Monitoring method, device

Abstract

The application discloses a kind of monitoring method, device, method includes: judging whether integrity monitoring module is normal work;If integrity monitoring module is normal work, based on GNSS correction data, determine target combination navigation algorithm;With target combination navigation algorithm, calculate residual sum of squares;Based on the integrity monitoring algorithm corresponding to target combination navigation algorithm and residual sum of squares, calculate horizontal protection level;Finally, based on horizontal protection level and preset threshold, generate prompt information, and send prompt information to automatic driving control unit.The application is verified whether integrity monitoring module is normal work before monitoring vehicle-mounted combination navigation system, avoids missing detection, error condition due to integrity monitoring module itself failure or card stagnation, improves monitoring reliability and effect.In addition, the integrity monitoring module of the application is monitored by two kinds of solving modes, and calculation is simple, to avoid additional operation amount.

Description

Technical Field

[0001] This application relates to the field of vehicle-mounted integrated navigation technology, and more specifically, to a monitoring method and device. Background Technology

[0002] As a crucial module for determining vehicle position and attitude, the operational stability and reliability of the output data of the in-vehicle navigation system directly affect the safety of navigation and positioning functions. Therefore, it is necessary to monitor the accuracy of its output data. Simultaneously, the robustness of the monitoring module of the in-vehicle navigation system should also be further managed to prevent the downstream autonomous driving control unit from using incorrect position and attitude data for vehicle control in the event of a monitoring module failure, thus avoiding potential hazards.

[0003] Currently, the monitoring of in-vehicle navigation systems is generally carried out through a monitoring module, which monitors the in-vehicle navigation system and reports the monitored data in order to manage the in-vehicle navigation system accordingly.

[0004] However, the above methods are prone to missed detections and errors due to the failure or malfunction of the monitoring module itself, resulting in poor monitoring performance. Summary of the Invention

[0005] The main purpose of this application is to provide a monitoring method and device to solve the problem of poor monitoring effect caused by missed detections and errors due to the failure or jamming of the monitoring module itself in related technologies.

[0006] To achieve the above objectives, firstly, this application provides a monitoring method, comprising:

[0007] Determine if the integrity monitoring module is working properly;

[0008] If the integrity monitoring module is working properly, the target integrated navigation algorithm is determined based on the GNSS correction data;

[0009] Calculate the sum of squared residuals using a target-integrated navigation algorithm;

[0010] Based on the integrity monitoring algorithm and residual sum of squares corresponding to the target integrated navigation algorithm, the horizontal protection level is calculated, wherein the integrity monitoring algorithm is set in the integrity monitoring module;

[0011] Based on the horizontal protection level and preset threshold, a prompt message is generated and sent to the autonomous driving control unit.

[0012] In one possible implementation, determining whether the integrity monitoring module is functioning correctly includes:

[0013] Send a request signal to the integrity monitoring module;

[0014] If no response signal is received from the integrity monitoring module, the integrity monitoring module is not working properly and sends a reset signal to the microcontroller.

[0015] If the integrity monitoring module receives a response signal in response to the request signal, the integrity monitoring module will operate normally.

[0016] In one possible implementation, a target integrated navigation algorithm is determined based on GNSS correction data, including:

[0017] Determine whether the GNSS correction data was successfully unpacked;

[0018] If the GNSS correction data is successfully unpacked, the target integrated navigation algorithm is the first integrated navigation algorithm, which is used to execute the integrated positioning solution;

[0019] If the GNSS correction data unpacking fails, the target integrated navigation algorithm is the second integrated navigation algorithm, which is used to execute the dead reckoning solution.

[0020] In one possible implementation, a target-integrated navigation algorithm is used to calculate the residual sum of squares, including:

[0021] The extended Kalman filter algorithm is used to calculate the error covariance;

[0022] After processing the error covariance, we obtain the longitude variance and latitude variance;

[0023] Calculate the sum of squared residuals based on the longitude and latitude variances.

[0024] In one possible implementation, the error covariance is expressed by the following formula:

[0025] P k =HP k-1 H T +Q

[0026] Where H is the measurement matrix, H T Let H be the transpose of H, Q be the measurement noise, and P be the transpose of H. k Let P be the error covariance at time k. k-1 Let be the error covariance at time k-1.

[0027] In one possible implementation, the horizontal protection level is calculated based on the integrity monitoring algorithm corresponding to the target integrated navigation algorithm and the residual sum of squares, including:

[0028] Calculate the lateral error between the vehicle's first position coordinates and the vehicle's second position coordinates, where the first position coordinates are the coordinates output by the integrated navigation algorithm module, and the second position coordinates are the coordinates output by the network real-time dynamic positioning algorithm module;

[0029] The horizontal protection level is obtained by multiplying the lateral error by the sum of squared residuals.

[0030] In one possible implementation, the horizontal protection level is calculated based on the integrity monitoring algorithm corresponding to the target integrated navigation algorithm and the residual sum of squares, including:

[0031] The squared residual is used as the level of protection.

