A method and device for positioning a UAV based on low-orbit observation effectiveness determination, a terminal device, and a storage medium

Abstract

The application discloses a kind of based on low orbit observation effectiveness determination unmanned plane positioning method, device, terminal equipment and storage medium, belong to unmanned plane positioning technical field, above-mentioned method is: obtaining current epoch's compass three PPP-B2b signal, GNSS satellite signal and low orbit satellite navigation enhancement signal, analysis obtains modified GNSS satellite orbit, clock difference parameter and the observation data of each low orbit satellite;According to observation data, the observation data quality index value of low orbit satellite is calculated, and compared with corresponding threshold value, determine effective low orbit observation data;Subsequently, filter positioning solution is carried out, and three kinds of positioning solutions are obtained;Finally, three positioning solutions are carried out joint consistency check and trusted level determination, determine final positioning result.Through implementation of the present application, can solve the problem that the quality defect of low orbit observation data in the low orbit observation link of prior art is considered insufficient, leading to the problem of inaccurate positioning result.

Description

Technical Field

[0001] This invention relates to the field of unmanned aerial vehicle (UAV) positioning technology, and in particular to a UAV positioning method, device, terminal equipment, and storage medium based on the effectiveness determination of low-orbit observation. Background Technology

[0002] Low Earth Orbit (LEO) satellite-enhanced navigation technology leverages the rapidly changing observation geometry generated by the high-speed motion of LEO satellites to significantly improve satellite spatial configuration, enhance observability, and provide stronger geometric support for rapid filter convergence and improved positioning performance. Integrating LEO satellite observations with BeiDou-3 PPP-B2b correction information allows for the simultaneous use of the high-precision orbital clock bias reference provided by BeiDou-3 PPP-B2b and the rapid geometric enhancement capabilities offered by LEO satellites, representing a crucial technical approach for improving the real-time, high-precision positioning performance of unmanned aerial vehicles (UAVs).

[0003] Existing PPP-B2b and low-Earth orbit satellite fusion positioning schemes mainly focus on improving positioning accuracy and convergence speed. They do not adequately consider problems that may occur in the low-Earth orbit observation link, such as excessively long observation time age, delayed orbit status update time, continuous loss of lock, decreased carrier-to-noise ratio, enhanced multipath interference, and abnormal observation residuals, which in turn lead to inaccurate positioning results. Summary of the Invention

[0004] This invention provides a UAV positioning method, device, terminal equipment, and storage medium based on the effectiveness determination of low-Earth orbit observations. It can solve the problem that existing technologies do not adequately consider issues that may occur in low-Earth orbit observation links, such as excessively long observation time age, delayed orbit state update time, continuous loss of lock, decreased carrier-to-noise ratio, enhanced multipath interference, and abnormal observation residuals, which lead to inaccurate positioning results.

[0005] An embodiment of the present invention provides a UAV positioning method based on the effectiveness determination of low-orbit observations, comprising: Acquire the BeiDou-3 PPP-B2b signal, GNSS satellite signal, and low-orbit satellite navigation enhancement signal for the current epoch; Based on the BeiDou-3 PPP-B2b signal, the GNSS broadcast ephemeris parameters in the GNSS satellite signal are corrected to obtain the corrected GNSS satellite orbit vector and GNSS satellite clock error parameters. The observation data of each low-Earth orbit satellite are extracted from the low-Earth orbit satellite navigation enhancement signal; Based on the observation data, the observation time age, orbital state update time age, consecutive loss of lock count, carrier-to-noise ratio, multipath error, and observation residual of each low-orbit satellite were calculated. The observation data corresponding to low-Earth orbit satellites whose observation time age is not greater than a preset observation time age threshold, whose orbit state update time age is not greater than a preset orbit state update time age threshold, whose consecutive loss of lock count is not greater than a preset consecutive loss of lock count threshold, whose carrier-to-noise ratio is not less than a preset carrier-to-noise ratio threshold, whose multipath error is not greater than a preset multipath error threshold, and whose absolute value of the observation residual is not greater than a preset observation residual threshold are taken as valid low-Earth orbit observation data. Based on GNSS satellite signals, corrected GNSS satellite orbit vectors, corrected GNSS satellite clock error parameters, observation data, and effective low-Earth orbit observation data, parallel filtering positioning solutions are performed to obtain pure GNSS positioning solutions, fully fused positioning solutions, and time-filtered fused positioning solutions. A joint consistency check is performed on the pure GNSS positioning solution, the fully fused positioning solution, and the time-filtered fused positioning solution to obtain the check result; and based on the check result and the effective low-orbit observation data, the final positioning result for the current epoch is determined.

[0006] Furthermore, based on the BeiDou-3 PPP-B2b signal, the GNSS broadcast ephemeris parameters in the GNSS satellite signal are corrected to obtain the corrected GNSS satellite orbit vector and GNSS satellite clock bias parameters, including: The BeiDou-3 PPP-B2b signal was decoded to obtain the equivalent orbit correction vector and clock correction number of each GNSS satellite; The GNSS satellite signals are demodulated to obtain the orbit vectors and clock bias parameters of each GNSS satellite in the GNSS broadcast ephemeris parameters; For each GNSS satellite, the difference between the orbit vector and the equivalent orbit correction vector is calculated to obtain the corrected GNSS satellite orbit vector; The difference between the clock bias parameter and the clock bias correction is calculated to obtain the corrected GNSS satellite clock bias parameter.

