Satellite navigation positioning evaluation method and device and storage medium

Abstract

The application discloses a positioning evaluation method and device for satellite navigation and a storage medium. The evaluation method comprises the following steps: acquiring a first positioning result of a satellite navigation system; calculating a sequence of track directions of the satellite navigation system based on the first positioning result; calculating the dispersion degree of the track directions and the maximum track direction deviation based on the sequence of the track directions; and evaluating the positioning result quality of the satellite navigation system based on the dispersion degree of the track directions and the maximum track direction deviation. The application can evaluate the positioning result of the satellite navigation positioning system.

Description

Technical Field

[0001] This disclosure relates to the field of integrated navigation and positioning technology, and in particular to a positioning evaluation method, apparatus, and storage medium for satellite navigation. Background Technology

[0002] Global Navigation Satellite System (GNSS), as a core means of acquiring spatial location information, has been widely used in fields such as autonomous driving, robot localization, and high-precision surveying. However, in actual operations, the positioning performance of GNSS systems often fluctuates drastically due to factors such as geographical obstruction and multipath interference. Currently, existing navigation satellite positioning schemes typically lack mechanisms for effectively evaluating the quality of positioning results. If the system blindly uses the current positioning results in navigation calculations when positioning quality deteriorates, it will directly lead to a significant decrease in overall positioning accuracy. Therefore, how to evaluate navigation satellite positioning results for use as a reference for integrated navigation systems deserves attention. Summary of the Invention

[0003] In view of this, embodiments of the present disclosure provide a positioning evaluation method, apparatus and storage medium for satellite navigation, with the aim of evaluating the positioning results of navigation satellite positioning systems in integrated navigation application scenarios.

[0004] In a first aspect, a positioning evaluation method for satellite navigation is provided, comprising: acquiring a first positioning result of a satellite navigation system; calculating and determining a course sequence of the satellite navigation system based on the first positioning result; calculating the dispersion of the course and the maximum course deviation based on the course sequence; and evaluating the quality of the positioning result of the satellite navigation system based on the dispersion of the course and the maximum course deviation.

[0005] Optionally, the positioning evaluation method further includes: obtaining the second positioning result of the inertial navigation system; calculating and determining the trajectory sequence of the satellite navigation system based on the first positioning result, including: starting the trajectory calculation when the first positioning result or the second positioning result meets the preset validity conditions; and determining the trajectory sequence according to the changes in the trajectory within the first preset time window.

[0006] The above-described satellite navigation positioning evaluation method acquires the initial positioning result from the satellite navigation system and constructs a complete trajectory sequence by calculating the changes in trajectory direction. This transforms discrete positioning point information into a feature sequence that records the evolution of the vehicle's motion direction over time. Based on this, statistical feature extraction is performed on the trajectory sequence to calculate the dispersion of the trajectory direction and the maximum trajectory deviation, thereby evaluating the quality of the satellite navigation system's positioning results. This transforms abstract and difficult-to-measure trajectory geometric features into quality evaluation indicators with quantifiable hierarchical levels. Ultimately, the positioning system can determine the reliability of the initial positioning result under the current navigation and positioning environment based on the determined positioning result quality, providing a basis for subsequent integrated navigation algorithms to adaptively adjust weights or intercept abnormal results based on data quality.

[0007] Optionally, the positioning evaluation method is used for the carrier, and the preset validity conditions include: at the first epoch, the carrier's wheel speed is valid and the wheel speed is greater than a first speed threshold, and the latitude and longitude in the first positioning result of the second epoch are both greater than zero, and the time difference between adjacent first and second epochs meets the preset sampling interval; or, at the first epoch, the wheel speed is invalid, the first speed in the first positioning result or the second speed in the second positioning result is greater than the first speed threshold, and the latitude and longitude in the first positioning result of the second epoch are both greater than zero, and the time difference between adjacent first and second epochs meets the preset sampling interval; wherein, the preset sampling interval is determined based on the data sampling interval of the satellite navigation system, and the second epoch is earlier than the first epoch.

[0008] Optionally, the positioning result quality of the satellite navigation system is evaluated based on the dispersion of the course direction and the maximum course direction deviation, including: matching the course direction standard deviation and the maximum course direction deviation with multiple preset course direction standard deviation thresholds and multiple maximum course direction deviation thresholds based on the fixed solution type of the first positioning result, and determining the corresponding trajectory smoothness level; obtaining the constant velocity quality, and determining the positioning result quality based on the constant velocity quality and the trajectory smoothness level.

[0009] Optionally, the positioning evaluation method for obtaining the speed determination quality includes: detecting whether the wheel speed of the carrier is effective; when the wheel speed of the carrier is detected to be effective, calculating the speed difference sequence between the speed of the satellite navigation system and the wheel speed within a second preset time window; and determining the mean and standard deviation of the speed difference as the speed determination quality based on the speed difference sequence.

[0010] Optionally, it further includes: determining whether the first positioning result meets preset anomaly conditions based on the trajectory smoothness level, the mean velocity difference, and the standard deviation of the velocity difference; when the preset anomaly conditions are met, determining that the first positioning result is in an unreliable state; wherein, the preset anomaly conditions include at least one of the following: the trajectory smoothness level is greater than or equal to a first level threshold, and the mean velocity difference is greater than a first mean threshold or the standard deviation of the velocity difference is greater than a first standard deviation threshold; or, the trajectory smoothness level is equal to a preset anomaly level; or, the mean velocity difference is greater than a second mean threshold or the standard deviation of the velocity difference is greater than a second standard deviation threshold.

[0011] Optionally, it also includes: when it is determined that the first positioning result is in an unreliable state, calculating the position measurement vector magnitude of the first positioning result; selecting the maximum value from the position observation noise corresponding to the first positioning result, the position measurement vector magnitude, and the preset distance corresponding to the interval where the position measurement vector magnitude is located, as the satellite navigation system position observation noise in which the first positioning result participates in the integrated navigation positioning fusion; when it is determined that the first positioning result is in an unreliable state and the velocity observation result in the first positioning result meets the preset discard condition, stopping the velocity observation result from participating in the integrated navigation positioning fusion.