[0032] In one possible implementation, a warning message is generated based on the horizontal protection level and a preset threshold, and the warning message is sent to the autonomous driving control unit, including:

[0033] If the level of protection exceeds the preset threshold, an alarm signal is generated and sent to the autonomous driving control unit.

[0034] In one possible implementation, before determining whether the GNSS correction data has been successfully unpacked, the following steps are also included:

[0035] Determine whether the observations of the GNSS receiver meet the preset observations.

[0036] Secondly, embodiments of the present invention provide a monitoring device, comprising:

[0037] The judgment module is used to determine whether the integrity monitoring module is working properly;

[0038] The algorithm determination module is used to determine the target integrated navigation algorithm based on GNSS correction data, assuming the integrity monitoring module is working properly.

[0039] The first calculation module is used to calculate the sum of squared residuals using the target integrated navigation algorithm;

[0040] The second calculation module is used to calculate the horizontal protection level based on the integrity monitoring algorithm and residual sum of squares corresponding to the target integrated navigation algorithm, wherein the integrity monitoring algorithm is set in the integrity monitoring module;

[0041] The prompt module is used to generate prompt information based on the horizontal protection level and preset thresholds, and send the prompt information to the autonomous driving control unit.

[0042] Thirdly, embodiments of the present invention provide a terminal, including a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the processor executes the computer program to implement the steps of any of the above monitoring methods.

[0043] Fourthly, embodiments of the present invention provide a computer-readable storage medium storing a computer program, which, when executed by a processor, implements the steps of any of the monitoring methods described above.

[0044] This invention provides a monitoring method and apparatus, comprising: determining whether an integrity monitoring module is functioning normally; if the integrity monitoring module is functioning normally, determining a target integrated navigation algorithm based on GNSS correction data; calculating the residual sum of squares using the target integrated navigation algorithm; further calculating a horizontal protection level based on the integrity monitoring algorithm corresponding to the target integrated navigation algorithm and the residual sum of squares, wherein the integrity monitoring algorithm is set in the integrity monitoring module; and finally generating a prompt message based on the horizontal protection level and a preset threshold, and sending the prompt message to the autonomous driving control unit. This invention verifies the functionality of the integrity monitoring module before monitoring the in-vehicle integrated navigation system, avoiding missed detections or errors due to module failure or malfunction, thus improving monitoring reliability and effectiveness. Furthermore, the integrity monitoring module of this invention monitors using two solution modes, simplifying calculations and avoiding additional computational load. Attached Figure Description

[0045] The accompanying drawings, which form part of this application, are used to provide a further understanding of the application and to make other features, objects, and advantages of the application more apparent. The illustrative embodiments and descriptions of this application are used to explain the application and do not constitute an undue limitation of the application. In the drawings:

[0046] Figure 1 This is a schematic diagram of the structure of a monitoring system provided in an embodiment of the present invention;

[0047] Figure 2 This is a flowchart illustrating the implementation of a monitoring method according to an embodiment of the present invention;

[0048] Figure 3 This is a flowchart illustrating the implementation of a monitoring method according to another embodiment of the present invention;

[0049] Figure 4 This is a schematic diagram of the structure of a monitoring device provided in an embodiment of the present invention;

[0050] Figure 5 This is a schematic diagram of the terminal provided in an embodiment of the present invention. Detailed Implementation

[0051] To make the objectives, technical solutions, and advantages of the embodiments of the present invention clearer, the technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of the present invention, and not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of the present invention.

[0052] The terms "first," "second," "third," "fourth," etc. (if present) in the specification, claims, and accompanying drawings of this invention are used to distinguish similar objects and are not necessarily used to describe a specific order or sequence. It should be understood that such data can be interchanged where appropriate so that embodiments of the invention described herein can be implemented in sequences other than those illustrated or described herein.

[0053] In this application embodiment, the terms "module" or "unit" refer to a computer program or part of a computer program that has a predetermined function and works with other related parts to achieve a predetermined goal, and can be implemented wholly or partially using software, hardware (such as processing circuitry or memory), or a combination thereof. Similarly, a processor (or multiple processors or memory) can be used to implement one or more modules or units. Furthermore, each module or unit can be part of an overall module or unit that includes the functionality of that module or unit.

[0054] It should be understood that in the various embodiments of the present invention, the sequence number of each process does not imply the order of execution. The execution order of each process should be determined by its function and internal logic, and should not constitute any limitation on the implementation process of the embodiments of the present invention.

[0055] It should be understood that in this invention, "comprising" and "having," and any variations thereof, are intended to cover non-exclusive inclusion, for example, a process, method, system, product, or device that includes a series of steps or units is not necessarily limited to those steps or units that are explicitly listed, but may include other steps or units that are not explicitly listed or that are inherent to such process, method, product, or device.

[0056] It should be understood that in this invention, "multiple" refers to two or more. "And / or" is merely a description of the relationship between related objects, indicating that three relationships can exist. For example, "and / or B" can represent: A existing alone, A and B existing simultaneously, and B existing alone. The character " / " generally indicates that the preceding and following related objects are in an "or" relationship. "Contains A, B, and C", "Contains A, B, and C" means that all three A, B, and C are contained; "Contains A, B, or C" means that one of A, B, and C is contained; "Contains A, B, and / or C" means that any one, two, or three of A, B, and C are contained.