[0007] Furthermore, based on GNSS satellite signals, corrected GNSS satellite orbit vectors, corrected GNSS satellite clock bias parameters, observation data, and effective low-Earth orbit observation data, parallel filtering positioning solutions are performed to obtain pure GNSS positioning solutions, fully fused positioning solutions, and time-filtered fused positioning solutions, including: The GNSS satellite signals are demodulated to obtain raw GNSS observations; Based on the corrected GNSS satellite orbit vectors and the corrected GNSS satellite clock error parameters, a pure GNSS precise point positioning model is constructed. Based on the observation data, the corrected GNSS satellite orbit vector, and the corrected GNSS satellite clock error parameters, a fully fused precise point positioning model is constructed. Based on the corrected GNSS satellite orbit vector, the corrected GNSS satellite clock error parameters, and effective low-Earth orbit observation data, a time-sensitive fusion precise single-point positioning model is constructed. Using the raw GNSS observations as input to the pure GNSS precise point positioning model, the raw GNSS observations and observation data as input to the fully fused precise point positioning model, and the raw GNSS observations and effective low-orbit observation data as input to the time-filtered fused precise point positioning model, extended Kalman filtering is performed to obtain the pure GNSS positioning solution, the fully fused positioning solution, and the time-filtered fused positioning solution.

[0008] Furthermore, a joint consistency check is performed on the pure GNSS positioning solution, the fully fused positioning solution, and the time-filtered fused positioning solution to obtain the check results, including: The pure GNSS positioning solution, the fully fused positioning solution, and the time-filtered fused positioning solution are paired up to obtain several solution pairs; Calculate the Mahalanobis distance statistic, three-dimensional position difference, and velocity difference for each solution pair; From the Mahalanobis distance statistics of all solution pairs, the largest Mahalanobis distance statistic is extracted and used as the joint consistency statistic for the current epoch. The joint consistency statistic, the three-dimensional position difference, and the velocity difference are used as the check results.

[0009] Furthermore, based on the verification results and the valid low-Earth orbit observation data, the final positioning result for the current epoch is determined, including: The maximum three-dimensional position difference and the maximum velocity difference are extracted from the verification results. Based on the effective low-Earth orbit observation data, determine the number of effective low-Earth orbit observations for the current epoch; The credibility level is determined based on the joint consistency statistics, the maximum three-dimensional position difference, the maximum velocity difference, and the quantity, resulting in a credibility determination result. The final positioning result is then determined based on the credibility determination result, the pure GNSS positioning solution, and the time-filtered fusion positioning solution.

[0010] Furthermore, based on the joint consistency statistics, maximum three-dimensional position difference, maximum velocity difference, and quantity, a trust level is determined to obtain a trust determination result, including: Based on the first preset effective observation quantity threshold, the first preset consistency threshold, the first preset position difference threshold, the first preset velocity difference threshold, the second preset effective observation quantity threshold, the second preset consistency threshold, the second preset position difference threshold, the second preset velocity difference threshold, the third preset consistency threshold, and the effective determination result of the pure GNSS positioning solution, the first judgment condition, the second judgment condition, and the third judgment condition are constructed. If the first judgment condition is met, the trust determination result is a precise trust level; If the second judgment condition is met, the trust determination result is a normal trust level; If the third judgment condition is met, the trust determination result is a downgraded availability level; If none of the first judgment condition, the second judgment condition, and the third judgment condition are met, the reliability determination result is a failure alarm level. Wherein, the first preset effective observation number threshold is not less than the second preset effective observation number threshold, and the second preset effective observation number threshold is not less than 1; the first preset consistency threshold is less than the second preset consistency threshold, and the second preset consistency threshold is less than the third preset consistency threshold; the first preset position difference threshold is less than the second preset position difference threshold; the first preset speed difference threshold is less than the second preset speed difference threshold. The first judgment condition is: the quantity is not less than the first preset effective observation quantity threshold, the joint consistency statistic is not greater than the first preset consistency threshold, the maximum three-dimensional position difference is not greater than the first preset position difference threshold, and the maximum velocity difference is not greater than the first preset velocity difference threshold; The second judgment condition is: the quantity is not less than the second preset effective observation quantity threshold, the joint consistency statistic is not greater than the second preset consistency threshold, the maximum three-dimensional position difference is not greater than the second preset position difference threshold, and the maximum velocity difference is not greater than the second preset velocity difference threshold; The third judgment condition is: the joint consistency statistic is not greater than the third preset consistency threshold, and the pure GNSS positioning solution is valid; wherein, the valid judgment result of the pure GNSS positioning solution is determined based on the number of pure GNSS positioning solutions and the number of original GNSS observations.