[0012] Optionally, when the magnitude of the position measurement vector is greater than the first distance threshold, the preset distance is the first distance value; when the magnitude of the position measurement vector is greater than the second distance threshold and less than or equal to the first distance threshold, the preset distance is the second distance value; when the magnitude of the position measurement vector is less than or equal to the second distance threshold, the preset distance is the third distance value; wherein, the first distance value is greater than the second distance value, and the second distance value is greater than the third distance value.

[0013] Secondly, a positioning evaluation device for satellite navigation is provided for combined navigation of a satellite navigation system and an inertial navigation system, comprising: an acquisition unit for acquiring a first positioning result of the satellite navigation system; a trajectory sequence determination unit for calculating and determining the trajectory sequence of the satellite navigation system based on the first positioning result; a trajectory sequence calculation unit for calculating the dispersion of the trajectory and the maximum trajectory deviation based on the trajectory sequence; and a positioning result quality determination unit for evaluating the positioning result quality of the satellite navigation system based on the trajectory standard deviation and the maximum trajectory deviation.

[0014] Thirdly, a computer-readable storage medium is provided, on which instructions are stored, which, when read by a processor, implement the satellite navigation positioning evaluation method provided in the first aspect above. Attached Figure Description

[0015] The accompanying drawings used in the description of the embodiments of this disclosure are briefly introduced below: Figure 1A schematic flowchart of a satellite navigation positioning evaluation method provided in some embodiments of this application is shown; Figure 2 A flowchart illustrating a method for determining the quality of positioning results provided in some embodiments of this application is shown. Figure 3 A flowchart illustrating a method for determining constant-speed mass provided in some embodiments of this application is shown. Figure 4 A flowchart illustrating a method for determining the quality of positioning results provided in some embodiments of this application is shown. Figure 5 The diagram shows a flowchart illustrating a method for determining the quality of positioning results based on constant velocity quality and trajectory smoothness level, provided in some embodiments of this application. Figure 6 A schematic diagram of the structure of a satellite navigation positioning evaluation device provided in some embodiments of this application is shown. Detailed Implementation

[0016] To more clearly illustrate the technical solutions in the embodiments of this disclosure, examples of implementation methods of this disclosure will be described below with reference to the accompanying drawings. The accompanying drawings described below are merely some embodiments of this disclosure. For those skilled in the art, other drawings and other implementation methods can be obtained based on these drawings without creative effort. Adjustments and improvements made without departing from the concept of this disclosure are all within the protection scope of this disclosure.

[0017] To keep the drawings simple, each figure only schematically shows the parts relevant to the embodiment, and they do not represent the actual structure of the product. In addition, for the sake of clarity and ease of understanding, some figures only schematically show parts of components with the same structure or function, and there may actually be more or fewer components with the same structure or function.

[0018] In this disclosure, unless otherwise expressly specified and limited, ordinal numbers, such as “first”, “second”, etc., are used only to distinguish and describe related objects, and should not be construed as indicating or implying the relative importance or order between related objects; furthermore, they do not represent the quantity of related objects. “Multiple” includes two or more, and other quantifiers are similar.

[0019] Global Navigation Satellite Systems (GNSS), as a crucial infrastructure for acquiring position and velocity information of a vehicle, are key to achieving precise operations in fields such as intelligent driving and industrial robotics. In the field of navigation and positioning technology, to ensure positioning continuity, the positioning results of GNSS and inertial navigation systems are typically fused. However, in complex conditions such as urban canyons or forest canopies, the signal of GNSS is easily damaged, resulting in positioning deviations or abnormal jumps. Current integrated navigation systems often struggle to identify the true reliability of positioning data due to a lack of real-time evaluation methods for the quality of positioning results. On the one hand, existing solutions cannot capture sudden changes in the positioning trajectory within a short period, leading to impaired trajectory smoothness; on the other hand, current technologies lack verification of data consistency among multiple sensors, preventing the system from responding promptly to velocity anomalies. These problems cause vehicles to continue using low-quality data for positioning even when the positioning quality is poor, resulting in a significant reduction in positioning accuracy and even threatening the operational safety of the GNSS-based vehicle. Therefore, how to accurately evaluate the quality of positioning results from GNSS is a pressing technical problem that needs to be solved in the field of navigation and positioning. To address the aforementioned issues, this application provides a method, apparatus, and storage medium for evaluating navigation satellite positioning results, aiming to enable the evaluation of navigation satellite positioning system positioning results in integrated navigation application scenarios.

[0020] The following description is in conjunction with the accompanying drawings: Figure 1 The diagram illustrates a flow chart of a satellite navigation positioning evaluation method provided in some embodiments of this application. This evaluation method is used for combined navigation of a satellite navigation system and an inertial navigation system, and includes at least the following steps: S110: Obtain the first positioning result from the satellite navigation system; S120: Calculate and determine the trajectory sequence of the satellite navigation system based on the first positioning result; S130: Based on the heading sequence, calculate the dispersion of the heading and the maximum heading deviation; S140: Evaluate the positioning quality of satellite navigation systems based on the dispersion of the course and the maximum course deviation.

[0021] The integrated navigation system described in the above embodiments can be mounted on a carrier, which can be a platform capable of supporting the integrated navigation equipment, such as a car, ship, robot, aircraft, or other equipment requiring positioning using integrated navigation equipment. The evaluation method for navigation satellite positioning results in this application can be implemented by the integrated navigation system or by a controller on the carrier (such as the central control unit of a car).