[0057] It should be understood that in this invention, "B corresponding to A", "B corresponding to A", "A and B correspond", or "B and A correspond" means that B is associated with A, and B can be determined based on A. Determining B based on A does not mean determining B solely based on A; B can also be determined based on A and / or other information. Matching A and B is defined as a similarity between A and B that is greater than or equal to a preset threshold.

[0058] Depending on the context, "if" as used here can be interpreted as "when," "when," "in response to determination," or "in response to detection."

[0059] The technical solution of the present invention will be described in detail below with reference to specific embodiments. These specific embodiments can be combined with each other, and the same or similar concepts or processes may not be described again in some embodiments.

[0060] To make the objectives, technical solutions, and advantages of the present invention clearer, specific embodiments will be described below in conjunction with the accompanying drawings.

[0061] In one embodiment, such as Figure 1 As shown, a monitoring system is provided, including:

[0062] The L1 application layer, L2 function monitoring layer, L3 monitoring management layer, and external interaction module are used to monitor the vehicle-mounted integrated navigation system through interaction between them.

[0063] The external interaction module includes GNSS (Global Navigation Satellite System) data processing software (also known as GNSS correction data unpacking software), chassis, and automatic driving control unit.

[0064] The GNSS correction data unpacking software and chassis provide the necessary input information for the vehicle-mounted integrated navigation system, while the autonomous driving control unit receives the vehicle position, attitude, and alarm signals AF-3 provided by the vehicle-mounted integrated navigation system.

[0065] The L1 application layer includes a GNSS receiver, an NRTK (Network Real-Time Kinematic) algorithm module, an IMU (Inertial Measurement Unit), an IMU calibration module, an integrated navigation algorithm module, and a microcontroller unit (MCU). The L1 application layer is responsible for performing the basic functions of GNSS+IMU integrated navigation under both available and unavailable GNSS and correction data conditions. This layer does not have a dedicated external monitoring mechanism. The GNSS receiver, IMU, and MCU all utilize functional safety components with self-test capabilities or redundancy.

[0066] The L2 functional monitoring layer includes integrity monitoring module 1 and integrity monitoring module 2. Integrity monitoring module 1 checks the correctness of the dead reckoning (DR) solution when the GNSS receiver or NRTK algorithm module is unavailable. Its input signals include the covariance matrix, calibrated acceleration, and angular velocity. Integrity monitoring module 2 checks the correctness of the combined positioning solution when both the GNSS receiver and NRTK algorithm module are available. Its input signals include the RTK (Real-Time Kinematic) solution, vehicle position and attitude, covariance matrix, and calibrated acceleration and angular velocity.

[0067] The L3 monitoring and management layer includes a centralized status management module. This module monitors the operational status of integrity monitoring module 1 and integrity monitoring module 2 in the L2 functional monitoring layer.

[0068] In one embodiment, such as Figure 2 As shown, a monitoring method is provided, including the following steps:

[0069] Step S201: Determine whether the integrity monitoring module is working properly.

[0070] The proper functioning of the integrity monitoring module is determined as follows: a request signal is sent to the integrity monitoring module. If no response signal is received from the integrity monitoring module in response to the request signal, the integrity monitoring module is not functioning properly and sends a reset signal to the microcontroller. If a response signal is received from the integrity monitoring module in response to the request signal, the integrity monitoring module is functioning properly.

[0071] The integrity monitoring module includes integrity monitoring module 1 and integrity monitoring module 2.

[0072] Combination Figure 1The status centralized management module sends query signal 1 (i.e. request signal 1) to the integrity monitoring module 1 and query signal 2 (i.e. request signal 2) to the integrity monitoring module 2 at fixed intervals.

[0073] If a response signal 1 is received from integrity monitoring module 1 and a response signal 2 is received from integrity monitoring module 2, it indicates that integrity monitoring module 1 and integrity monitoring module 2 are operating normally. Otherwise, it indicates that integrity monitoring module 1 and integrity monitoring module 2 have detected "abnormal heartbeat". In this case, the status centralized management module sends a reset signal to the microcontroller to request a reset.

[0074] Furthermore, if the state centralized management module receives alarm signal AF-1 from integrity monitoring module 1 or alarm signal AF-2 from integrity monitoring module 2, it indicates that integrity monitoring module 1 and integrity monitoring module 2 are operating normally, and the result calculated by the integrated navigation algorithm module is incorrect. Therefore, it needs to send alarm signal AF-3 to the autonomous driving control unit to prompt the autonomous driving control unit to disable the result calculated by the integrated navigation algorithm module.

[0075] Step S202: If the integrity monitoring module is working normally, determine the target integrated navigation algorithm based on the GNSS correction data.