[0011] Furthermore, based on the aforementioned reliable determination result, the pure GNSS positioning solution, and the time-sensitive fusion positioning solution, the final positioning result is determined, including: If the credibility determination result is a precise credibility level or a regular credibility level, the time-sensitive screening and fusion positioning solution will be used as the final positioning result. If the reliability determination result is a downgraded usability level, the pure GNSS positioning solution will be used as the final positioning result; If the reliability determination result is a failure alarm level, then the final location result is a location failure, and a location failure alarm is issued.

[0012] Based on the above method embodiments, the present invention provides corresponding apparatus embodiments; This invention provides a UAV positioning device based on low-orbit observation effectiveness determination, comprising: The system includes a signal acquisition module, a parameter correction module, an observation data extraction module, a comparison data calculation module, a data comparison module, a positioning calculation module, and a positioning determination module. The signal acquisition module is used to acquire the BeiDou-3 PPP-B2b signal, GNSS satellite signal and low-orbit satellite navigation enhancement signal in the current epoch; The parameter correction module is used to correct the GNSS broadcast ephemeris parameters in the GNSS satellite signal according to the BeiDou-3 PPP-B2b signal, so as to obtain the corrected GNSS satellite orbit vector and GNSS satellite clock error parameters. The observation data extraction module is used to extract the observation data of each low-orbit satellite from the low-orbit satellite navigation enhancement signal; The comparison data calculation module is used to calculate the observation time age, orbital state update time age, consecutive loss of lock count, carrier-to-noise ratio, multipath error and observation residual of each low-orbit satellite based on the observation data. The data comparison module is used to take the observation data corresponding to low-Earth orbit satellites whose observation time age is not greater than a preset observation time age threshold, whose orbit state update time age is not greater than a preset orbit state update time age threshold, whose consecutive loss count is not greater than a preset consecutive loss count threshold, whose carrier-to-noise ratio is not less than a preset carrier-to-noise ratio threshold, whose multipath error is not greater than a preset multipath error threshold, and whose absolute value of the observation residual is not greater than a preset observation residual threshold as valid low-Earth orbit observation data. The positioning calculation module is used to perform parallel filtering positioning calculations based on GNSS satellite signals, corrected GNSS satellite orbit vectors, corrected GNSS satellite clock error parameters, observation data, and effective low-orbit observation data to obtain pure GNSS positioning solutions, fully fused positioning solutions, and time-filtered fused positioning solutions. The positioning determination module is used to perform a joint consistency check on the pure GNSS positioning solution, the fully fused positioning solution, and the time-filtered fused positioning solution to obtain the check result; and to determine the final positioning result for the current epoch based on the check result and the effective low-orbit observation data.

[0013] Based on the above method embodiments, the present invention provides a corresponding terminal device embodiment; The present invention provides a terminal device, including a processor, a memory, and a computer program stored in the memory and configured to be executed by the processor. When the processor executes the computer program, it implements the UAV positioning method based on low-orbit observation effectiveness determination described in any embodiment of the present invention.

[0014] Based on the above method embodiments, the present invention provides a corresponding storage medium embodiment; The present invention provides a storage medium including a processor, a memory, and a computer program stored in the memory and configured to be executed by the processor. When the processor executes the computer program, it implements the UAV positioning method based on low-orbit observation effectiveness determination described in any embodiment of the present invention.

[0015] The embodiments of the present invention have the following beneficial effects: This invention provides a UAV positioning method, device, terminal equipment, and storage medium based on low-Earth orbit (LEO) observation validity determination. The method includes: acquiring the BeiDou-3 PPP-B2b signal, GNSS satellite signal, and LEO satellite navigation enhancement signal at the current epoch; correcting the GNSS broadcast ephemeris parameters in the GNSS satellite signal based on the BeiDou-3 PPP-B2b signal to obtain the corrected GNSS satellite orbit vector and GNSS satellite clock error parameters; extracting observation data of each LEO satellite from the LEO satellite navigation enhancement signal; calculating the observation time age, orbital state update time age, consecutive loss-of-lock count, carrier-to-noise ratio, multipath error, and observation residual of each LEO satellite based on the observation data; and ensuring that the observation time age is not greater than a preset observation time age threshold and the orbital state update time age is not greater than a preset orbital state update time age threshold. The observation data corresponding to low-Earth orbit (LEO) satellites that meet the following criteria are used as valid LEO observation data: the state update time age threshold, the consecutive loss-of-lock count not exceeding a preset consecutive loss-of-lock count threshold, the carrier-to-noise ratio not less than a preset carrier-to-noise ratio threshold, the multipath error not exceeding a preset multipath error threshold, and the absolute value of the observation residual not exceeding a preset observation residual threshold. Parallel filtering positioning solutions are then performed based on GNSS satellite signals, corrected GNSS satellite orbit vectors, corrected GNSS satellite clock bias parameters, observation data, and valid LEO observation data to obtain pure GNSS positioning solutions, fully fused positioning solutions, and time-filtered fused positioning solutions. A joint consistency check is performed on these solutions to obtain a check result. Finally, based on the check result and the valid LEO observation data, the final positioning result for the current epoch is determined. Therefore, in this invention, the observation time age, orbital state update time age, consecutive loss of lock count, carrier-to-noise ratio, multipath error, and observation residual of each low-orbit satellite are compared with the corresponding thresholds to extract effective low-orbit observation data. Then, positioning calculation is performed based on the effective low-orbit observation data. This overcomes the problem of inaccurate positioning results caused by insufficient consideration of existing technologies, such as excessively large observation time age, delayed orbital state update time, consecutive loss of lock, decreased carrier-to-noise ratio, enhanced multipath interference, and abnormal observation residuals. Attached Figure Description

[0016] To more clearly illustrate the technical solution of this application, the drawings used in the embodiments will be briefly introduced below. Obviously, the drawings described below are only some embodiments of this application. For those skilled in the art, other drawings can be obtained from these drawings without creative effort.