[0022] In the operation of integrated navigation, the first positioning result of the satellite navigation system can be obtained. This first positioning result reflects the spatial state information of the vehicle at the current moment, such as parameters including but not limited to the vehicle's position coordinates or motion velocity. Further, the trajectory sequence of the satellite navigation system can be calculated and determined based on the first positioning result. The calculation of the trajectory can analyze the geometric and physical characteristics of the satellite navigation system's output trajectory. For example, the spatial displacement vector between consecutive epochs can be extracted using the first positioning result, reflecting the instantaneous motion direction of the vehicle between adjacent sampling epochs. To capture dynamic disturbances during motion, this application can construct a complete trajectory sequence by calculating the change in trajectory, thereby transforming discrete positioning point information into a feature sequence that records the evolution trend of the vehicle's motion direction over time. Based on this, this application can also calculate the dispersion of the trajectory and the maximum trajectory deviation by extracting statistical features from the trajectory sequence. The dispersion of the trajectory can be determined using parameters such as the trajectory standard deviation, the mean absolute deviation of the trajectory, and the median absolute deviation. For example, taking the track orientation standard deviation as an example, this parameter can be used to quantify the overall dispersion of the carrier's motion direction within an observation period, thereby effectively identifying jitter phenomena in the trajectory. The maximum track orientation deviation, on the other hand, focuses on the most dramatic instantaneous direction jumps within the observation window, thus accurately capturing sudden changes in positioning points caused by multipath effects, non-line-of-sight interference, or satellite signal lock-off jumps. After obtaining the above multi-dimensional statistical characteristic parameters, this application can further determine the positioning result quality of the satellite navigation system based on the track orientation standard deviation and the maximum track orientation deviation. For example, the track orientation standard deviation can be compared with a preset track orientation standard deviation threshold, and the maximum track orientation deviation can be compared with a preset track orientation deviation threshold. When either or both exceed the threshold, different positioning result quality levels are given. For example, when neither exceeds the threshold, it indicates that the overall navigation trajectory presented by the first positioning result is very smooth, and the positioning result is relatively reliable, thus receiving a high positioning result quality evaluation; conversely, a lower positioning result quality evaluation is given. This transforms abstract and difficult-to-measure trajectory geometric features into quality evaluation indicators with quantifiable hierarchical levels. Ultimately, the system can determine the reliability of the first positioning result under the current navigation and positioning environment based on the determined positioning result quality. Thus, the originally singular positioning data is assigned a confidence label, providing a basis for subsequent integrated navigation algorithms to adaptively adjust weights based on data quality or intercept abnormal results. For example, it can increase the proportion of the first positioning result with a higher quality rating in the integrated navigation fusion positioning process, and vice versa, thereby improving the positioning accuracy and reliability of the integrated navigation system in complex positioning scenarios.

[0023] In some embodiments of this application, the satellite navigation positioning evaluation method further includes: acquiring a second positioning result from an inertial navigation system. Calculating and determining the trajectory sequence of the satellite navigation system based on the first positioning result includes: initiating trajectory calculation when the first positioning result or the second positioning result of the inertial navigation system meets a preset validity condition; and determining the trajectory sequence based on changes in the trajectory within a first preset time window.

[0024] The preset validity conditions include: at the first epoch, the vehicle's wheel speed is valid and greater than the first speed threshold, and the latitude and longitude in the first positioning result of the second epoch are both greater than zero, and the time difference between adjacent first and second epochs meets the preset satellite navigation system sampling interval; or, at the first epoch, the wheel speed is invalid, the first speed in the first positioning result or the second speed in the second positioning result is greater than the first speed threshold, and the latitude and longitude in the first positioning result of the second epoch are both greater than zero, and the time difference between adjacent first and second epochs meets the preset satellite navigation system sampling interval; wherein, the second epoch is earlier than the first epoch.

[0025] To ensure the accuracy of subsequent trajectory calculations and avoid noise interference, this application can pre-screen the validity of positioning data before calculating the trajectory based on the first positioning result. The trajectory calculation process is only formally initiated when the first positioning result or the second positioning result from the inertial navigation system meets the preset validity conditions. This ensures that the positioning points involved in the calculation have spatiotemporal continuity and are in a true state of motion, avoiding distortion of calculation results due to positioning drift of the vehicle or abnormal sensor data. Taking a vehicle equipped with a combined navigation system as an example, at the first epoch (i.e., the current detection epoch), the wheel speed data status fed back by the vehicle equipped with the combined navigation system can be identified first. For example, the wheel speed can be required to be greater than a first speed threshold to confirm that the vehicle is in a driving condition with a clear direction of motion. Simultaneously, the historical validity of the positioning data is traced back to verify that in the second epoch, earlier than the first epoch, both longitude and latitude values ​​are greater than zero, thereby confirming that the positioning system has entered the effective global coordinate output stage. Furthermore, the continuity of time is also a core criterion for determining data validity. Therefore, the time difference between adjacent first and second epochs can be required to meet the sampling interval requirements of the preset satellite navigation system. For example, this time difference should be within a preset reasonable ratio range to prevent logical jumps or breaks in the trajectory calculation due to data frame loss, communication delays, or severe sampling lag. In another scenario, when the wheel speed data at the first epoch is invalid due to hardware failure or communication interruption, the determination can be based on the speed observation value. As long as at least one of the first speed in the first positioning result or the second speed in the second positioning result is greater than the aforementioned first speed threshold, and simultaneously meets the conditions that the latitude and longitude of the second epoch are both greater than zero and the time difference between epochs is within the sampling interval constraint, the current positioning status can also be determined to be valid and trajectory calculation can be initiated. Through the above determination method, it can be ensured that the vehicle's wheel speed sensor can accurately control the validity of positioning data under both normal and abnormal operating conditions. After the above screening, the trajectory changes within the first preset time window can be further extracted. The first preset time window can be composed of multiple consecutive positioning epochs, thereby capturing the change process of the vehicle's motion direction within a short time series. By calculating the changes in the trajectory direction within this window, the trajectory direction sequence can be determined, laying a data foundation for subsequent extraction of trajectory smoothness features using statistical methods. This application can utilize the vehicle's velocity and spatiotemporal continuity as constraints, thereby reducing the calculation deviation of the trajectory direction and ensuring that the trajectory direction sequence can truly and effectively reflect the vehicle's driving trajectory characteristics.

