Data processing methods, apparatus, equipment and computer storage media

Abstract

This disclosure provides a data processing method, apparatus, device, and computer storage medium. First, frame loss detection is performed on first fused positioning data and first GNSS data to obtain reliable positioning data without frame loss. Then, data alignment is performed according to a standard output time to obtain first positioning data corresponding to the standard output time, which is used for data filtering. Finally, more reliable second positioning data is filtered out from the first positioning data for output. In this way, during the high-frequency output of the integrated navigation system, frame loss faults can be addressed, and the data without frame loss can be compared and filtered to output the most reliable positioning data. This ensures the continuity and integrity of the integrated navigation system in the vehicle terminal under high-frequency output conditions, improving the reliability of the integrated navigation in the vehicle terminal.

Description

Technical Field

[0001] This disclosure belongs to the field of navigation technology, and in particular relates to a data processing method, apparatus, device and computer storage medium. Background Technology

[0002] Global Navigation Satellite System (GNSS) and Strapdown Inertial Navigation System (SINS) have strong complementary advantages, and the GNSS / SINS integrated navigation system is widely used in vehicle navigation applications. With the large-scale and rapid development of applications such as autonomous driving and intelligent vehicle IoT, the requirements for the frequency, continuity, and integrity of the output results of the above-mentioned integrated navigation system are also becoming more stringent.

[0003] However, in practical applications, GNSS signals or SINS data from integrated navigation systems are prone to frame loss or errors, leading to deviations in the system's output. When the output of the integrated navigation system deviates, it can pose unpredictable risks to downstream applications. Summary of the Invention

[0004] This disclosure provides a data processing method, apparatus, device, and computer storage medium that, through data filtering, obtains more reliable positioning data, thereby improving the reliability of vehicle-mounted terminals in integrated navigation applications.

[0005] On one hand, this disclosure provides a data processing method applied to an in-vehicle terminal, the method comprising:

[0006] Acquire the first fused positioning data and the first Global Navigation Satellite System (GNSS) data;

[0007] Based on the first time information in the first fused positioning data and the second time information in the first global navigation satellite system GNSS data, frame loss detection is performed to obtain the second fused positioning data and / or the second global navigation satellite system GNSS data without frame loss.

[0008] The second fused positioning data and / or the second Global Navigation Satellite System (GNSS) data are aligned according to a standard output time to obtain the first positioning data corresponding to the standard output time; the standard output time is the data output time determined according to a preset output frequency; the first positioning data includes the third fused positioning data and / or the third Global Navigation Satellite System (GNSS) data aligned to the standard output time.

[0009] The third fused positioning data and / or the third Global Navigation Satellite System (GNSS) data are filtered according to a preset filtering strategy to obtain the second positioning data and output it.

[0010] In some embodiments, aligning the second fused positioning data and / or the second Global Navigation Satellite System (GNSS) data according to a standard output time includes at least one of the following:

[0011] The time information of the second fused positioning data is aligned with the standard output time, and the second fused positioning data is interpolated according to the standard output time to obtain the third fused positioning data corresponding to the standard output time.

[0012] Second Global Navigation Satellite System (GNSS) data aligned with the standard output time is identified as Third Global Navigation Satellite System (GNSS) data.

[0013] In some embodiments, the third fused positioning data and / or the third Global Navigation Satellite System (GNSS) data are filtered according to a preset filtering strategy to obtain second positioning data and output, including at least one of the following:

[0014] When the first positioning data contains one of the third fused positioning data and the third global navigation satellite system GNSS data, the corresponding third fused positioning data or the third global navigation satellite system GNSS data is determined as the first data filtering result, and the first data filtering result is output as the second positioning data.

[0015] When the first positioning data includes the third fused positioning data and the third global navigation satellite system (GNSS) data, the third fused positioning data and the third global navigation satellite system (GNSS) data are compared and filtered to obtain the second data filtering result, and the second data filtering result is output as the second positioning result.

[0016] In some embodiments, the comparison and filtering of third-party fused positioning data and third-party Global Navigation Satellite System (GNSS) data includes:

[0017] The difference between the third fused positioning data and the third global navigation satellite system GNSS data is used to obtain the horizontal position difference and the vertical position difference.

[0018] When both the horizontal position difference and the vertical position difference are less than the preset position threshold, and the third global navigation satellite system GNSS data meets the first preset condition, the third global navigation satellite system GNSS data is determined as the second data screening result;

[0019] When both the horizontal and vertical position differences are less than the preset position thresholds, and the third global navigation satellite system (GNSS) data does not meet the first preset condition, the third fused positioning data is determined as the second data filtering result.

[0020] In some embodiments, comparing and filtering third fused positioning data and third Global Navigation Satellite System (GNSS) data further includes:

[0021] When the difference in horizontal position and / or vertical position is greater than a preset position threshold, the second positioning data corresponding to the previous epoch of the first positioning data is obtained;

[0022] According to the preset velocity model, the second positioning data of the previous epoch is extrapolated to the standard output time to obtain the extrapolated position data;

[0023] The extrapolated location data, the third fused positioning data, and the third Global Navigation Satellite System (GNSS) data are compared and filtered to obtain the second data filtering result.

[0024] In some embodiments, the second positioning data of the previous epoch is extrapolated to the standard output time according to a preset velocity model to obtain extrapolated position data, including:

[0025] Using the odometer speed value obtained from the vehicle terminal, or the average speed value of the speed value in the third fusion positioning data within a preset speed range, the second positioning data of the previous epoch is extrapolated horizontally to obtain the extrapolated horizontal position at the corresponding standard output time.

[0026] Using the vertical velocity value corresponding to the second positioning data of the previous epoch, the second positioning data of the previous epoch is vertically extrapolated to obtain the extrapolated vertical position at the corresponding standard output time.

[0027] The extrapolated horizontal and vertical positions are defined as the extrapolated position data.