[0017] Figure 1 This is a flowchart illustrating a UAV positioning method based on low-orbit observation validity determination, provided by an embodiment of the present invention.

[0018] Figure 2 This is a schematic diagram of the structure of a UAV positioning device based on the effectiveness determination of low-orbit observation provided in an embodiment of the present invention. Detailed Implementation

[0019] To make the objectives, technical solutions, and advantages of this application clearer, the technical solutions of this application will be clearly and completely described below with reference to the accompanying drawings of the embodiments. Obviously, the described embodiments are only some embodiments of this application, not all embodiments. Based on the embodiments of this application, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of this application.

[0020] Unless otherwise defined, all technical and scientific terms used herein have the same meaning as commonly understood by one of ordinary skill in the art to which this application pertains; the terminology used herein is for the purpose of describing particular embodiments only and is not intended to limit the application; the terms “comprising” and “having”, and any variations thereof, in the specification, claims, and foregoing description of the drawings are intended to cover non-exclusive inclusion.

[0021] In the description of the embodiments of this application, technical terms such as "first" and "second" are used only to distinguish different objects and should not be construed as indicating or implying relative importance or implicitly specifying the number, specific order, or primary and secondary relationship of the indicated technical features. In the description of the embodiments of this application, "multiple" means two or more, unless otherwise explicitly defined.

[0022] In this document, the term "embodiment" means that a particular feature, structure, or characteristic described in connection with an embodiment may be included in at least one embodiment of this application. The appearance of this phrase in various places throughout the specification does not necessarily refer to the same embodiment, nor is it a separate or alternative embodiment mutually exclusive with other embodiments. It will be explicitly and implicitly understood by those skilled in the art that the embodiments described herein can be combined with other embodiments.

[0023] In the description of the embodiments in this application, the term "and / or" is merely a description of the relationship between related objects, indicating that three relationships can exist. For example, A and / or B can represent: A existing alone, A and B existing simultaneously, and B existing alone. Additionally, the character " / " in this document generally indicates that the preceding and following related objects have an "or" relationship.

[0024] In the description of the embodiments of this application, the term "multiple" refers to two or more (including two), similarly, "multiple sets" refers to two or more (including two sets), and "multiple pieces" refers to two or more (including two pieces).

[0025] In the description of the embodiments of this application, unless otherwise expressly specified and limited, technical terms such as "installation," "connection," "joining," and "fixing" should be interpreted broadly. For example, they can refer to a fixed connection, a detachable connection, or an integral part; they can refer to a mechanical connection or an electrical connection; they can refer to a direct connection or an indirect connection through an intermediate medium; they can refer to the internal communication of two components or the interaction between two components. For those skilled in the art, the specific meaning of the above terms in the embodiments of this application can be understood according to the specific circumstances.

[0026] See Figure 1 To address the problem of inaccurate positioning results caused by insufficient consideration of existing technologies in low-Earth orbit (LEO) observation links, which may lead to issues such as excessively long observation ages, delayed orbital state update times, continuous loss of lock, decreased carrier-to-noise ratio, enhanced multipath interference, and abnormal observation residuals, this invention provides a UAV positioning method based on LEO observation validity determination, comprising: Step S101: Obtain the BeiDou-3 PPP-B2b signal, GNSS satellite signal, and low-orbit satellite navigation enhancement signal for the current epoch; Specifically, low-Earth orbit (LEO) satellite navigation enhancement signals are dual-frequency or multi-frequency pseudorange signals and carrier phase signals broadcast by LEO navigation enhancement satellites.

[0027] All of the above information can be received by drones performing inspection, surveying, emergency response, or logistics operations in environments with no or weak network coverage.

[0028] Step S102: Correct the GNSS broadcast ephemeris parameters in the GNSS satellite signal according to the BeiDou-3 PPP-B2b signal to obtain the corrected GNSS satellite orbit vector and GNSS satellite clock error parameters; Specifically, based on the orbital corrections and clock corrections in the acquired BeiDou-3 PPP-B2b signal, the GNSS broadcast ephemeris in the GNSS satellite signal is corrected to obtain the GNSS satellite orbital vector and clock error parameters for precise point positioning calculation.