[0026] In some embodiments of this application, the quality of positioning results of a satellite navigation system is evaluated based on the dispersion of the course direction and the maximum course direction deviation, including: matching the course direction standard deviation and the maximum course direction deviation with multiple preset course direction standard deviation thresholds and multiple maximum course direction deviation thresholds based on the fixed solution type of the first positioning result, and determining the corresponding trajectory smoothness level; obtaining the constant velocity quality, and determining the positioning result quality based on the constant velocity quality and the trajectory smoothness level.

[0027] In the above embodiments, the quality of satellite navigation system positioning results can be determined using a more refined hierarchical judgment. By differentially measuring the trajectory characteristics under different positioning accuracy states, accurate judgment of positioning anomalies can be achieved. In the field of satellite positioning technology, a fixed solution represents that the receiver has successfully solved the integer ambiguity of the carrier phase, and the corresponding motion trajectory should have extremely high geometric smoothness under ideal conditions. Based on this prior solution type state, taking the degree of dispersion determined by the track direction standard deviation as an example, the calculated track direction standard deviation and maximum track direction deviation can be matched hierarchically with multiple preset sets of track direction standard deviation thresholds and maximum track direction deviation thresholds. For example, when the system detects that the current epoch is a fixed solution, it will match a more stringent threshold logic. For example, if the track direction standard deviation is less than x degrees and the maximum track direction deviation is less than y degrees, the system determines that the corresponding trajectory smoothness level is a value of 1, representing the highest quality. Correspondingly, if the current epoch is in a non-fixed solution state, considering the inherent fluctuations in the signal processing process, it can dynamically switch to a relatively relaxed judgment boundary. For example, if the standard deviation of the trajectory is less than x+1 degrees and the maximum trajectory deviation is less than y+1 degrees, it will also be classified as trajectory smoothness level 1. By setting differentiated thresholds for different positioning solution states, the calculated statistical feature values ​​can be accurately mapped to multiple preset level intervals. These could include levels 2 and 3 representing good trajectory quality, and levels 4 and 5 representing average or poor trajectory quality. In extreme cases, if the standard deviation of the trajectory and the maximum trajectory deviation fluctuate drastically, for example, exceeding x+50 degrees and y+100 degrees respectively, the system can classify it as level 9, representing extremely poor trajectory quality. After completing the above level classification, the positioning result quality can be determined based on the matched trajectory smoothness level. This graded evaluation system not only quantifies the geometric smoothness of the current trajectory but also provides a highly discriminative decision-making basis for subsequent differentiated handling strategies based on different quality levels. The above values ​​are only examples; actual numerical settings can be set according to engineering design requirements, such as using binary numbers in machine language, etc., and are not specifically limited here.

[0028] In some embodiments of this application, Figure 2A flowchart illustrating a method for determining the quality of positioning results provided in some embodiments of this application is shown.

[0029] S201: Reset trajectory smoothness level; S202: Determine if the wheel speed is valid; if the wheel speed is valid, proceed to step S203; if the wheel speed is invalid, proceed to step S204. S203: Determine whether the wheel speed is greater than the first speed threshold, whether the latitude and longitude in the positioning result of the second epoch are greater than zero, and whether the time difference between adjacent detection epochs meets the preset satellite navigation system sampling interval; if the aforementioned conditions are met, proceed to step S205; if the aforementioned conditions are not met, proceed to step S215. S204: Determine whether the first velocity result of the satellite navigation system or the second velocity result of the inertial navigation system is greater than the first velocity threshold, whether the latitude and longitude in the positioning result of the second epoch are greater than zero, and whether the time difference between the first epoch and the second epoch meets the preset sampling interval of the satellite navigation system; if the aforementioned conditions are met, proceed to step S205; if the aforementioned conditions are not met, proceed to step S215. S205: Calculate the course direction based on the forward and backward position changes of the satellite navigation system; S206: Determine if the course direction of the second epoch is valid; if valid, proceed to step S207; if invalid, proceed to step S214. S207: Determine the change in track direction based on the difference between the track direction in the first epoch and the track direction in the second epoch, and perform angle reduction.

[0030] S208: Based on the changes in trajectory within the first preset time window, determine the sequence of trajectory changes, and calculate the standard deviation of the trajectory changes and the maximum trajectory deviation of the sequence. S209: When the first positioning result is a fixed solution, and the standard deviation of the trajectory is less than x degrees and the maximum trajectory deviation is less than y degrees, or when the first positioning result is a non-fixed solution, and the standard deviation of the trajectory is less than x+1 degrees and the maximum trajectory deviation is less than y+1 degrees, the trajectory smoothness level is determined to be level 1; if the requirements of step S209 are not met, the judgment in S210 is further executed. S210: If the standard deviation of the trajectory is less than x+1 degrees and the maximum trajectory deviation is less than y+1 degrees, the trajectory smoothness level is determined to be level 2; if the requirements of step S210 are not met, the judgment of S211 is further executed. S211: If the standard deviation of the trajectory is less than x+2 degrees and the maximum trajectory deviation is less than y+2 degrees, the trajectory smoothness level is determined to be level 3; if the requirements of step S211 are not met, the judgment of S212 is further executed. S212: When the first positioning result is a fixed solution, and the standard deviation of the trajectory is less than x+10 degrees and the maximum trajectory deviation is less than y+20 degrees, or when the first positioning result is a non-fixed solution, and the standard deviation of the trajectory is less than x+20 degrees and the maximum trajectory deviation is less than y+40 degrees, the trajectory smoothness level is determined to be level 4; if the requirements of step S212 are not met, the trajectory smoothness level is initially determined to be level 5, and the judgment in step S213 is executed. S213: When the standard deviation of the trajectory is greater than x+40 degrees and the maximum trajectory deviation is greater than y+100 degrees, the trajectory smoothness level is determined to be level 9. S214: Update the trajectory of the second epoch to the trajectory of the first epoch; S215: Clear the trajectory change buffer and determine the trajectory of the second epoch as invalid.