[0028] In some embodiments, extrapolated location data, third fused positioning data, and third Global Navigation Satellite System (GNSS) data are compared and filtered to obtain a second data filtering result, including:

[0029] The extrapolated position data is subtracted from the third fused positioning data and the third Global Navigation Satellite System (GNSS) data respectively to obtain the first set of position difference values ​​and the second set of position difference values.

[0030] Compare the position differences of the first group and the second group, and determine the third fused positioning data or third Global Navigation Satellite System (GNSS) data corresponding to the smaller group as the second data filtering result.

[0031] In some embodiments, after determining the smaller set of corresponding third fused positioning data or third Global Navigation Satellite System (GNSS) data as the second data filtering result, the method further includes:

[0032] Based on the positional difference between the second data screening result and the extrapolated positional data, the corresponding confidence adjustment factor is determined using a preset confidence adjustment model.

[0033] The second data screening results are adjusted by a confidence level adjustment factor to obtain the third location data.

[0034] In some embodiments, frame loss detection is performed based on first time information in the first fused positioning data and second time information in the first Global Navigation Satellite System (GNSS) data, and second fused positioning data and / or second GNSS data without frame loss are obtained, including:

[0035] The first time difference is obtained by subtracting the first time information from the third time information of the GNSS data of the previous epoch corresponding to the second time information.

[0036] When the first time difference meets the second preset condition, it is determined that the first global navigation satellite system GNSS data has lost frames; and when the second preset condition is not met, the first global navigation satellite system GNSS data is determined as second global navigation satellite system GNSS data without lost frames.

[0037] When the first time difference meets the third preset condition, it is determined that the first fused positioning data has lost a frame; and when the third preset condition is not met, the first fused positioning data is determined as the second fused positioning data without lost frames.

[0038] In some embodiments, the second preset condition includes: the first time difference is positive, and the absolute value of the first time difference exceeds N times the duration of the output interval corresponding to the preset output frequency;

[0039] The third preset condition includes: the first time difference is negative, and the absolute value of the first time difference exceeds N times the duration of the output interval corresponding to the preset output frequency.

[0040] On the other hand, embodiments of this disclosure provide a data processing apparatus, the apparatus comprising:

[0041] The acquisition module is used to acquire the first fused positioning data and the first Global Navigation Satellite System (GNSS) data;

[0042] The detection module is used to perform frame loss detection based on the first time information in the first fused positioning data and the second time information in the first global navigation satellite system GNSS data, and to obtain the second fused positioning data and / or the second global navigation satellite system GNSS data without frame loss.

[0043] The alignment module is used to align the second fused positioning data and / or the second Global Navigation Satellite System (GNSS) data according to a standard output time to obtain the first positioning data corresponding to the standard output time; the standard output time is the data output time determined according to a preset output frequency; the first positioning data includes the third fused positioning data and / or the third Global Navigation Satellite System (GNSS) data aligned to the standard output time;

[0044] The filtering output module is used to filter the third fused positioning data and / or the third global navigation satellite system GNSS data according to a preset filtering strategy to obtain the second positioning data and output it.

[0045] In another aspect, embodiments of this disclosure provide a data processing apparatus, the apparatus including: a processor and a memory storing computer program instructions;

[0046] The steps of implementing a data processing method according to any one embodiment when a processor executes computer program instructions.

[0047] In another aspect, embodiments of this disclosure provide a computer storage medium storing computer program instructions, which, when executed by a processor, implement the steps of a data processing method according to any one embodiment.

[0048] The data processing method, apparatus, device, and computer storage medium of this disclosure first perform frame loss detection on first fused positioning data and first GNSS data to obtain reliable positioning data without frame loss. Then, data alignment is performed according to a standard output time to obtain first positioning data corresponding to the standard output time for data filtering. Finally, more reliable second positioning data is filtered out from the first positioning data and output. In this way, during the high-frequency result output process of the integrated navigation system, frame loss faults can be addressed, and the data without frame loss can be compared and filtered to output the most reliable positioning data. This ensures the continuity and integrity of the integrated navigation system in the vehicle terminal under high-frequency result output conditions, improving the reliability of the integrated navigation in the vehicle terminal. Attached Figure Description

[0049] To more clearly illustrate the technical solutions of the embodiments of this disclosure, the accompanying drawings used in the embodiments of this disclosure will be briefly introduced below. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0050] Figure 1 This is a schematic flowchart of a data processing method provided in one embodiment of the present disclosure;

[0051] Figure 2 This is a schematic flowchart of a data processing method provided in a specific embodiment of this disclosure;

[0052] Figure 3 This is a flowchart illustrating a data processing method in one example of this disclosure;

[0053] Figure 4 This is a schematic flowchart of a data processing method provided in another specific embodiment of this disclosure;

[0054] Figure 5 This is a flowchart illustrating a data processing method in another example of this disclosure;

[0055] Figure 6A This is a flowchart illustrating another example of the data processing method disclosed in this publication;

[0056] Figure 6B This is a flowchart illustrating a data processing method in yet another example of this disclosure;

[0057] Figure 7 This is a flowchart illustrating a data processing method in yet another specific embodiment of this disclosure;

[0058] Figure 8 This is a schematic diagram of the structure of a data processing apparatus provided in another embodiment of this disclosure;

[0059] Figure 9 This is a schematic diagram of the structure of a data processing device provided in another embodiment of this disclosure. Detailed Implementation

[0060] The features and exemplary embodiments of various aspects of this disclosure will now be described in detail. To make the objectives, technical solutions, and advantages of this disclosure clearer, the following detailed description, in conjunction with the accompanying drawings and specific embodiments, will provide a further detailed description. It should be understood that the specific embodiments described herein are intended only to explain this disclosure and not to limit it. For those skilled in the art, this disclosure can be implemented without some of these specific details. The following description of the embodiments is merely to provide a better understanding of this disclosure by illustrating examples.