[0076] Based on GNSS correction data, the target integrated navigation algorithm is determined in the following way: it is determined whether the GNSS correction data was successfully unpacked. If the GNSS correction data was successfully unpacked, the target integrated navigation algorithm is the first integrated navigation algorithm, which is used to execute the integrated positioning solution; if the GNSS correction data was not successfully unpacked, the target integrated navigation algorithm is the second integrated navigation algorithm, which is used to execute the dead reckoning solution.

[0077] If the GNSS correction data is successfully unpacked, it means that the NRTK algorithm module can use the GNSS correction data to calculate high-precision position coordinates. Then the input information of the integrated navigation algorithm module includes the high-precision position coordinates calculated by the NRTK algorithm module, the wheel speed and steering angle output by the chassis, and the calibrated acceleration and angular velocity output by the IMU calibration module.

[0078] If the GNSS correction data unpacking fails, it indicates that the position coordinates calculated by the NRTK algorithm module may be incorrect. Therefore, the input information of the integrated navigation algorithm module includes the wheel speed and steering angle output by the chassis, and the calibrated acceleration and angular velocity output by the IMU calibration module.

[0079] Step S203: Calculate the sum of squared residuals using the target integrated navigation algorithm.

[0080] The residual sum of squares is calculated using a target-integrated navigation algorithm, which is achieved as follows: the extended Kalman filter algorithm is used to calculate the error covariance, and then the error covariance is processed to obtain the longitude variance and latitude variance. Based on the longitude variance and latitude variance, the residual sum of squares is calculated.

[0081] The error covariance is expressed by the following formula:

[0082] P k =HP k-1 H T +Q (1)

[0083] Where H is the measurement matrix, H T Let H be the transpose of H, Q be the measurement noise, and P be the transpose of H. k Let P be the error covariance at time k. k-1 Let be the error covariance at time k-1.

[0084] The error covariance P is calculated using the above formula. k Then, the error covariance can be processed to obtain the longitude variance and latitude variance. Specifically,

[0085] Longitude variance can be expressed by the following formula:

[0086]

[0087] Where var_lon is the longitude variance. The error covariance P k The first element on the main diagonal.

[0088] Latitude variance can be expressed by the following formula:

[0089]

[0090] Where var_lat is the latitudinal variance. The error covariance P k The second element on the main diagonal.

[0091] Once the longitude and latitude variances are calculated, the residual sum of squares can be calculated based on these variances, as follows:

[0092]

[0093] Where SSE is the sum of squared residuals.

[0094] Step S204: Calculate the horizontal protection level based on the integrity monitoring algorithm and residual sum of squares corresponding to the target integrated navigation algorithm.

[0095] The integrity monitoring algorithm is set in the integrity monitoring module.

[0096] In one embodiment, the horizontal protection level is calculated based on the integrity monitoring algorithm and residual sum of squares corresponding to the target integrated navigation algorithm: first, the lateral error between the vehicle's first position coordinates and the vehicle's second position coordinates is calculated, where the first position coordinates are the coordinates output by the integrated navigation algorithm module and the second position coordinates are the coordinates output by the network real-time dynamic positioning algorithm module; then, the lateral error is multiplied by the residual sum of squares to obtain the horizontal protection level.

[0097] If the integrated navigation algorithm module uses the high-precision position coordinates (i.e., the vehicle's second position coordinates) output by the NRTK algorithm module, then calculate the lateral error w between the vehicle's first position coordinates output by the integrated navigation algorithm module and the vehicle's second position coordinates output by the NRTK algorithm module.

[0098] After calculating the lateral error w, the Horizontal Protection Level (HPL) can be calculated using the following formula:

[0099] HPL = w * SSE (5)

[0100] In another implementation, the horizontal protection level is calculated based on the integrity monitoring algorithm corresponding to the target integrated navigation algorithm and the residual sum of squares: the residual squares are used as the horizontal protection level.

[0101] The horizontal protection level can be calculated using the following formula:

[0102] HPL = SSE (6)

[0103] Step S205: Based on the horizontal protection level and preset threshold, generate a prompt message and send the prompt message to the automatic driving control unit.

[0104] Based on the horizontal protection level and a preset threshold, a prompt message is generated and sent to the autonomous driving control unit. If the horizontal protection level exceeds the preset threshold, an alarm signal is generated and sent to the autonomous driving control unit. The preset threshold can be set according to specific circumstances and is not specifically limited here.

[0105] If the horizontal alarm limit is set to a preset threshold, then the horizontal protection level HPL calculated by formula (5) is set to 0. If the horizontal protection level HPL exceeds the horizontal alarm limit, then the alarm signal AF-2 = 0 is set and an alarm signal is sent to the status centralized management module to indicate that there is a data correctness abnormality. Otherwise, AF-2 = 1 is kept, and it is considered that there is no data correctness abnormality. The automatic driving control unit can be prompted that the data is available.

[0106] If the horizontal protection level HPL calculated by formula (6) exceeds the horizontal alarm threshold, the alarm signal AF-1 = 0 is set and an alarm signal is sent to the status centralized management module to indicate that there is a data correctness abnormality. Otherwise, AF-1 = 1 is maintained, and it is considered that there is no data correctness abnormality. The automatic driving control unit can be prompted that the data is available.