[0031] The specific implementation and beneficial effects of the above methods can be found in the above embodiments, and will not be repeated here.

[0032] In some embodiments of this application, determining the reliability of the first positioning result based on the positioning result quality further includes: determining the positioning result quality based on the constant velocity quality and the trajectory smoothness level; Figure 3 A flowchart illustrating a method for determining constant-velocity mass according to some embodiments of this application is shown. The method includes: S310: Detects whether the wheel speed of the carrier is effective; S320: When the vehicle's wheel speed is detected to be valid, calculate the speed difference sequence between the satellite navigation system's speed and the wheel speed within the second preset time window; S330: Based on the speed difference sequence, determine the mean and standard deviation of the speed difference as constant speed mass.

[0033] In the above embodiments, the validity of the wheel speed data fed back by the carrier equipped with the integrated navigation system is first detected. Since the wheel speed meter is directly installed on the carrier chassis, its data is less affected by external electromagnetic interference and can directly reflect the actual physical displacement of the carrier relative to the ground. Therefore, it has certain reference value in determining the accuracy of satellite velocity measurement. After confirming the validity of the wheel speed data, a specific second preset time window can be selected, such as an observation window containing multiple consecutive sampling epochs. Within this second preset time window, the deviation between the instantaneous velocity value of the satellite navigation system and the synchronously acquired carrier wheel speed value is continuously calculated, thereby transforming the originally isolated sampling points into a velocity difference sequence that can reflect the dynamic velocity change trend. After acquiring the velocity difference sequence, the distribution characteristics of the deviation can be calculated to determine the mean and standard deviation of the velocity difference, and this statistical index is used as the final velocity determination quality. Among them, the mean velocity difference can effectively reveal whether the satellite navigation system has persistent systematic errors caused by multipath interference or non-line-of-sight signals; while the standard deviation of the velocity difference can accurately capture the instantaneous velocity measurement instability caused by satellite lock-up or severe signal fluctuations. This application, through speed deviation detection, can compensate for the shortcomings of satellite navigation systems in evaluating a single dimension under complex operating conditions. By introducing speed quality verification, it ensures that the reliability judgment logic can be established on the constraints of real physical motion speed, thereby improving the accuracy of identifying dynamic abnormal data.

[0034] In some embodiments of this application, Figure 4 A flowchart illustrating another satellite navigation positioning evaluation method provided in some embodiments of this application is shown.

[0035] S401: Reset trajectory smoothness level; S402: Determine if the wheel speed is valid; if the wheel speed is valid, execute steps S403 and S4041; if the wheel speed is invalid, execute step 405. S403: Determine whether the wheel speed is greater than the first speed threshold, whether the latitude and longitude in the positioning result of the second epoch are greater than zero, and whether the time difference between adjacent detection epochs meets the preset satellite navigation system sampling interval; if the above conditions are met, execute step S406; if the above conditions are not met, execute step S416. S4041: When wheel speed is valid, calculate the speed difference sequence between the satellite navigation system speed and wheel speed within the second preset time window; S4042: Determine the mean and standard deviation of the speed difference based on the speed difference sequence; S405: Determine whether the first velocity result of the satellite navigation system or the second velocity result of the inertial navigation system is greater than the first velocity threshold, whether the latitude and longitude in the positioning result of the second epoch are greater than zero, and whether the time difference between the first epoch and the second epoch meets the preset sampling interval of the satellite navigation system; if the aforementioned conditions are met, execute step S406; if the aforementioned conditions are not met, execute step S416. S406: Calculate the course direction based on the forward and backward position changes of the satellite navigation system; S407: Determine if the course direction of the second epoch is valid; if valid, proceed to step S408; if invalid, proceed to step S415. S408: Determine the change in track direction based on the difference between the track direction in the first epoch and the track direction in the second epoch, and perform angle reduction.

[0036] S409: Based on the trajectory changes within the first preset time window, determine the trajectory change sequence, and calculate the trajectory standard deviation and maximum trajectory deviation of the trajectory change sequence; S410: When the first positioning result is a fixed solution, the mean velocity difference is less than the mean velocity difference threshold, the standard deviation of the velocity difference is less than the standard deviation of the velocity difference threshold, and the standard deviation of the trajectory is less than x degrees, and the maximum trajectory deviation is less than y degrees; or, when the first positioning result is a non-fixed solution, the mean velocity difference is less than the mean velocity difference threshold, the standard deviation of the velocity difference is less than the standard deviation of the velocity difference threshold, and the standard deviation of the trajectory is less than x+1 degrees, and the maximum trajectory deviation is less than y+1 degrees, the trajectory smoothness level is determined to be level 1; if the requirements of step S410 are not met, the judgment in S411 is further executed. S411: If the mean speed difference is less than the mean speed difference threshold, the standard deviation of the speed difference is less than the standard deviation of the speed difference threshold, the standard deviation of the trajectory is less than x+1 degrees, and the maximum trajectory deviation is less than y+1 degrees, then the trajectory smoothness level is determined to be level 2; if the requirements of step S411 are not met, then the judgment in S412 is further executed. S412: If the mean speed difference is less than the mean speed difference threshold, the standard deviation of the speed difference is less than the standard deviation of the speed difference threshold, the standard deviation of the trajectory is less than x+2 degrees, and the maximum trajectory deviation is less than y+2 degrees, then the trajectory smoothness level is determined to be level 3; if the requirements of step S412 are not met, then the judgment in S413 is further executed. S413: When the first positioning result is a fixed solution, the mean velocity difference is less than the mean velocity difference threshold, the standard deviation of the velocity difference is less than the standard deviation of the velocity difference threshold, and the standard deviation of the trajectory is less than x+10 degrees, and the maximum trajectory deviation is less than y+20 degrees; or, when the first positioning result is a non-fixed solution, the mean velocity difference is less than the mean velocity difference threshold, the standard deviation of the velocity difference is less than the standard deviation of the velocity difference threshold, and the standard deviation of the trajectory is less than x+20 degrees, and the maximum trajectory deviation is less than y+40 degrees, the trajectory smoothness level is determined to be level 4; if the requirements of step S413 are not met, the trajectory smoothness level is initially determined to be level 5, and the judgment in step S414 is executed. S414: When the standard deviation of the trajectory is greater than x+40 degrees and the maximum trajectory deviation is greater than y+100 degrees, the trajectory smoothness level is determined to be level 9. S415: Update the trajectory of the second epoch to the trajectory of the first epoch; S416: Clear the trajectory change buffer and determine the trajectory of the second epoch as invalid.