[0061] It should be noted that, in this document, relational terms such as "first" and "second" are used merely to distinguish one entity or operation from another, and do not necessarily require or imply any such actual relationship or order between these entities or operations. Furthermore, the terms "comprising," "including," or any other variations thereof are intended to cover non-exclusive inclusion, such that a process, method, article, or apparatus that comprises a list of elements includes not only those elements but also other elements not expressly listed, or elements inherent to such a process, method, article, or apparatus. Without further limitations, an element defined by the phrase "comprising..." does not exclude the presence of additional identical elements in the process, method, article, or apparatus that includes said element.

[0062] Global Navigation Satellite System (GNSS) and Strapdown Inertial Navigation System (SINS) have strong complementary advantages, and the GNSS / SINS integrated navigation system is widely used in vehicle navigation applications. In vehicle integrated navigation applications, the GNSS / SINS integrated navigation system can further integrate information such as the vehicle's wheel speed to obtain more accurate fused positioning data, thus providing more precise location information.

[0063] However, in practical applications, especially in complex urban environments, GNSS is susceptible to data loss or gross errors due to environmental factors (such as terrain obstruction). Furthermore, SINS may suffer from biased results due to a lack of observation updates (i.e., inability to fuse with GNSS data) or the fusion of incorrect GNSS observations. Simultaneously, within the fusion framework of conventional integrated navigation systems, factors such as frame loss by sensors (e.g., inertial measurement units, IMUs) can cause the integrated navigation system to fail to output results in a timely manner, posing unpredictable risks to downstream applications.

[0064] To address the problems of the prior art, this disclosure provides a data processing method, apparatus, device, and computer storage medium. The data processing method provided by this disclosure is described first.

[0065] Figure 1 A flowchart illustrating a data processing method provided in one embodiment of this disclosure is shown. Figure 1 As shown, this method is applied to an in-vehicle terminal, and the method includes:

[0066] S101: Acquire the first fused positioning data and the first Global Navigation Satellite System (GNSS) data;

[0067] S102: Based on the first time information in the first fused positioning data and the second time information in the first global navigation satellite system GNSS data, perform frame loss detection and obtain the second fused positioning data and / or the second global navigation satellite system GNSS data without frame loss;

[0068] S103: Align the second fused positioning data and / or the second Global Navigation Satellite System (GNSS) data according to the standard output time to obtain the first positioning data corresponding to the standard output time; the standard output time is the data output time determined according to the preset output frequency; the first positioning data includes the third fused positioning data and / or the third Global Navigation Satellite System (GNSS) data aligned to the standard output time;

[0069] S104: Filter the third fused positioning data and / or the third Global Navigation Satellite System (GNSS) data according to a preset filtering strategy to obtain the second positioning data and output it.

[0070] In this embodiment, the first fused positioning data and the first Global Navigation Satellite System (GNSS) data come from different data sources, making it unlikely that both types of data will be simultaneously missing or erroneous. Therefore, this embodiment first performs frame loss detection on the first fused positioning data and the first GNSS data to obtain second fused positioning data and / or second GNSS data without frame loss. Then, the data is aligned according to the standard output time to obtain the first positioning data corresponding to the standard output time. Next, the more reliable second positioning data is selected and output from the first positioning data. In this way, during the high-frequency output of the integrated navigation system, frame loss faults can be detected, and the data without frame loss can be compared and filtered to output the most reliable positioning data. This ensures the continuity and integrity of the integrated navigation system in the vehicle terminal during high-frequency output, improving the reliability of the integrated navigation in the vehicle terminal.

[0071] In one specific embodiment, step S101, acquiring the first fused positioning data and the first Global Navigation Satellite System (GNSS) data, may specifically include:

[0072] Acquire at least the first fused positioning data obtained by fusing inertial navigation data and Global Positioning Satellite System (GNSS) data; and

[0073] Acquire first Global Navigation Satellite System (GNSS) data, including at least second time information.

[0074] Typically, during vehicle operation, the onboard terminal continuously acquires GNSS data, SINS data, and wheel speed information from the odometer. Based on the acquired data from at least these three heterogeneous sources, the onboard terminal first performs time updates and observation updates.

[0075] During the time update process, SINS data is primarily used for mechanical orchestration and state prediction to obtain preliminary positioning results. Based on these preliminary positioning results, observation updates can then proceed. During the observation update process, the results of the time update are filtered and updated using currently acquired GNSS or odometry data to obtain the first fused positioning data.

[0076] When there are data loss frames or data errors in GNSS data, SINS data, and wheel speed information from the odometer, some or all of the three types of data will still be fused, but the resulting fused positioning data is not completely reliable. Therefore, in this embodiment, the vehicle terminal acquires the first fused positioning data for subsequent frame loss detection.

[0077] In this embodiment, the GNSS receiver outputs raw observation values ​​such as pseudorange and phase at a preset sampling rate (e.g., 10Hz), and outputs empty data packets containing time stamps (i.e., GNSS data packets containing only time information) in a completely unlocked scenario. After receiving the data packets (i.e., GNSS data from the First Global Navigation Satellite System) sent by the GNSS receiver, the vehicle-mounted terminal in this embodiment performs frame loss detection on the data packets to determine whether the data packets have lost frames.

[0078] It is understood that in this embodiment, the acquisition of the first Global Navigation Satellite System (GNSS) data and the acquisition of the first fused positioning data by the vehicle terminal are two different processes. Correspondingly, the GNSS data used to fuse the first fused positioning data is different data from the aforementioned first GNSS data, which are generated in two different processes.

[0079] Furthermore, since the calculation of fused positioning data takes less time than the calculation of GNSS data, in this embodiment, the updated fused positioning data is first cached in the data cache. When step S101 is executed, the latest cached fused positioning data is retrieved from the data cache and used as the aforementioned first fused positioning data.

[0080] After acquiring the first fused positioning data and the first Global Navigation Satellite System (GNSS) data, frame loss detection is performed. Frame loss detection can be referenced from [reference needed]. Figure 2 .

[0081] Figure 2 The diagram shown is a flowchart illustrating a data processing method provided in a specific embodiment of this disclosure.