[0029] In a preferred embodiment, the GNSS broadcast ephemeris parameters in the GNSS satellite signal are corrected based on the BeiDou-3 PPP-B2b signal to obtain the corrected GNSS satellite orbit vector and GNSS satellite clock bias parameters, including: The BeiDou-3 PPP-B2b signal was decoded to obtain the equivalent orbit correction vector and clock correction number of each GNSS satellite; The GNSS satellite signals are demodulated to obtain the orbit vectors and clock bias parameters of each GNSS satellite in the GNSS broadcast ephemeris parameters; For each GNSS satellite, the difference between the orbit vector and the equivalent orbit correction vector is calculated to obtain the corrected GNSS satellite orbit vector; Specifically, the corrected GNSS satellite orbit vector is calculated using the following formula: In the formula, This represents the corrected orbit vector of the s-th GNSS satellite. This represents the orbit vector of the s-th GNSS satellite calculated from the broadcast ephemeris. Let represent the equivalent orbit correction vector of the s-th GNSS satellite, where s represents the GNSS satellite number.

[0030] The difference between the clock bias parameter and the clock bias correction is calculated to obtain the corrected GNSS satellite clock bias parameter.

[0031] Specifically, the corrected GNSS satellite clock bias parameters are calculated using the following formula: In the formula, This represents the corrected GNSS satellite clock bias parameter for the s-th GNSS satellite, in meters. This represents the clock bias parameter in the broadcast ephemeris of the s-th GNSS satellite, in meters. This represents the clock error correction for the s-th GNSS satellite, expressed in meters.

[0032] In this preferred embodiment, the GNSS broadcast ephemeris parameters in the GNSS satellite signal are corrected using the BeiDou-3 PPP-B2b signal, resulting in the corrected GNSS satellite orbit vector and GNSS satellite clock bias parameters.

[0033] Step S103: Extract the observation data of each low-orbit satellite from the low-orbit satellite navigation enhancement signal; Specifically, by demodulating and decoding the low-orbit satellite navigation enhancement signal, pseudorange observations, carrier phase observations, and corresponding time stamp information are obtained, which serve as the aforementioned observation data.

[0034] Step S104: Based on the observation data, calculate the observation time age, orbital state update time age, consecutive loss of lock count, carrier-to-noise ratio, multipath error, and observation residual for each low-orbit satellite; Specifically, the observation age is calculated by subtracting the timestamp information from the current epoch time from the timestamp information in the observation data. The smaller this time difference, the fresher the observation data and the better it reflects the current state. If the observation age is too large, it means the observation data is outdated; it may be old data captured by the receiver several epochs ago but not processed in time, or data lag due to signal processing delays. The formula for calculating the observation age is: In the formula, This represents the observation age of the l-th low-orbit satellite at epoch k. This represents the epoch time corresponding to epoch k. This represents the time stamp information in the observation data of the l-th low-orbit satellite at epoch k.

[0035] Specifically, in addition to broadcasting ranging signals, low-Earth orbit satellites also broadcast their own orbital parameters, which are mathematical information describing the satellite's trajectory in space. These orbital parameters are generated by the satellite's onboard computer and updated periodically, with each update including a reference timestamp indicating when the parameters were calculated.

[0036] Therefore, by demodulating the orbital parameters and their reference timestamp, the difference between the current epoch and this reference timestamp is the orbital state update age. Low-Earth orbit (LEO) satellites, due to their lower orbits and greater susceptibility to perturbations such as atmospheric drag, experience rapid decay of their orbital parameters over time. If the update age is too large, it indicates that the orbital parameters broadcast by the satellite itself have not been updated for a long time. Using such old parameters in positioning calculations will significantly reduce accuracy. The orbital state update age is calculated using the following formula: In the formula, This represents the orbital state update time age of the l-th low-Earth orbit satellite at epoch k. This represents the reference timestamp corresponding to the orbital parameters of the l-th low-orbit satellite at epoch k.

[0037] Specifically, the receiver maintains a counter for each tracked low-Earth orbit satellite. The integer ambiguity term in the carrier phase observation is the core of precise positioning, but it relies on the receiver continuously and uninterruptedly tracking the phase changes of the satellite signal. Once the signal is blocked or interfered with, the tracking loop will temporarily break down; this phenomenon is called "lost lock." The signal reacquired after the loss of lock may exhibit a jump in the integer ambiguity term of its carrier phase observation, known as a cycle slip.

[0038] Therefore, the receiver uses an internal cycle slip detection algorithm to monitor the continuity of the carrier phase of each satellite in real time. Common methods for detecting cycle slips include comparing whether the observations of different frequency combinations are consistent, and comparing whether the Doppler integral value matches the carrier phase change.

[0039] When a cycle slip or complete signal loss is detected at the current epoch, the continuous loss-of-lock counter for that satellite increments by one. When signals are tracked normally for several consecutive epochs without any cycle slips detected, the counter is reset to zero. The value of this counter is the continuous loss-of-lock count.

[0040] Specifically, the carrier-to-noise ratio (CNR) is an observation that is measured in real time and directly output by the tracking loop inside the receiver during signal processing. When the receiver is tracking the signal of a satellite, the tracking loop continuously measures the received signal power and the noise power at the bottom, then takes the ratio of the two and calculates the CNR.

[0041] Specifically, a higher carrier-to-noise ratio (CNR) indicates a clearer signal and higher measurement accuracy. A decreased CNR usually means that the satellite elevation angle is too low, the signal has passed through a thicker layer of atmosphere, or there is obstruction or interference around the drone.