[0037] The specific implementation and beneficial effects of the above methods can be found in the above embodiments, and will not be repeated here.

[0038] In some embodiments of this application, determining the positioning result quality based on constant speed quality and trajectory smoothness level further includes: determining whether the first positioning result meets preset anomaly conditions based on trajectory smoothness level, mean velocity difference, and standard deviation of velocity difference; when the preset anomaly conditions are met, determining that the first positioning result is in an unreliable state; wherein, the preset anomaly conditions include at least one of the following: the trajectory smoothness level is greater than or equal to a first level threshold, and the mean velocity difference is greater than a first mean threshold or the standard deviation of velocity difference is greater than a first standard deviation threshold; or, the trajectory smoothness level is equal to a preset anomaly level; or, the mean velocity difference is greater than a second mean threshold or the standard deviation of velocity difference is greater than a second standard deviation threshold.

[0039] In the above embodiments, the reliability of the first positioning result quality evaluation can be improved by constructing a multi-dimensional evaluation mechanism. For example, by coupling the trajectory smoothness level, which reflects spatial geometric characteristics, with the velocity difference statistical characteristics, which reflect dynamic consistency, the positioning result quality of the satellite navigation system under complex operating conditions can be identified. In this application, the system can determine whether the first positioning result meets preset anomaly conditions based on the trajectory smoothness level, the mean velocity difference, and the standard deviation of the velocity difference. Once at least one of the preset anomaly conditions is met, the system determines that the first positioning result is in an unreliable state, thereby providing a clear logical trigger signal for downgrading the navigation satellite positioning result or intercepting the data. The design of the preset anomaly conditions can accommodate the differences in the impact of different degrees of signal interference on positioning accuracy, constructing a hierarchical judgment process. When the trajectory smoothness level is greater than or equal to the first level threshold (for example, the first level threshold can be set to level 4, which distinguishes between good and poor trajectory smoothness), it indicates that the positioning trajectory has significant geometric fluctuations. At this time, if the mean velocity difference is simultaneously detected to be greater than the first mean threshold, or the standard deviation of the velocity difference is greater than the first standard deviation threshold, it indicates that the positioning result deviates from the normal movement trend of the carrier in both velocity and trajectory dimensions, and the system determines that the positioning result is unreliable. This collaborative judgment mechanism can sensitively capture abnormal positioning conditions where a single indicator has not yet reached an extreme threshold, but the overall performance is significantly unsatisfactory. When the trajectory smoothness level is equal to the preset abnormality level (for example, level 9, the maximum abnormality level), regardless of the velocity dimension indicator, the system directly determines that the first positioning result is in an unreliable state. In this application, higher-level trajectory anomalies typically correspond to sudden jumps in the physical location of the positioning point caused by severe non-line-of-sight interference or multipath effects. Such data carries extremely high risk and must be intercepted. When the mean velocity difference is greater than the second mean threshold or the standard deviation of the velocity difference is greater than the second standard deviation threshold, the system also determines that the abnormal conditions are met. The second mean threshold is significantly larger than the first mean threshold, indicating an unacceptable deviation between the observed velocity of the satellite navigation system and the actual wheel speed of the vehicle, suggesting a possible severe jump in the satellite signal. Therefore, this application effectively addresses the problem of single judgment criteria and easy omissions in traditional schemes. This reliability judgment based on multi-dimensional features ensures that the integrated navigation system can adaptively adjust subsequent fusion strategies according to the true quality state of the first positioning result, thereby enhancing the safety and reliability of the navigation system in complex dynamic conditions such as urban canyons and under viaducts.

[0040] In some embodiments of this application, the method further includes: when it is determined that the first positioning result is in an unreliable state, calculating the position measurement vector magnitude of the first positioning result; selecting the maximum value from the position observation noise corresponding to the first positioning result, the position measurement vector magnitude, and the preset distance corresponding to the interval where the position measurement vector magnitude is located, as the satellite navigation system position observation noise in which the first positioning result participates in the integrated navigation positioning fusion; when it is determined that the first positioning result is in an unreliable state and the velocity observation result in the first positioning result meets the preset discard condition, stopping the velocity observation result from participating in the integrated navigation positioning fusion.

[0041] When the magnitude of the position measurement vector is greater than the first distance threshold, the preset distance is the first distance value; when the magnitude of the position measurement vector is greater than the second distance threshold and less than or equal to the first distance threshold, the preset distance is the second distance value; when the magnitude of the position measurement vector is less than or equal to the second distance threshold, the preset distance is the third distance value; wherein, the first distance value is greater than the second distance value, and the second distance value is greater than the third distance value.