[0082] like Figure 2 As shown, in this embodiment, in step S102, frame loss detection is performed based on the first time information in the first fused positioning data and the second time information in the first Global Navigation Satellite System (GNSS) data, and second fused positioning data and / or second GNSS data without frame loss are obtained. Specifically, this may include steps S201 to S203:

[0083] S201: Subtract the first time information from the third time information of the GNSS data of the previous epoch corresponding to the second time information to obtain the first time difference value.

[0084] Both the first fused positioning data and the first Global Navigation Satellite System (GNSS) data have predetermined update frequencies (i.e., output frequencies). The first time information in the first fused positioning data can be the time when the data is cached in the data buffer. The second time information in the first GNSS data can be the time when the vehicle-mounted terminal receives the data.

[0085] refer to Figure 3 After the vehicle-mounted terminal receives the first Global Navigation Satellite System (GNSS) data, if the GNSS data is a data packet without lost frames, it will perform GNSS positioning calculation on the data packet separately and store the GNSS positioning result in the GNSS positioning data storage area. Therefore, the aforementioned previous epoch GNSS data is the GNSS positioning result updated in the previous epoch of the second time information in the GNSS positioning data storage area.

[0086] Query the third time information of the previous epoch of GNSS data corresponding to the second time information, and subtract the first time information from the third time information to obtain the first time difference value.

[0087] S202: When the first time difference meets the second preset condition, it is determined that the first global navigation satellite system GNSS data has lost frames; and when the second preset condition is not met, the first global navigation satellite system GNSS data is determined as the second global navigation satellite system GNSS data without lost frames.

[0088] For example, the second preset condition includes: the first time difference is positive, and the absolute value of the first time difference exceeds N times the duration of the output interval corresponding to the preset output frequency, where N is a preset value and N can be a positive number.

[0089] When the first time difference meets the second preset condition, it indicates that the first fused positioning data is updated normally, but the GNSS data is not updated normally, that is, the first global navigation satellite system GNSS data is losing frames.

[0090] When the first time difference does not meet the second preset condition, it can be directly determined that the first global navigation satellite system GNSS data has not lost frames, and the first global navigation satellite system GNSS data is identified as the second global navigation satellite system GNSS data with no lost frames, and subsequent calculation steps are performed.

[0091] S203: When the first time difference meets the third preset condition, it is determined that the first fused positioning data has lost frames; and when the third preset condition is not met, the first fused positioning data is determined as the second fused positioning data without lost frames.

[0092] For example, the third preset condition includes: the first time difference is negative, and the absolute value of the first time difference exceeds N times the duration of the output interval corresponding to the preset output frequency.

[0093] When the first time difference meets the third preset condition, it indicates that the first fused positioning data has not been updated normally, but the GNSS data has been updated normally. The first fused positioning data has not been updated normally, possibly due to anomalies such as frame loss in some or all of the GNSS data, SINS data, and odometer data in the fused positioning. The first fused positioning data is not the latest positioning data, so it can be discarded and no longer participate in the subsequent calculation steps of the method in this embodiment.

[0094] When the first time difference does not meet the third preset condition, it can be directly determined that the first global navigation satellite system GNSS data has not lost frames, and the first fused positioning data is determined as the second fused positioning data without lost frames, which can be used for subsequent calculation steps.

[0095] In this embodiment, by performing frame loss detection on the fused positioning data and received GNSS data, and selecting the data without frame loss for subsequent fusion processes, the final positioning result is obtained. This not only ensures the reliability of the underlying data upon which the positioning result is based, but also guarantees the continuity of the final positioning data output. Furthermore, to a certain extent, it can effectively solve the problem of not being able to output positioning results when GNSS data packets are empty or when sensors (such as IMUs) drop frames during traditional navigation processes. For example, by using GNSS data without frame loss to achieve the final positioning result output, it helps improve the availability of the system.

[0096] In this embodiment, reference Figure 2 Step S103, performed based on the frame loss detection result, involves aligning the second fused positioning data and / or the second Global Navigation Satellite System (GNSS) data according to the standard output time. This may specifically include at least one of the following steps S204 and S206:

[0097] S204: Align the time information of the second fused positioning data with the standard output time, and perform interpolation calculation on the second fused positioning data according to the standard output time to obtain the third fused positioning data corresponding to the standard output time;

[0098] S205: Identify second Global Navigation Satellite System (GNSS) data that is aligned with the standard output time as third Global Navigation Satellite System (GNSS) data.

[0099] If, after frame loss detection, neither the first Global Navigation Satellite System (GNSS) data nor the first fused positioning data has lost any frames, then the above two data alignments in this embodiment are performed; if, after frame loss detection, neither the first GNSS data nor the first fused positioning data has lost any frames, then only the data for which no frames have lost are aligned with the corresponding items.

[0100] In this embodiment, the standard output time is the data output time determined by the vehicle terminal during navigation calculation based on a preset navigation and positioning data output frequency. Generally, the update frequency of the GNSS positioning data storage area is the same as the navigation and positioning data output frequency. The time information in the second global navigation satellite system (GNSS) data can be directly aligned to the standard output time, and the second GNSS data corresponding to the standard output time is directly identified as the third GNSS data.

[0101] Since the update time of the fused positioning data is different from the standard output time, in this embodiment, the time information of the second fused positioning data is time-aligned with the standard output time, and the second fused positioning data is interpolated according to the standard output time to obtain the third fused positioning data corresponding to the standard output time.

[0102] In this embodiment, as Figure 2 As shown, after obtaining the third fused positioning data and the third Global Navigation Satellite System (GNSS) data corresponding to the standard output time, the following is also included:

[0103] S206: The first positioning data is composed of the third fused positioning data and / or the third global navigation satellite system GNSS data.

[0104] The subsequent data filtering process is executed based on the data contained in the first positioning data corresponding to the standard output time. This avoids positioning result output deviations caused by inconsistencies in the time attributes between different data points during the data filtering process.