[0042] Specifically, multipath error in low-Earth orbit (LEO) satellite observation data can be calculated using a dual-frequency code-phase multipath combination. The basic principle is as follows: for two frequency points of the same LEO satellite, both dual-frequency pseudorange and dual-frequency carrier phase observations contain terms such as geometric distance, receiver clock error, satellite clock error, tropospheric delay, and ionospheric delay. By constructing a dual-frequency code-phase linear combination, common terms such as geometric distance, receiver clock error, satellite clock error, and tropospheric delay can be eliminated, as well as the first-order ionospheric delay term. The remaining terms mainly include pseudorange multipath error, observation noise, and constant terms formed by carrier phase ambiguity and hardware delay bias. Since the multipath error in pseudorange observations is usually significantly greater than that in carrier phase observations, this combination, after being averaged or smoothed over continuous arcs, can be used as an estimate of the pseudorange multipath error.

[0043] In the formula, Represents the epoch Time The estimated value of the pseudorange multipath error of a low-orbit satellite at the first frequency point. Represents the epoch Time The pseudorange multipath error estimate of a low-orbit satellite at the second frequency point; Represents the epoch Time The pseudorange observation value of a low-orbit satellite at the first frequency point, in meters. Represents the epoch Time The pseudorange observation value of the low-orbit satellite at the second frequency point. Represents the epoch Time The distance measured from a low-orbit satellite at the first frequency point, converted from carrier phase observations, in meters. Represents the epoch Time The distance measured from a low-orbit satellite at the second frequency point, converted from carrier phase observations, is expressed in meters. This indicates the carrier frequency of the first frequency point. This indicates the carrier frequency of the second frequency point. and All are the first The constant term is estimated for a low-orbit satellite at a corresponding frequency point within a continuous tracking arc. The constant term is formed by carrier phase ambiguity and hardware delay bias.

[0044] Finally, in actual judgment, one can take... Alternatively, an estimated value of the pseudorange multipath error at one of the frequency points can be selected as the aforementioned multipath error for the corresponding low-Earth orbit satellite.

[0045] Specifically, for calculating the observation residuals, an ionospheric-free combined observation model consistent with the subsequent precise point positioning model is preferred. First, based on the receiver's current three-dimensional position, receiver clock bias, low-Earth orbit satellite orbit parameters, and low-Earth orbit satellite clock bias parameters, the geometric distance between the receiver and the low-Earth orbit satellite is calculated. Then, corrections for tropospheric delay, relativistic effects, and Earth rotation effects are added to obtain the ideal observation value for the ionospheric-free combined pseudorange. Finally, the ideal observation value for the ionospheric-free combined pseudorange is subtracted from the actual ionospheric-free combined pseudorange observation value obtained by the receiver to obtain the ionospheric-free combined pseudorange observation residual. The smaller this observation residual, the better the consistency between the current positioning status and the low-Earth orbit satellite observation data; a significantly increased observation residual indicates that the low-Earth orbit satellite observation data may be abnormal, or that the current positioning status has a large deviation. The above observation residuals are calculated using the following formula: In the formula, Represents the epoch Time Receiver With the The geometric distance between low-Earth orbit satellites, in meters. Represents the epoch Time Receiver The three-dimensional position vector, Represents the epoch Time The three-dimensional position vector of a low-Earth orbit satellite. Represents the epoch Time Ideal observation values ​​of ionospheric-free pseudoranges corresponding to 10 low-Earth orbit satellites, in meters. Represents the epoch Time Actual observed pseudorange values ​​for the ionosphere-free combination of several low-Earth orbit satellites, in meters. Represents the epoch Time Receiver The receiver clock bias parameter, in meters. Represents the kth epoch. Clock bias parameters for low-Earth orbit satellites, in meters. Represents the receiver at epoch k. With the The tropospheric delay correction term for links between low-Earth orbit satellites, in meters. This represents the relativistic effect correction term for the l-th low-orbit satellite at epoch k, in meters. This represents the Earth rotation effect correction term for the l-th low-orbit satellite at epoch k, in meters. Represents the epoch Time The ionospheric-free pseudorange observation residuals of a low-orbit satellite are the aforementioned observation residuals, expressed in meters.

[0046] In this preferred embodiment, the observation time age, orbital state update time age, consecutive loss-of-lock count, carrier-to-noise ratio, multipath error, and observation residuals of each low-orbit satellite are calculated based on the observation data.