[0042] In the above embodiments, once the first positioning result is determined to be unreliable, a more refined determination process can be initiated to prevent inferior satellite observation data from affecting the positioning result of the integrated navigation system. This application can calculate the position measurement vector magnitude of the first positioning result in real time. This position measurement vector magnitude reflects the spatial deviation distance between the instantaneous position coordinates output by the satellite navigation system and a reference benchmark (e.g., the predicted position calculated by the inertial navigation system or the fused position from the previous moment). The magnitude of this value can intuitively quantify the degree of change in the current positioning point and measure the magnitude of the data deviating from the true trajectory. Furthermore, the position observation noise in the first positioning result can be adaptively reconstructed based on the position measurement vector magnitude. The maximum value is selected from the original position observation noise corresponding to the first positioning result, the position measurement vector magnitude, and a preset distance constant corresponding to the interval where the position measurement vector magnitude is located, and this maximum value is used as the reconstructed position observation noise that the first positioning result ultimately participates in the integrated navigation positioning fusion. In this way, when the positioning point shifts drastically, the system's observation noise will increase significantly, thereby automatically reducing the gain weight of the observation at that location in the backend fusion algorithm, thus effectively suppressing abnormal positioning trajectories.

[0043] Regarding the selection of the preset distance constant, this application can adopt a stepped configuration scheme based on the severity of the jump. For example, when the magnitude of the position measurement vector is greater than 50 meters, the preset distance constant can be set to 15 meters; when the magnitude of the position measurement vector is in the range of 10 meters to 50 meters, the preset distance constant is set to 10 meters; and when the magnitude of the position measurement vector is less than or equal to 10 meters, the preset distance constant can be set to 1 meter. By introducing the above preset distance constant, the system can set a confidence threshold for different levels of abnormal observations, thereby effectively avoiding the risk of Kalman filter divergence caused by the underestimation of the original noise under certain extreme conditions. In addition, if the first positioning result is in an unreliable state, the system can further verify whether the velocity observation result meets the preset discard conditions. If it does, the system executes an interception command and stops the velocity observation result from participating in subsequent integrated navigation positioning fusion. Since velocity information can be used as a first derivative in integrated navigation for state updates, velocity observations containing large systematic errors or non-smoothness will quickly cause position state drift. Therefore, through the differentiated handling of position degradation and speed interception mentioned above, this application can ensure the high-precision output stability of the integrated navigation system under all operating conditions.

[0044] Figure 5 The diagram illustrates a flowchart of a method for determining the quality of positioning results based on constant velocity quality and trajectory smoothness level, provided in some embodiments of this application. The method includes: S501: Determine if the trajectory smoothness level is greater than or equal to the first level threshold, and the mean speed difference is greater than the first mean threshold or the standard deviation of the speed difference is greater than the first standard deviation threshold; or, the trajectory smoothness level is equal to the preset anomaly level; or, the mean speed difference is greater than the second mean threshold or the standard deviation of the speed difference is greater than the second standard deviation threshold.

[0045] S502: Detect the position observation of the first positioning result. If the detection is successful, proceed to step S503; otherwise, proceed to step S508.

[0046] S503: Is the magnitude of the position measurement vector greater than the first preset distance constant? If it is, proceed to step S504; otherwise, proceed to step 505.

[0047] S504: Select the maximum value among the position observation noise, position measurement vector magnitude, and first preset distance constant corresponding to the first positioning result, and use it as the satellite navigation system position observation noise that participates in the integrated navigation positioning fusion of the first positioning result.

[0048] S505: Determine whether the magnitude of the position measurement vector is greater than the second preset distance constant. If it is, proceed to step S506; otherwise, proceed to step S507.

[0049] S506: Select the maximum value among the position observation noise, position measurement vector magnitude, and second preset distance constant corresponding to the first positioning result, and use it as the satellite navigation system position observation noise that participates in the integrated navigation positioning fusion of the first positioning result.

[0050] S507: Select the maximum value among the position observation noise, position measurement vector magnitude, and third preset distance constant corresponding to the first positioning result, and use it as the satellite navigation system position observation noise that participates in the integrated navigation positioning fusion of the first positioning result.

[0051] S508: Detect the velocity observation of the first positioning result. If the detection passes, proceed to step S509; otherwise, skip to the end.

[0052] S509: Velocity observations not used from the first positioning result.

[0053] In the above embodiments, when executing step S502, the detection is essentially a pre-check of the validity flag of the location observation data. Although step S501 has determined that the overall positioning quality is abnormal, the system first needs to confirm whether there are any location observation results to be processed. If the location observation is detected to be valid, it means that the location data has the basis for subsequent fusion and retrieval. At this time, the system does not directly discard the data, but executes steps S503 to S507 to evaluate the physical magnitude of the location jump by calculating the magnitude of the location measurement vector, and then reconstructs the observation noise of the location observation, thereby realizing the degraded use of the location data. If the location observation itself is detected to be invalid, the system believes that there is no need to reconstruct its noise and directly jumps to step S508 to process the velocity dimension.

[0054] Step S508 establishes an interception mechanism for velocity data. Since step S501 clearly indicates that the GNSS data quality for the current epoch is substandard, step S508 performs a final flag check on the erroneous velocity data before it enters the integrated navigation solution core. When step S508 confirms that the flag of the current velocity observation is still valid, it means that this unreliable velocity data, without intervention, will directly participate in subsequent positioning fusion corrections. Therefore, the system immediately executes step S509, forcibly executing an operation that does not use the velocity observation from the first positioning result. In practice, this operation includes modifying the valid flag of the velocity observation from valid to invalid, or removing it from the input buffer.

[0055] Figure 6A schematic diagram of a positioning evaluation device for satellite navigation provided in some embodiments of this application is shown. The evaluation device 600 is used for combined navigation of a satellite navigation system and an inertial navigation system, and includes: an acquisition unit 610 for acquiring a first positioning result from the satellite navigation system; a trajectory sequence determination unit 620 for calculating and determining a trajectory sequence of the satellite navigation system based on the first positioning result; a trajectory sequence calculation unit 630 for calculating the dispersion of the trajectory and the maximum trajectory deviation based on the trajectory sequence; and a positioning result quality determination unit 640 for evaluating the positioning result quality of the satellite navigation system based on the dispersion of the trajectory and the maximum trajectory deviation.