[0105] In one specific embodiment, based on the data contained in the first positioning data, step S104 filters the third fused positioning data and / or the third Global Navigation Satellite System (GNSS) data according to a preset filtering strategy to obtain and output the second positioning data. Specifically, this may include at least one of the following:

[0106] When the first positioning data contains one of the third fused positioning data and the third global navigation satellite system GNSS data, the corresponding third fused positioning data or the third global navigation satellite system GNSS data is determined as the first data filtering result, and the first data filtering result is output as the second positioning data.

[0107] When the first positioning data includes the third fused positioning data and the third global navigation satellite system (GNSS) data, the third fused positioning data and the third global navigation satellite system (GNSS) data are compared and filtered to obtain the second data filtering result, and the second data filtering result is output as the second positioning result.

[0108] In this embodiment, if only third fused positioning data or only third Global Navigation Satellite System (GNSS) data is obtained after frame loss detection and data alignment, and the first positioning data contains only one type of data and cannot be compared, then the corresponding third fused positioning data or third GNSS data can be determined as the first data filtering result, and the first data filtering result is output as the second positioning data. The second positioning data is the final positioning result.

[0109] If, after frame loss detection and data alignment, the third fused positioning data and the third Global Navigation Satellite System (GNSS) data are obtained, the first positioning data, which contains both types of data, can be compared and filtered to select the more reliable data for output.

[0110] For example, in step S104, such as Figure 4 As shown, if third-generation fused positioning data and third-generation GNSS data are obtained after frame loss detection and data alignment, the comparison and filtering of third-generation fused positioning data and third-generation GNSS data may specifically include the following steps S401 to S403:

[0111] S401: Subtract the third fused positioning data from the third Global Navigation Satellite System (GNSS) data to obtain the horizontal position difference and the vertical position difference.

[0112] In step S401, the third fused positioning data and the third Global Navigation Satellite System (GNSS) data each contain positioning results. These two positioning results are mapped to the same coordinate system, such as the WGS-84 coordinate system (World Geodetic System-1984 Coordinate System), to obtain two specific position coordinates. The difference between these two coordinates is then calculated to obtain the horizontal and vertical position differences between them.

[0113] S402: When both the horizontal position difference and the vertical position difference are less than the preset position threshold, and the third global navigation satellite system GNSS data meets the first preset condition, the third global navigation satellite system GNSS data is determined as the second data filtering result.

[0114] In this embodiment, the preset position threshold is an empirical value, which can be set according to the actual situation.

[0115] The first presupposition condition is for determining whether the GNSS data from the third global navigation satellite system is reliable. Those skilled in the art will understand that the reliability of GNSS positioning results obtained by vehicle-mounted terminals through GNSS calculations can typically be assessed by setting up a conventional data quality assessment model.

[0116] In this step, when both the horizontal position difference and the vertical position difference are less than the preset position threshold, and the third global navigation satellite system (GNSS) data is reliable, the third GNSS data is determined as the second data filtering result.

[0117] S403: When both the horizontal position difference and the vertical position difference are less than the preset position threshold, and the third global navigation satellite system GNSS data does not meet the first preset condition, the third fused positioning data is determined as the second data filtering result.

[0118] For example, in step S104, when comparing and filtering the third fused positioning data and the third Global Navigation Satellite System (GNSS) data, such as... Figure 5 As shown, the specific steps S501 to S503 may also be included:

[0119] S501: When the difference in horizontal position and / or vertical position is greater than a preset position threshold, obtain the second positioning data of the previous epoch corresponding to the first positioning data.

[0120] When either the horizontal position difference or the vertical position difference exceeds a preset position threshold, data filtering is performed using the second positioning data from the previous epoch corresponding to the current first positioning data. The second positioning data from the previous epoch corresponding to the current first positioning data is the final positioning result output from the previous epoch.

[0121] S502: According to the preset velocity model, the second positioning data of the previous epoch is extrapolated to the standard output time to obtain the extrapolated position data.

[0122] In this step, the position of the second positioning data from the previous epoch is mapped to a coordinate system, such as the WGS-84 coordinate system. The coordinates of the second positioning data from the previous epoch are then extrapolated according to a preset velocity model.

[0123] In this step, the preset velocity model can be represented by the following equation (1):

[0124] Pos derived =Pos k-1 +Vel*dt (1)

[0125] In equation (1), Pos derived For the recursively obtained position (i.e., extrapolated position data), Pos k-1 dt represents the position in the second positioning data of the previous epoch, Vel represents the recursive velocity information, and dt represents the time interval between the standard output time corresponding to the first positioning data and the previous epoch.

[0126] Based on the coordinates of the second positioning data from the previous epoch, when extrapolating horizontally according to the preset speed model, the recursive speed information Vel can be obtained from the odometer speed value acquired by the vehicle terminal, or from the average level speed value obtained from the third fused positioning data. This average level speed value is the average speed value of the speed value in the third fused positioning data within the preset speed range.

[0127] The horizontal position in the second positioning data of the previous epoch is extrapolated horizontally using the odometer speed value or the average speed value obtained from the third fusion positioning data to obtain the extrapolated horizontal position at the corresponding standard output time.

[0128] Based on the coordinates of the second positioning data from the previous epoch, when extrapolating in the vertical direction according to the preset velocity model, the recursive velocity information Vel can use the corresponding vertical velocity value in the second positioning data from the previous epoch to obtain the extrapolated vertical position at the corresponding standard output time.

[0129] Then, the extrapolated horizontal position and extrapolated vertical position are determined as the extrapolated position data.

[0130] S503: Compare and filter the extrapolated position data, the third fused positioning data, and the third Global Navigation Satellite System (GNSS) data to obtain the second data filtering result.

[0131] For example, such as Figure 6A As shown, this step may specifically include:

[0132] S601: Subtract the extrapolated position data from the third fused positioning data and the third Global Navigation Satellite System (GNSS) data respectively to obtain the first set of position difference values ​​and the second set of position difference values.