[0107] When the status centralized management module receives alarm signal AF-1 or alarm signal AF-2, it can send alarm signal AF-3 to the autonomous driving control unit to indicate that the data is unavailable.

[0108] Combination Figure 3 Before determining whether the GNSS correction data has been successfully unpacked, the process also includes: determining whether the observations of the GNSS receiver meet the preset observations; if the observations of the GNSS receiver meet the preset observations, then determining whether the GNSS correction data has been successfully unpacked; if the observations of the GNSS receiver do not meet the preset observations, then executing the step of calculating the horizontal protection level based on the integrity monitoring algorithm and the residual sum of squares corresponding to the target integrated navigation algorithm, wherein the residual sum of squares is used as the horizontal protection level.

[0109] This invention provides a monitoring method, comprising: determining whether an integrity monitoring module is working properly; if the integrity monitoring module is working properly, determining a target integrated navigation algorithm based on GNSS correction data; calculating the residual sum of squares using the target integrated navigation algorithm; further calculating the horizontal protection level based on the integrity monitoring algorithm corresponding to the target integrated navigation algorithm and the residual sum of squares, wherein the integrity monitoring algorithm is set in the integrity monitoring module; and finally generating a prompt message based on the horizontal protection level and a preset threshold, and sending the prompt message to the autonomous driving control unit. This invention verifies the proper functioning of the integrity monitoring module before monitoring the in-vehicle integrated navigation system, avoiding missed detections or errors due to module failure or malfunction, thus improving monitoring reliability and effectiveness. Furthermore, the integrity monitoring module of this invention monitors using two solution modes, simplifying calculations and avoiding additional computational load.

[0110] It should be understood that the sequence number of each step in the above embodiments does not imply the order of execution. The execution order of each process should be determined by its function and internal logic, and should not constitute any limitation on the implementation process of the embodiments of the present invention.

[0111] The following are device embodiments of the present invention. For details not described in detail, please refer to the corresponding method embodiments described above.

[0112] Figure 4 A schematic diagram of a monitoring device provided in an embodiment of the present invention is shown. For ease of explanation, only the parts related to the embodiment of the present invention are shown. The monitoring device includes a judgment module 401, an algorithm determination module 402, a first calculation module 403, a second calculation module 404, and a prompting module 405, as detailed below:

[0113] Module 401 is used to determine whether the integrity monitoring module is working properly.

[0114] The algorithm determination module 402 is used to determine the target integrated navigation algorithm based on GNSS correction data if the integrity monitoring module is working normally.

[0115] The first calculation module 403 is used to calculate the sum of squared residuals using the target integrated navigation algorithm;

[0116] The second calculation module 404 is used to calculate the horizontal protection level based on the integrity monitoring algorithm and residual sum of squares corresponding to the target integrated navigation algorithm, wherein the integrity monitoring algorithm is set in the integrity monitoring module;

[0117] The prompt module 405 is used to generate prompt information based on the horizontal protection level and preset threshold, and send the prompt information to the autonomous driving control unit.

[0118] In one possible implementation, the judgment module 401 is also used to send a request signal to the integrity monitoring module;

[0119] If no response signal is received from the integrity monitoring module, the integrity monitoring module is not working properly and sends a reset signal to the microcontroller.

[0120] If the integrity monitoring module receives a response signal in response to the request signal, the integrity monitoring module will operate normally.

[0121] In one possible implementation, the algorithm determination module 402 is also used to determine whether the GNSS correction data has been successfully unpacked;

[0122] If the GNSS correction data is successfully unpacked, the target integrated navigation algorithm is the first integrated navigation algorithm, which is used to execute the integrated positioning solution;

[0123] If the GNSS correction data unpacking fails, the target integrated navigation algorithm is the second integrated navigation algorithm, which is used to execute the dead reckoning solution.

[0124] In one possible implementation, the first calculation module 403 is also used to calculate the error covariance using an extended Kalman filter algorithm;

[0125] After processing the error covariance, we obtain the longitude variance and latitude variance;

[0126] Calculate the sum of squared residuals based on the longitude and latitude variances.

[0127] In one possible implementation, the error covariance is expressed by the following formula:

[0128] P k =HP k-1 H T +Q

[0129] Where H is the measurement matrix, H T Let H be the transpose of H, Q be the measurement noise, and P be the transpose of H. k Let P be the error covariance at time k. k-1 Let be the error covariance at time k-1.

[0130] In one possible implementation, the second calculation module 404 is further used to calculate the lateral error between the vehicle's first position coordinates and the vehicle's second position coordinates, wherein the first position coordinates are the coordinates output by the integrated navigation algorithm module, and the second position coordinates are the coordinates output by the network real-time dynamic positioning algorithm module.

[0131] The horizontal protection level is obtained by multiplying the lateral error by the sum of squared residuals.

[0132] In one possible implementation, the second calculation module 404 is also used to use the squared residual as the level of protection.