[0056] Based on the same technical concept, this application also provides a computer-readable storage medium storing instructions thereon, which, when read by a processor, implement the evaluation method for navigation satellite positioning results as provided in the above embodiments.

[0057] In the above embodiments, the descriptions of each embodiment have their own emphasis. Parts not described in detail or in a particular embodiment can be referred to in the relevant descriptions of other embodiments. Furthermore, the above embodiments can be freely combined as needed.

Claims

1. A positioning evaluation method for satellite navigation, characterized in that, include: Obtain the first positioning result from the satellite navigation system; Based on the first positioning result, the trajectory sequence of the satellite navigation system is calculated and determined; Based on the trajectory sequence, the dispersion of the trajectory and the maximum trajectory deviation are calculated; The positioning quality of the satellite navigation system is evaluated based on the dispersion of the course direction and the maximum course direction deviation.

2. The positioning evaluation method for satellite navigation according to claim 1, characterized in that, The location evaluation method also includes: Obtain the second positioning result from the inertial navigation system; The step of calculating and determining the trajectory sequence of the satellite navigation system based on the first positioning result includes: When the first positioning result or the second positioning result meets the preset validity conditions, the calculation of the flight path is initiated; The trajectory sequence is determined based on the changes in the trajectory within the first preset time window.

3. The positioning evaluation method for satellite navigation according to claim 2, characterized in that, For a carrier, the preset validity conditions include: In the first epoch, the wheel speed of the carrier is valid and the wheel speed is greater than the first speed threshold, and the latitude and longitude in the first positioning result of the second epoch are both greater than zero, and the time difference between adjacent first epochs and second epochs meets the preset sampling interval. Alternatively, in the first epoch, the wheel speed is invalid, the first speed in the first positioning result or the second speed in the second positioning result is greater than the first speed threshold, and the latitude and longitude in the first positioning result of the second epoch are both greater than zero, and the time difference between adjacent first epochs and second epochs meets the preset sampling interval. The preset sampling interval is determined based on the data sampling interval of the satellite navigation system, and the second epoch is earlier than the first epoch.

4. The positioning evaluation method for satellite navigation according to any one of claims 1 to 3, characterized in that, The evaluation of the positioning result quality of the satellite navigation system based on the dispersion of the course direction and the maximum course direction deviation includes: Based on the fixed solution type of the first positioning result, the standard deviation of the trajectory and the maximum trajectory deviation are matched with multiple preset standard deviation thresholds of the trajectory and multiple maximum trajectory deviation thresholds to determine the corresponding trajectory smoothness level. Obtain the constant speed quality, and determine the positioning result quality based on the constant speed quality and the trajectory smoothness level.

5. The positioning evaluation method for satellite navigation according to claim 4, characterized in that, The acquisition of constant velocity mass includes: The effectiveness of the test carrier's wheel speed is verified. When the wheel speed of the carrier is detected to be valid, the speed difference sequence between the speed of the satellite navigation system and the wheel speed within the second preset time window is calculated; Based on the speed difference sequence, the mean speed difference and the standard deviation of the speed difference are determined as the constant speed mass.

6. The positioning evaluation method for satellite navigation according to claim 5, characterized in that, Also includes: Based on the trajectory smoothness level, the mean velocity difference, and the standard deviation of the velocity difference, determine whether the first positioning result meets the preset abnormal conditions; When the preset abnormal conditions are met, the first location result is determined to be in an unreliable state; The preset abnormal conditions include at least one of the following: The trajectory smoothness level is greater than or equal to the first level threshold, and the mean speed difference is greater than the first mean threshold or the standard deviation of the speed difference is greater than the first standard deviation threshold. Alternatively, the trajectory smoothness level is equal to a preset anomaly level; Alternatively, the mean of the speed difference is greater than the second mean threshold or the standard deviation of the speed difference is greater than the second standard deviation threshold.

7. The positioning evaluation method for satellite navigation according to any one of claims 1 to 3, characterized in that, Also includes: When it is determined that the first positioning result is in an unreliable state, the position measurement vector magnitude of the first positioning result is calculated; The maximum value is selected from the position observation noise corresponding to the first positioning result, the position measurement vector magnitude, and the preset distance corresponding to the interval where the position measurement vector magnitude is located, and is used as the satellite navigation system position observation noise in which the first positioning result participates in the integrated navigation positioning fusion. When it is determined that the first positioning result is in an unreliable state, and the velocity observation result in the first positioning result meets the preset discard conditions, the velocity observation result is stopped from participating in the integrated navigation positioning fusion.

8. The positioning evaluation method for satellite navigation according to claim 7, characterized in that, When the magnitude of the position measurement vector is greater than the first distance threshold, the preset distance is the first distance value; When the magnitude of the position measurement vector is greater than the second distance threshold and less than or equal to the first distance threshold, the preset distance is the second distance value; When the magnitude of the position measurement vector is less than or equal to the second distance threshold, the preset distance is the third distance value; Wherein, the first distance value is greater than the second distance value, and the second distance value is greater than the third distance value.

9. A positioning evaluation device for satellite navigation, characterized in that, Combined navigation for satellite navigation systems and inertial navigation systems, including: The acquisition unit is used to acquire the first positioning result of the satellite navigation system; A trajectory sequence determination unit is used to calculate and determine the trajectory sequence of the satellite navigation system based on the first positioning result; The trajectory sequence calculation unit calculates the dispersion of the trajectory and the maximum trajectory deviation based on the trajectory sequence. The positioning result quality determination unit evaluates the positioning result quality of the satellite navigation system based on the standard deviation of the trajectory and the maximum trajectory deviation.

10. A computer-readable storage medium, characterized in that, It stores instructions that, when read by a processor, implement the satellite navigation positioning evaluation method as described in any one of claims 1 to 8.

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