[0133] refer to Figure 6B As shown, the extrapolated position data and the third fused positioning data are subtracted in the same coordinate system to obtain the first set of position difference values; the first set of position difference values ​​includes the first set of horizontal position difference values ​​and the first set of vertical position difference values.

[0134] Similarly, the extrapolated position data and the GNSS data from the third global navigation satellite system are subtracted to obtain the second set of position difference values; the second set of position difference values ​​includes the second set of horizontal position difference values ​​and the second set of vertical position difference values.

[0135] S602: Compare the position difference of the first group and the position difference of the second group, and determine the third fused positioning data or third global navigation satellite system GNSS data corresponding to the smaller group as the second data filtering result.

[0136] When the position difference between the first group and the second group is large, the third Global Navigation Satellite System (GNSS) data is selected as the second data selection result. When the position difference between the first group and the second group is small, the third fused positioning data is selected as the second data selection result.

[0137] S603: Determine the second data filtering result as the second positioning result and output it.

[0138] In this embodiment, the third Global Navigation Satellite System (GNSS) data corresponds to the GNSS positioning information obtained from individual GNSS calculations, while the third fused positioning data corresponds to the fused positioning data of GNSS data, SINS data, and odometer wheel speed data. Since SINS data can contain various navigation information such as acceleration, velocity, position, heading, and attitude, this embodiment allows for the filtering of heterogeneous data. Redundancy monitoring is performed using individual GNSS positioning information, navigation information including heading information, and odometer wheel speed information, and frame loss detection is used to filter out data with missing frames. The data without missing frames is then filtered again to select the more accurate and reliable data results as the final positioning result, thus optimizing the output positioning result and enhancing the safety of the entire vehicle system.

[0139] In one specific implementation, after obtaining the second data filtering result, such as Figure 7 As shown, the data processing method disclosed herein may further include:

[0140] S701: Based on the position difference between the second data screening result and the extrapolated position data, determine the corresponding confidence adjustment factor through the preset confidence adjustment model;

[0141] S702: Adjust the second data screening results by the confidence adjustment factor to obtain the third positioning data.

[0142] In this embodiment, the position difference between the second data filtering result and the extrapolated position data is calculated to obtain the corresponding position difference value. Based on this position difference value, the standard deviation of the output second data filtering result is amplified to adjust the confidence level of the output result.

[0143] Based on the corresponding positional difference dv, the confidence level of the results is adjusted according to the following formulas (2) and (3):

[0144]

[0145] std modified =std original *factor (3)

[0146] In equation (2) above, factor is the confidence adjustment factor of the output result, dv is the position difference between the second data screening result and the extrapolated position data; K and threshold are the correlation coefficient and the difference threshold, respectively, and both K and threshold are empirical values.

[0147] In equation (3) above, std modified std original These are the standard deviations of the positional results before and after adjustment, respectively.

[0148] Based on the confidence adjustment factor determined by the location difference dv, the second data screening result is adjusted according to formula (3) to obtain the third positioning data, which is then output as the final positioning result.

[0149] The output results, adjusted according to the confidence level, are more consistent with the actual situation of the selected results, which can improve the reliability and integrity of the system.

[0150] Figure 8 A schematic diagram of a data processing apparatus structure provided in an embodiment of this disclosure is shown. Figure 8 As shown, the device includes:

[0151] Acquisition module 801 is used to acquire first fused positioning data and first global navigation satellite system (GNSS) data;

[0152] The detection module 802 is used to perform frame loss detection based on the first time information in the first fused positioning data and / or based on the second time information in the first global navigation satellite system GNSS data, and to obtain the second fused positioning data and / or the second global navigation satellite system GNSS data without frame loss.

[0153] Alignment module 803 is used to align the second fused positioning data and / or the second global navigation satellite system GNSS data according to a standard output time to obtain the first positioning data corresponding to the standard output time; the standard output time is the data output time determined according to a preset output frequency; the first positioning data includes the third fused positioning data and / or the third global navigation satellite system GNSS data aligned to the standard output time;

[0154] The filtering output module 804 is used to filter the third fused positioning data and / or the third global navigation satellite system GNSS data according to a preset filtering strategy to obtain the second positioning data and output it.

[0155] For example, the acquisition module 801 can perform the above... Figure 1 In step S101 shown above, the detection module 802 can perform the above-mentioned steps. Figure 1 In step S102 shown, the alignment module 803 can perform the above-described steps. Figure 1 The filtering output module 804 can perform the above-described step S103 shown in the figure. Figure 1 Step S104 is shown in the figure.

[0156] It should be noted that the above Figures 1 to 7 All relevant content of each step involved in the illustrated method embodiment can be referenced from the functional description of the corresponding functional module and can achieve its corresponding technical effect. For the sake of brevity, it will not be repeated here.

[0157] Figure 9 A schematic diagram of the hardware structure of the data processing device provided in an embodiment of this disclosure is shown.

[0158] The data processing device may include a processor 901 and a memory 902 storing computer program instructions.

[0159] Specifically, the processor 901 may include a central processing unit (CPU), an application specific integrated circuit (ASIC), or one or more integrated circuits that can be configured to implement the embodiments of this disclosure.

[0160] Memory 902 may include mass storage for data or instructions. For example, and not limitingly, memory 902 may include a hard disk drive (HDD), floppy disk drive, flash memory, optical disk, magneto-optical disk, magnetic tape, or Universal Serial Bus (USB) drive, or a combination of two or more of these. Where appropriate, memory 902 may include removable or non-removable (or fixed) media. Where appropriate, memory 902 may be internal or external to an integrated gateway disaster recovery device. In a particular embodiment, memory 902 is non-volatile solid-state memory. Typically, memory includes one or more tangible (non-transitory) computer-readable storage media (e.g., memory devices) encoded with software including computer-executable instructions, and when the software is executed (e.g., by one or more processors), it is operable to perform the operations described with reference to the method according to one aspect of this disclosure.