[0133] In one possible implementation, the alert module 405 is further configured to generate an alarm signal if the level of protection exceeds a preset threshold, and send the alarm signal to the autonomous driving control unit.

[0134] In one possible implementation, before the judgment module 401, there is also an observation judgment module, which is used to determine whether the observations of the GNSS receiver meet the preset observations.

[0135] This invention provides a monitoring device specifically used to determine whether an integrity monitoring module is functioning correctly. If the integrity monitoring module is functioning correctly, it determines the target integrated navigation algorithm based on GNSS correction data, then calculates the residual sum of squares using the target integrated navigation algorithm. Further, based on the integrity monitoring algorithm corresponding to the target integrated navigation algorithm and the residual sum of squares, it calculates the horizontal protection level. The integrity monitoring algorithm is set within the integrity monitoring module. Finally, based on the horizontal protection level and a preset threshold, it generates a prompt message and sends it to the autonomous driving control unit. This invention verifies the functionality of the integrity monitoring module before monitoring the in-vehicle integrated navigation system, avoiding missed detections or errors due to module failure or malfunction, thus improving monitoring reliability and effectiveness. Furthermore, the integrity monitoring module of this invention uses two calculation modes for monitoring, simplifying the calculation and avoiding additional computational load.

[0136] Figure 5 This is a schematic diagram of a terminal provided in an embodiment of the present invention. Figure 5 As shown, the terminal 5 in this embodiment includes a processor 501, a memory 502, and a computer program 505 stored in the memory 502 and executable on the processor 501. When the processor 501 executes the computer program 505, it implements the steps in the various monitoring method embodiments described above, for example... Figure 2 Steps 201-205 are shown. Alternatively, when processor 501 executes computer program 505, it implements the functions of each module / unit in the above-described monitoring device embodiments, for example... Figure 4 The functions of modules / units 401-405 shown.

[0137] The present invention also provides a readable storage medium storing a computer program, which, when executed by a processor, is used to implement a monitoring method provided in the various embodiments described above, including:

[0138] Determine if the integrity monitoring module is working properly;

[0139] If the integrity monitoring module is working properly, the target integrated navigation algorithm is determined based on the GNSS correction data;

[0140] Calculate the sum of squared residuals using a target-integrated navigation algorithm;

[0141] Based on the integrity monitoring algorithm and residual sum of squares corresponding to the target integrated navigation algorithm, the horizontal protection level is calculated, wherein the integrity monitoring algorithm is set in the integrity monitoring module;

[0142] Based on the horizontal protection level and preset threshold, a prompt message is generated and sent to the autonomous driving control unit.

[0143] In one possible implementation, determining whether the integrity monitoring module is functioning correctly includes:

[0144] Send a request signal to the integrity monitoring module;

[0145] If no response signal is received from the integrity monitoring module, the integrity monitoring module is not working properly and sends a reset signal to the microcontroller.

[0146] If the integrity monitoring module receives a response signal in response to the request signal, the integrity monitoring module will operate normally.

[0147] In one possible implementation, a target integrated navigation algorithm is determined based on GNSS correction data, including:

[0148] Determine whether the GNSS correction data was successfully unpacked;

[0149] If the GNSS correction data is successfully unpacked, the target integrated navigation algorithm is the first integrated navigation algorithm, which is used to execute the integrated positioning solution;

[0150] If the GNSS correction data unpacking fails, the target integrated navigation algorithm is the second integrated navigation algorithm, which is used to execute the dead reckoning solution.

[0151] In one possible implementation, a target-integrated navigation algorithm is used to calculate the residual sum of squares, including:

[0152] The extended Kalman filter algorithm is used to calculate the error covariance;

[0153] After processing the error covariance, we obtain the longitude variance and latitude variance;

[0154] Calculate the sum of squared residuals based on the longitude and latitude variances.

[0155] In one possible implementation, the error covariance is expressed by the following formula:

[0156] P k =HP k-1 H T +Q

[0157] Where H is the measurement matrix, H T Let H be the transpose of H, Q be the measurement noise, and P be the transpose of H. k Let P be the error covariance at time k. k-1 Let be the error covariance at time k-1.

[0158] In one possible implementation, the horizontal protection level is calculated based on the integrity monitoring algorithm corresponding to the target integrated navigation algorithm and the residual sum of squares, including:

[0159] Calculate the lateral error between the vehicle's first position coordinates and the vehicle's second position coordinates, where the first position coordinates are the coordinates output by the integrated navigation algorithm module, and the second position coordinates are the coordinates output by the network real-time dynamic positioning algorithm module;

[0160] The horizontal protection level is obtained by multiplying the lateral error by the sum of squared residuals.

[0161] In one possible implementation, the horizontal protection level is calculated based on the integrity monitoring algorithm corresponding to the target integrated navigation algorithm and the residual sum of squares, including:

[0162] The squared residual is used as the level of protection.

[0163] In one possible implementation, a warning message is generated based on the horizontal protection level and a preset threshold, and the warning message is sent to the autonomous driving control unit, including:

[0164] If the level of protection exceeds the preset threshold, an alarm signal is generated and sent to the autonomous driving control unit.