[0047] Step S105: The observation data corresponding to the low-Earth orbit satellites whose observation time age is not greater than a preset observation time age threshold, whose orbit state update time age is not greater than a preset orbit state update time age threshold, whose consecutive loss count is not greater than a preset consecutive loss count threshold, whose carrier-to-noise ratio is not less than a preset carrier-to-noise ratio threshold, whose multipath error is not greater than a preset multipath error threshold, and whose absolute value of the observation residual is not greater than a preset observation residual threshold are taken as valid low-Earth orbit observation data. Specifically, the above determination process can be represented by the following formula: In the formula, This represents the valid determination indicator value for the l-th low-Earth orbit satellite at epoch k. A value of 1 indicates that the observation data corresponding to this low-Earth orbit satellite is valid low-Earth orbit observation data, while a value of 0 indicates that the observation data corresponding to this low-Earth orbit satellite is not valid low-Earth orbit observation data. This indicates the preset observation time age threshold. This indicates the preset orbital state update time age threshold. This represents the consecutive loss-of-lock count of the l-th low-orbit satellite at epoch k. This indicates the preset threshold for consecutive unlock counts. This represents the carrier-to-noise ratio of the l-th low-orbit satellite at epoch k. This indicates the preset carrier-to-noise ratio threshold. This represents the multipath error of the l-th low-orbit satellite at epoch k. This indicates the preset multipath error threshold. This represents the observation residual of the l-th low-orbit satellite at epoch k. This indicates the preset observation residual threshold. This represents the set of valid low-orbit observation data for epoch k.

[0048] Specifically, in determining each low-Earth orbit satellite After the value, By integrating the observation data from low-Earth orbit satellites with a value of 1, a set of effective low-Earth orbit observation data can be obtained.

[0049] Step S106: Based on the GNSS satellite signal, the corrected GNSS satellite orbit vector, the corrected GNSS satellite clock error parameters, the observation data, and the effective low-Earth orbit observation data, perform parallel filtering positioning calculations to obtain the pure GNSS positioning solution, the fully fused positioning solution, and the time-filtered fused positioning solution; Specifically, by first using GNSS satellite signals, corrected GNSS satellite orbit vectors, corrected GNSS satellite clock bias parameters, observation data, and effective low-Earth orbit observation data, three precise point positioning models are constructed: a pure GNSS precise point positioning model (i.e., GNSS-only precise point positioning model), a fully fused precise point positioning model (i.e., GNSS / LEO fully fused precise point positioning model), and a time-filtered fused precise point positioning model (i.e., GNSS / LEO time-filtered fused precise point positioning model). Then, filtering and solving are performed to obtain the pure GNSS positioning solution, the fully fused positioning solution, and the time-filtered fused positioning solution. Each positioning solution contains a three-dimensional position vector and a position covariance matrix.

[0050] In a preferred embodiment, parallel filtering positioning solutions are performed based on GNSS satellite signals, corrected GNSS satellite orbit vectors, corrected GNSS satellite clock bias parameters, observation data, and effective low-Earth orbit observation data to obtain pure GNSS positioning solutions, fully fused positioning solutions, and time-filtered fused positioning solutions, including: The GNSS satellite signals are demodulated to obtain raw GNSS observations; Based on the corrected GNSS satellite orbit vectors and the corrected GNSS satellite clock error parameters, a pure GNSS precise point positioning model is constructed. Based on the observation data, the corrected GNSS satellite orbit vector, and the corrected GNSS satellite clock error parameters, a fully fused precise point positioning model is constructed. Based on the corrected GNSS satellite orbit vector, the corrected GNSS satellite clock error parameters, and effective low-Earth orbit observation data, a time-sensitive fusion precise single-point positioning model is constructed. Using the raw GNSS observations as input to the pure GNSS precise point positioning model, the raw GNSS observations and observation data as input to the fully fused precise point positioning model, and the raw GNSS observations and effective low-orbit observation data as input to the time-filtered fused precise point positioning model, extended Kalman filtering is performed to obtain the pure GNSS positioning solution, the fully fused positioning solution, and the time-filtered fused positioning solution.

[0051] Specifically, the observation equations for GNSS satellites are first constructed as follows: In the formula, This represents the ionospherically incompatible pseudorange observation of receiver r for the s-th GNSS satellite. This represents the geometric distance between receiver r and the s-th GNSS satellite, in meters. This represents the receiver clock bias parameter, in meters. This represents the corrected clock bias parameters of the s-th GNSS satellite. This represents the tropospheric delay correction term for the link between receiver r and the s-th GNSS satellite. and Represents the observed noise term. This represents the carrier phase observation value of receiver r for the s-th GNSS satellite. The parameter represents the phase deviation of the receiver r relative to the s-th GNSS satellite without ionospheric combined carrier, expressed in meters.

[0052] For low-Earth orbit satellites, the observation equations are constructed as follows: In the formula, and Represents the observed noise term. This represents the ionospheric-free pseudorange observation of receiver r for the l-th low-Earth orbit satellite. Indicates receiver r and the first The geometric distance between low-Earth orbit satellites, in meters. This represents the clock bias parameter of the l-th low-Earth orbit satellite, in meters. This represents the tropospheric delay correction term for the link between receiver r and the l-th low-Earth orbit satellite. This represents the carrier phase observation value of receiver r for the l-th low-Earth orbit satellite. This represents the ionospheric combined carrier phase deviation parameter of receiver r for the l-th low-Earth orbit satellite.