[0161] The processor 901 implements any of the data processing methods described in the above embodiments by reading and executing computer program instructions stored in the memory 902.

[0162] In one example, the data processing device may further include a communication interface 903 and a bus 910. Wherein, as... Figure 9 As shown, the processor 901, memory 902, and communication interface 903 are connected through bus 910 and complete communication with each other.

[0163] The communication interface 903 is mainly used to realize communication between various modules, devices, units and / or equipment in the embodiments of this disclosure.

[0164] Bus 910 includes hardware, software, or both, that couples components of a data processing device together. For example, and not limitingly, the bus may include an Accelerated Graphics Port (AGP) or other graphics bus, an Enhanced Industry Standard Architecture (EISA) bus, a Front Side Bus (FSB), HyperTransport (HT) interconnect, an Industry Standard Architecture (ISA) bus, an Infinite Bandwidth Interconnect, a Low Pin Count (LPC) bus, a memory bus, a Microchannel Architecture (MCA) bus, a Peripheral Component Interconnect (PCI) bus, a PCI-Express (PCI-X) bus, a Serial Advanced Technology Attachment (SATA) bus, a Video Electronics Standards Association Local (VLB) bus, or other suitable buses, or combinations of two or more of these. Where appropriate, bus 910 may include one or more buses. Although specific buses are described and illustrated in embodiments of this disclosure, this disclosure contemplates any suitable bus or interconnect.

[0165] Furthermore, in conjunction with the data processing methods in the above embodiments, this disclosure can provide a computer storage medium for implementation. The computer storage medium stores computer program instructions; when these computer program instructions are executed by a processor, they implement any of the data processing methods in the above embodiments.

[0166] The functional modules shown in the above-described block diagram can be implemented as hardware, software, firmware, or a combination thereof. When implemented in hardware, they can be, for example, electronic circuits, application-specific integrated circuits (ASICs), appropriate firmware, plug-ins, function cards, etc. When implemented in software, the elements of this disclosure are programs or code segments used to perform the required tasks.

[0167] It should also be noted that the exemplary embodiments mentioned in this disclosure describe methods or systems based on a series of steps or apparatus. However, this disclosure is not limited to the order of the above steps; that is, the steps can be performed in the order mentioned in the embodiments, or in a different order, or several steps can be performed simultaneously.

[0168] The aspects of this disclosure have been described above with reference to flowchart illustrations and / or block diagrams of methods, apparatus (systems), and computer program products according to embodiments of this disclosure. It should be understood that each block in the flowchart illustrations and / or block diagrams, and combinations of blocks in the flowchart illustrations and / or block diagrams, can be implemented by computer program instructions. These computer program instructions can be provided to a processor of a general-purpose computer, a special-purpose computer, or other programmable data processing apparatus to produce a machine such that these instructions, executable via the processor of the computer or other programmable data processing apparatus, enable the implementation of the functions / actions specified in one or more blocks of the flowchart illustrations and / or block diagrams. Such a processor can be, but is not limited to, a general-purpose processor, a special-purpose processor, a special application processor, or a field-programmable logic circuit. It is also understood that each block in the block diagrams and / or flowcharts, and combinations of blocks in the block diagrams and / or flowcharts, can also be implemented by special-purpose hardware performing the specified functions or actions, or can be implemented by a combination of special-purpose hardware and computer instructions.

[0169] The above description is merely a specific embodiment of this disclosure. Those skilled in the art will clearly understand that, for the sake of convenience and brevity, the specific working processes of the systems, modules, and units described above can be referred to the corresponding processes in the foregoing method embodiments, and will not be repeated here. It should be understood that the protection scope of this disclosure is not limited thereto. Any person skilled in the art can easily conceive of various equivalent modifications or substitutions within the technical scope disclosed in this disclosure, and these modifications or substitutions should all be covered within the protection scope of this disclosure.

Claims

1. A data processing method, characterized in that, Applications in vehicle-mounted terminals include: Acquire first fused positioning data and first global navigation satellite system (GNSS) data; the first fused positioning data is obtained by filtering and updating the SINS data using the currently acquired GNSS data and the wheel speed information of the odometer during the observation and update process based on wheel speed information from the odometer, GNSS data and strapdown inertial navigation system (SINS) data. Based on the first time information in the first fused positioning data and the second time information in the first global navigation satellite system GNSS data, frame loss detection is performed to obtain the second fused positioning data and / or the second global navigation satellite system GNSS data without frame loss. The second fused positioning data and / or the second Global Navigation Satellite System (GNSS) data are aligned according to a standard output time to obtain the first positioning data corresponding to the standard output time; the standard output time is a data output time determined according to a preset output frequency; the first positioning data includes third fused positioning data and / or third Global Navigation Satellite System (GNSS) data aligned to the standard output time; The third fused positioning data and / or the third Global Navigation Satellite System (GNSS) data are filtered for reliability according to a preset filtering strategy to obtain the second positioning data and output it. The step of aligning the second fused positioning data and / or the second Global Navigation Satellite System (GNSS) data according to the standard output time includes at least one of the following: The time information of the second fused positioning data is aligned with the standard output time, and the second fused positioning data is interpolated according to the standard output time to obtain the third fused positioning data corresponding to the standard output time. The second Global Navigation Satellite System (GNSS) data aligned with the standard output time is identified as the third Global Navigation Satellite System (GNSS) data.

2. The data processing method according to claim 1, characterized in that, The step of filtering the third fused positioning data and / or the third Global Navigation Satellite System (GNSS) data according to a preset filtering strategy to obtain and output the second positioning data includes at least one of the following: When the first positioning data contains one of the third fused positioning data and the third global navigation satellite system GNSS data, the corresponding third fused positioning data or the third global navigation satellite system GNSS data is determined as the first data filtering result, and the first data filtering result is output as the second positioning data. When the first positioning data includes the third fused positioning data and the third Global Navigation Satellite System (GNSS) data, the third fused positioning data and the third GNSS data are compared and filtered to obtain a second data filtering result, and the second data filtering result is output as the second positioning data.