[0165] In one possible implementation, before determining whether the GNSS correction data has been successfully unpacked, the following steps are also included:

[0166] Determine whether the observations of the GNSS receiver meet the preset observations.

[0167] The readable storage medium can be a computer storage medium or a communication medium. A communication medium includes any medium that facilitates the transfer of computer programs from one location to another. A computer storage medium can be any available medium accessible to a general-purpose or special-purpose computer. For example, a readable storage medium is coupled to a processor, enabling the processor to read information from and write information to the readable storage medium. Of course, the readable storage medium can also be a component of the processor. The processor and the readable storage medium can reside in an Application-Specific Integrated Circuit (ASIC). Alternatively, the ASIC can be located in a user device. Of course, the processor and the readable storage medium can also exist as discrete components in a communication device. The readable storage medium can be a read-only memory (ROM), random access memory (RAM), CD-ROM, magnetic tape, floppy disk, and optical data storage device, etc.

[0168] The present invention also provides a program product including executable instructions stored in a readable storage medium. At least one processor of the device can read the executable instructions from the readable storage medium, and the execution of the executable instructions by the at least one processor causes the device to implement a monitoring method provided in the various embodiments described above, including:

[0169] Determine if the integrity monitoring module is working properly;

[0170] If the integrity monitoring module is working properly, the target integrated navigation algorithm is determined based on the GNSS correction data;

[0171] Calculate the sum of squared residuals using a target-integrated navigation algorithm;

[0172] Based on the integrity monitoring algorithm and residual sum of squares corresponding to the target integrated navigation algorithm, the horizontal protection level is calculated, wherein the integrity monitoring algorithm is set in the integrity monitoring module;

[0173] Based on the horizontal protection level and preset threshold, a prompt message is generated and sent to the autonomous driving control unit.

[0174] In one possible implementation, determining whether the integrity monitoring module is functioning correctly includes:

[0175] Send a request signal to the integrity monitoring module;

[0176] If no response signal is received from the integrity monitoring module, the integrity monitoring module is not working properly and sends a reset signal to the microcontroller.

[0177] If the integrity monitoring module receives a response signal in response to the request signal, the integrity monitoring module will operate normally.

[0178] In one possible implementation, a target integrated navigation algorithm is determined based on GNSS correction data, including:

[0179] Determine whether the GNSS correction data was successfully unpacked;

[0180] If the GNSS correction data is successfully unpacked, the target integrated navigation algorithm is the first integrated navigation algorithm, which is used to execute the integrated positioning solution;

[0181] If the GNSS correction data unpacking fails, the target integrated navigation algorithm is the second integrated navigation algorithm, which is used to execute the dead reckoning solution.

[0182] In one possible implementation, a target-integrated navigation algorithm is used to calculate the residual sum of squares, including:

[0183] The extended Kalman filter algorithm is used to calculate the error covariance;

[0184] After processing the error covariance, we obtain the longitude variance and latitude variance;

[0185] Calculate the sum of squared residuals based on the longitude and latitude variances.

[0186] In one possible implementation, the error covariance is expressed by the following formula:

[0187] P k =HP k-1 H T +Q

[0188] Where H is the measurement matrix, H T Let H be the transpose of H, Q be the measurement noise, and P be the transpose of H. k Let P be the error covariance at time k. k-1 Let be the error covariance at time k-1.

[0189] In one possible implementation, the horizontal protection level is calculated based on the integrity monitoring algorithm corresponding to the target integrated navigation algorithm and the residual sum of squares, including:

[0190] Calculate the lateral error between the vehicle's first position coordinates and the vehicle's second position coordinates, where the first position coordinates are the coordinates output by the integrated navigation algorithm module, and the second position coordinates are the coordinates output by the network real-time dynamic positioning algorithm module;

[0191] The horizontal protection level is obtained by multiplying the lateral error by the sum of squared residuals.

[0192] In one possible implementation, the horizontal protection level is calculated based on the integrity monitoring algorithm corresponding to the target integrated navigation algorithm and the residual sum of squares, including:

[0193] The squared residual is used as the level of protection.

[0194] In one possible implementation, a warning message is generated based on the horizontal protection level and a preset threshold, and the warning message is sent to the autonomous driving control unit, including:

[0195] If the level of protection exceeds the preset threshold, an alarm signal is generated and sent to the autonomous driving control unit.

[0196] In one possible implementation, before determining whether the GNSS correction data has been successfully unpacked, the following steps are also included:

[0197] Determine whether the observations of the GNSS receiver meet the preset observations.

[0198] In the embodiments of the above-described device, it should be understood that the processor can be a Central Processing Unit (CPU), or other general-purpose processors, digital signal processors (DSPs), application-specific integrated circuits (ASICs), etc. The general-purpose processor can be a microprocessor or any conventional processor. The steps of the method disclosed in this invention can be directly manifested as being executed by a hardware processor, or executed by a combination of hardware and software modules within the processor.

