutual coupling or direct coupling or communication connection shown or discussed can be through some interfaces, indirect coupling or communication connection of devices or units, which can be electrical, mechanical or other forms.

[0091] The units described as separate components may or may not be physically separate, and the components shown as units may be one physical unit or multiple physical units, that is, they may be located in one place or distributed in multiple places. Some or all of the units may be selected according to actual needs to achieve the purpose of the present embodiment.

[0092] In addition, the functional units in the various embodiments of the present application may be integrated into a single processing unit, or each unit may exist physically separately, or two or more units may be integrated into a single unit. The aforementioned integrated units may be implemented in the form of hardware or software functional units.

[0093] If the integrated unit is implemented in the form of a software functional unit and sold or used as an independent product, it can be stored in a readable storage medium. Based on this understanding, the technical solution of the embodiment of the present application, or the part that contributes to the prior art, or all or part of the technical solution can be embodied in the form of a software product. The software product is stored in a storage medium and includes several instructions for enabling a device (which can be a single-chip microcomputer, chip, etc.) or a processor to execute all or part of the steps of the various embodiments of the present application. The aforementioned storage medium includes: U disk, mobile hard disk, read-only memory (ROM), random access memory (RAM), disk or optical disk, and other media that can store program code.

[0094] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the present application and are not intended to limit the present application. Although the present application has been described in detail with reference to the preferred embodiments, those skilled in the art should understand that the technical solutions of the present application may be modified or replaced by equivalents without departing from the spirit and scope of the technical solutions of the present application.

Claims

1. A gyroscope data verification method, applied to electronic equipment, characterized in that: The method comprises: Obtaining gyroscope data of the vehicle, and determining at least one of a frame loss rate, a frame repetition rate, and a deviation coefficient of the gyroscope data; Determining the credibility of the gyroscope data based on at least one of the frame loss rate, the frame repetition rate, and the deviation coefficient; When the credibility is less than a preset credibility threshold, it is determined that the gyroscope data is credible.

2. The gyroscope data verification method according to claim 1, wherein: The obtaining of the vehicle's gyroscope data includes: The gyroscope sensor controlling the vehicle detects a gyroscope signal at preset time intervals to obtain the gyroscope data, wherein the gyroscope data includes vehicle posture data and a timestamp, and the vehicle posture data includes at least the acceleration and / or angle corresponding to at least one coordinate axis among the x-axis, y-axis and z-axis.

3. The gyroscope data verification method according to claim 2, wherein: Determining a frame loss rate of the gyroscope data includes: Based on a set of timestamps of a preset number of frames of gyroscope data, a frame loss rate of the gyroscope data is determined.

4. The gyroscope data verification method according to claim 3, wherein: The determining the frame loss rate of the gyroscope data based on a set of timestamps of a preset number of gyroscope data includes: Determining a total duration corresponding to any set of preset number of gyroscope data based on a timestamp of a first frame of gyroscope data and a timestamp of a last frame of gyroscope data in any set of preset number of gyroscope data; Calculating an ideal number of frames of the gyroscope data within the total time duration based on the total time duration and a preset frame interval duration of the gyroscope data; Based on the preset frame number and the ideal frame number, a frame loss rate of the gyroscope data is determined.

5. The gyroscope data verification method according to claim 2, wherein: Determining a reframe rate of the gyroscope data, including: The reframe rate of the gyroscope data is determined based on a set of reframe numbers of the gyroscope data of a preset frame number.

6. The gyroscope data verification method according to claim 5, wherein: The determining the reframe rate of the gyroscope data based on the number of reframes of the gyroscope data of a set of preset frame numbers includes: Determine the number of frames in which the vehicle posture data of two adjacent gyroscope data are the same and the timestamps are different in any set of preset frames of gyroscope data as the number of repeated frames; A reframe rate of the gyroscope data is determined based on the reframe number and the preset frame number.

7. The gyroscope data verification method according to claim 2, wherein: Determining a bias coefficient of the gyroscope data, including: The deviation coefficient of the gyroscope data is determined based on abnormal data included in a set of gyroscope data of a preset number of frames, wherein the abnormal data indicates that the vehicle posture data does not meet the standard deviation.

8. The gyroscope data verification method according to claim 7, wherein: The determining of the deviation coefficient of the gyroscope data based on abnormal data included in a set of gyroscope data of a preset number of frames includes: Calculate the standard deviation of the vehicle attitude data for each axis in any set of preset frames of gyroscope data; determining a scalar value of the per-axle vehicle posture data based on the per-axle vehicle posture data and the average vehicle posture data; If the scalar value of the vehicle posture data of each axle is greater than a preset multiple of the standard deviation, determining that the vehicle posture data of each axle is the abnormal data, and determining a sequence number corresponding to the abnormal data; Merge the sequence numbers of abnormal data of different axes to obtain the total number of abnormal data; Adjust the preset multiple, repeat the above steps to obtain the total number of abnormal data until the total number of abnormal data meets the preset condition, and determine the deviation coefficient based on the total number of abnormal data that meets the preset condition and the preset number of frames.

9. The gyroscope data verification method according to claim 1, wherein: The determining the credibility of the gyroscope data based on at least one of the frame loss rate, the frame repetition rate, and the deviation coefficient includes: At least one of the frame loss rate, the frame repetition rate, and the deviation coefficient is summed or weighted to obtain the credibility.

10. An electronic device, characterized in that: The electronic device comprises a memory and a processor: Wherein, the memory is used to store program instructions; The processor is configured to read and execute the program instructions stored in the memory, and when the program instructions are executed by the processor, the electronic device executes the gyroscope data verification method according to any one of claims 1 to 9.

11. A vehicle, characterized in that: The vehicle includes the electronic device according to claim 10.

12. A computer storage medium, characterized in that The computer storage medium stores program instructions, and when the program instructions are executed on an electronic device, a processor of the electronic device executes the gyroscope data verification method according to any one of claims 1 to 9.

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