3. The data processing method according to claim 2, characterized in that, The comparison and filtering of the third fused positioning data and the third Global Navigation Satellite System (GNSS) data includes: The difference between the third fused positioning data and the third global navigation satellite system (GNSS) data is calculated to obtain the horizontal position difference and the vertical position difference. When both the horizontal position difference and the vertical position difference are less than a preset position threshold, and the third global navigation satellite system GNSS data meets the first preset condition, the third global navigation satellite system GNSS data is determined as the second data filtering result; When both the horizontal position difference and the vertical position difference are less than the preset position threshold, and the third global navigation satellite system (GNSS) data does not meet the first preset condition, the third fused positioning data is determined as the second data filtering result.

4. The data processing method according to claim 3, characterized in that, The comparison and filtering of the third fused positioning data and the third Global Navigation Satellite System (GNSS) data also includes: When the horizontal position difference and / or vertical position difference is greater than the preset position threshold, the second positioning data corresponding to the previous epoch of the first positioning data is obtained; According to the preset velocity model, the second positioning data of the previous epoch is extrapolated to the standard output time to obtain the extrapolated position data; The extrapolated location data, the third fused positioning data, and the third Global Navigation Satellite System (GNSS) data are compared and filtered to obtain the second data filtering result.

5. The data processing method according to claim 4, characterized in that, The step of extrapolating the second positioning data of the previous epoch to the standard output time according to the preset velocity model to obtain extrapolated position data includes: Using the odometer speed value obtained by the vehicle terminal, or the average speed value of the speed value in the third fused positioning data within a preset speed range, the second positioning data of the previous epoch is extrapolated horizontally to obtain the extrapolated horizontal position corresponding to the standard output time. Using the vertical velocity value corresponding to the second positioning data of the previous epoch, the second positioning data of the previous epoch is vertically extrapolated to obtain the extrapolated vertical position corresponding to the standard output time. The extrapolated horizontal position and extrapolated vertical position are determined as the extrapolated position data.

6. The data processing method according to claim 4, characterized in that, The step of comparing and filtering the extrapolated position data, the third fused positioning data, and the third Global Navigation Satellite System (GNSS) data to obtain the second data filtering result includes: The extrapolated position data is subtracted from the third fused positioning data and the third Global Navigation Satellite System (GNSS) data respectively to obtain the first set of position difference values ​​and the second set of position difference values. By comparing the first set of position differences with the second set of position differences, the third fused positioning data or the third global navigation satellite system GNSS data corresponding to the smaller set is determined as the second data filtering result.

7. The data processing method according to claim 6, characterized in that, After determining the smaller set of corresponding third fused positioning data or third Global Navigation Satellite System (GNSS) data as the second data filtering result, the method further includes: Based on the positional difference between the second data filtering result and the extrapolated positional data, a corresponding confidence adjustment factor is determined using a preset confidence adjustment model. The second data filtering result is adjusted by the confidence adjustment factor to obtain the third location data.

8. The data processing method according to claim 1, characterized in that, The step of performing frame loss detection based on the first time information in the first fused positioning data and the second time information in the first Global Navigation Satellite System (GNSS) data, and obtaining second fused positioning data and / or second GNSS data without frame loss, includes: The first time difference is obtained by subtracting the first time information from the third time information of the GNSS data of the previous epoch corresponding to the second time information; When the first time difference meets the second preset condition, it is determined that the first Global Navigation Satellite System (GNSS) data has lost frames; and when the second preset condition is not met, the first GNSS data is determined as the second GNSS data that has not lost frames. When the first time difference meets the third preset condition, it is determined that the first fused positioning data has lost a frame; and when the third preset condition is not met, the first fused positioning data is determined as the second fused positioning data that has not lost a frame.

9. The data processing method according to claim 8, characterized in that, The second preset condition includes: the first time difference is positive, and the absolute value of the first time difference exceeds N times the duration of the output interval corresponding to the preset output frequency; The third preset condition includes: the first time difference is negative, and the absolute value of the first time difference exceeds N times the duration of the output interval corresponding to the preset output frequency.

10. A data processing apparatus, characterized in that, include: The acquisition module is used to acquire the first fused positioning data and the first Global Navigation Satellite System (GNSS) data; The detection module is used to perform frame loss detection based on the first time information in the first fused positioning data and the second time information in the first Global Navigation Satellite System (GNSS) data, and obtain second fused positioning data and / or second GNSS data without frame loss; the first fused positioning data is obtained by filtering and updating the SINS data using the currently acquired GNSS data and the wheel speed information of the odometer during the observation update process based on wheel speed information from the odometry, GNSS data and strapdown inertial navigation system (SINS) data; An alignment module is used to align the second fused positioning data and / or the second Global Navigation Satellite System (GNSS) data according to a standard output time to obtain first positioning data corresponding to the standard output time; the standard output time is a data output time determined according to a preset output frequency; the first positioning data includes third fused positioning data and / or third Global Navigation Satellite System (GNSS) data aligned to the standard output time; The filtering output module is used to filter the third fused positioning data and / or the third global navigation satellite system GNSS data according to a preset filtering strategy to obtain the second positioning data and output it. The alignment module is specifically used for at least one of the following: The time information of the second fused positioning data is aligned with the standard output time, and the second fused positioning data is interpolated according to the standard output time to obtain the third fused positioning data corresponding to the standard output time. The second Global Navigation Satellite System (GNSS) data aligned with the standard output time is identified as the third Global Navigation Satellite System (GNSS) data.

11. A data processing device, characterized in that, The device includes: a processor and a memory storing computer program instructions; When the processor executes the computer program instructions, it implements the data processing method as described in any one of claims 1-9.

12. A computer storage medium, characterized in that, The computer storage medium stores computer program instructions, which, when executed by a processor, implement the data processing method as described in any one of claims 1-9.

Images