[0199] The above embodiments are only used to illustrate the technical solutions of the present invention, and are not intended to limit it. Although the present invention has been described in detail with reference to the foregoing embodiments, those skilled in the art should understand that modifications can still be made to the technical solutions described in the foregoing embodiments, or equivalent substitutions can be made to some of the technical features. Such modifications or substitutions do not cause the essence of the corresponding technical solutions to deviate from the spirit and scope of the technical solutions of the embodiments of the present invention, and should all be included within the protection scope of the present invention.

Claims

1. A monitoring method, characterized in that, include: Determine if the integrity monitoring module is working properly; If the integrity monitoring module is working properly, the target integrated navigation algorithm is determined based on the GNSS correction data; Using the target integrated navigation algorithm, calculate the residual sum of squares; Based on the integrity monitoring algorithm corresponding to the target integrated navigation algorithm and the residual sum of squares, the horizontal protection level is calculated, wherein the integrity monitoring algorithm is set in the integrity monitoring module; Based on the horizontal protection level and the preset threshold, a prompt message is generated and sent to the autonomous driving control unit; The step of calculating the residual sum of squares using the target integrated navigation algorithm includes: The extended Kalman filter algorithm is used to calculate the error covariance; The error covariance is processed to obtain the longitude variance and latitude variance; Based on the longitude variance and latitude variance, the residual sum of squares is calculated, wherein the calculation method for the residual sum of squares based on the longitude variance and latitude variance is as follows: Where SSE is the residual sum of squares, var_lon is the longitude variance, and var_lat is the latitude variance.

2. The monitoring method as described in claim 1, characterized in that, The determination of whether the integrity monitoring module is working properly includes: Send a request signal to the integrity monitoring module; If no response signal is received from the integrity monitoring module in response to the request signal, the integrity monitoring module is not working properly and sends a reset signal to the microcontroller; If the integrity monitoring module receives a response signal in response to the request signal, the integrity monitoring module will operate normally.

3. The monitoring method as described in claim 1, characterized in that, The target integrated navigation algorithm based on GNSS correction data includes: Determine whether the GNSS correction data was successfully unpacked; If the GNSS correction data is successfully unpacked, the target integrated navigation algorithm is the first integrated navigation algorithm, wherein the first integrated navigation algorithm is used to execute the integrated positioning solution; If the GNSS correction data unpacking fails, the target integrated navigation algorithm is the second integrated navigation algorithm, wherein the second integrated navigation algorithm is used to execute the dead reckoning solution.

4. The monitoring method as described in claim 1, characterized in that, The error covariance is expressed by the following formula: in, For the measurement matrix, for transpose, To measure noise, Let k be the error covariance. Let be the error covariance at time k-1.

5. The monitoring method as described in claim 1, characterized in that, The calculation of the horizontal protection level based on the integrity monitoring algorithm corresponding to the target integrated navigation algorithm and the residual sum of squares includes: Calculate the lateral error between the vehicle's first position coordinates and the vehicle's second position coordinates, where the first position coordinates are the coordinates output by the integrated navigation algorithm module, and the second position coordinates are the coordinates output by the network real-time dynamic positioning algorithm module; The horizontal protection level is obtained by multiplying the lateral error with the sum of squared residuals.

6. The monitoring method as described in claim 1, characterized in that, The calculation of the horizontal protection level based on the integrity monitoring algorithm corresponding to the target integrated navigation algorithm and the residual sum of squares includes: The sum of squared residuals is used as the level of protection.

7. The monitoring method as described in claim 5 or 6, characterized in that, The step of generating a prompt message based on the horizontal protection level and a preset threshold, and sending the prompt message to the autonomous driving control unit, includes: If the level of protection exceeds the preset threshold, an alarm signal is generated and sent to the autonomous driving control unit.

8. The monitoring method as described in claim 3, characterized in that, Before determining whether the GNSS correction data has been successfully unpacked, the process also includes: Determine whether the observations of the GNSS receiver meet the preset observations.

9. A monitoring device, characterized in that, include: The judgment module is used to determine whether the integrity monitoring module is working properly; The algorithm determination module is used to determine the target integrated navigation algorithm based on GNSS correction data, assuming the integrity monitoring module is working properly. The first calculation module is used to calculate the sum of squared residuals using the target integrated navigation algorithm; The second calculation module is used to calculate the horizontal protection level based on the integrity monitoring algorithm corresponding to the target integrated navigation algorithm and the residual sum of squares, wherein the integrity monitoring algorithm is set in the integrity monitoring module; The prompting module is used to generate prompting information based on the horizontal protection level and a preset threshold, and send the prompting information to the autonomous driving control unit; The step of calculating the residual sum of squares using the target integrated navigation algorithm includes: The extended Kalman filter algorithm is used to calculate the error covariance; The error covariance is processed to obtain the longitude variance and latitude variance; Based on the longitude variance and latitude variance, the residual sum of squares is calculated, wherein the calculation method for the residual sum of squares based on the longitude variance and latitude variance is as follows: Where SSE is the residual sum of squares, var_lon is the longitude variance, and var_lat is the latitude variance.

Images