[0053] Subsequently, for the pure GNSS precise point positioning model, only the observation equations of the GNSS satellites are used for construction, and the geometric distance between the receiver and the GNSS satellites is calculated. At that time, the satellite position parameters adopt the modified GNSS satellite orbit vector; the fully fused precise point positioning model is constructed using observation equations from both GNSS satellites and low-Earth orbit satellites, and the required observations are raw GNSS observations and observation data from all low-Earth orbit satellites; the time-sensitive fused precise point positioning model is constructed using observation equations from both GNSS satellites and low-Earth orbit satellites, and the required observations are raw GNSS observations and effective low-Earth orbit observation data.

[0054] Then, parallel extended Kalman filtering is used to calculate the positioning solution to obtain pure GNSS positioning solution, fully fused positioning solution and time-filtered fused positioning solution.

[0055] For any parallel solution branch Its state vector Defined as: In the formula, This indicates the branch number for parallel computation, and , This indicates that a pure GNSS positioning solution has been obtained. This represents a fully fused localization solution. This indicates the timeliness of the filtering, fusion, and positioning solution. , , Indicates branch In the calendar The three-dimensional position coordinate components are expressed in meters. Indicates the branch at epoch k. The corresponding clock bias parameter of receiver r, in meters. Indicates the branch at epoch k. The carrier phase deviation parameter corresponding to the observation channel, in meters. Indicates branch The number of carrier phase deviation parameters.

[0056] When performing parallel extended Kalman filter calculations, the prediction and update formulas are as follows: In the formula, Let represent the prior state vector at epoch k corresponding to branch i. This represents the posterior state vector at epoch k-1 corresponding to branch i. This represents the state transition matrix from epoch k-1 to epoch k corresponding to branch i. This represents the process noise covariance matrix at epoch k corresponding to branch i. Let represent the prior covariance matrix at epoch k corresponding to branch i. This represents the posterior covariance matrix at epoch k corresponding to branch i. This represents the posterior covariance matrix at epoch k-1 corresponding to branch i. This represents the Kalman gain matrix at epoch k corresponding to branch i. Let represent the Jacobian matrix of the observation equation with respect to the state vector at epoch k corresponding to branch i. This represents the observation noise covariance matrix at epoch k corresponding to branch i. Let represent the posterior state vector at epoch k corresponding to branch i. This represents the observation vector at epoch k corresponding to branch i. Let i be the nonlinear observation function corresponding to branch i. This represents the posterior covariance matrix at epoch k corresponding to branch i. It is an identity matrix.

[0057] It should be noted that in this invention, the tropospheric delay is determined using a priori models and is not estimated as an independent state parameter of the extended Kalman filter. After parallel filtering and positioning calculations, based on the obtained posterior covariance matrix and posterior state vector at epoch k, pure GNSS positioning solutions, fully fused positioning solutions, and time-filtered fused positioning solutions containing three-dimensional position vectors and position covariance matrices are obtained.

[0058] In this preferred embodiment, parallel filtering positioning solutions are performed based on GNSS satellite signals, corrected GNSS satellite orbit vectors, corrected GNSS satellite clock bias parameters, observation data, and effective low-Earth orbit observation data to obtain pure GNSS positioning solutions, fully fused positioning solutions, and time-filtered fused positioning solutions.

[0059] Step S107: Perform a joint consistency check on the pure GNSS positioning solution, the fully fused positioning solution, and the time-filtered fused positioning solution to obtain the check result; and determine the final positioning result for the current epoch based on the check result and the effective low-orbit observation data.

[0060] Specifically, firstly, based on the three positioning solutions, the Mahalanobis distance, position difference, and velocity difference are calculated to achieve joint consistency verification, and then the final positioning result is determined based on the verification results.

[0061] In a preferred embodiment, a joint consistency check is performed on the pure GNSS positioning solution, the fully fused positioning solution, and the time-filtered fused positioning solution to obtain the check result, including: The pure GNSS positioning solution, the fully fused positioning solution, and the time-filtered fused positioning solution are paired up to obtain several solution pairs; Calculate the Mahalanobis distance statistic, three-dimensional position difference, and velocity difference for each solution pair; Specifically, taking any pair of solutions as an example, its Mahalanobis distance statistic, three-dimensional position difference, and velocity difference are calculated based on the following formula: In the formula, Let represent the Mahalanobis distance statistic for the solution pair corresponding to location solutions a and b at epoch k. Let represent the three-dimensional position vector of the solution 'a' at epoch k. Determine the three-dimensional position vector of solution b at epoch k. This represents the position covariance matrix of the solution a at epoch k. This represents the position covariance matrix of the solution b at epoch k. This indicates that the location solutions a and b are in the epoch. The three-dimensional position difference Solution and solution In the calendar Mahalanobis distance statistics, Indicates the location solution In the calendar The equivalent velocity vector, Indicates the time interval between adjacent epochs. Indicates the location solution With location solution In the calendar Speed ​​difference, This indicates that the solution b is located in the epoch. The equivalent velocity vector. and .

[0062] From the Mahalanobis distance statistics of all solution pairs, the largest Mahalanobis distance statistic is extracted and used as the joint consistency statistic for the current epoch. Specifically, joint consistency statistics can characterize epochs. The overall statistical consistency among the three sets of location solutions is such that the joint consistency statistic can be determined based on the following formula: In the formula, Represents the epoch The corresponding joint consistency statistic, This represents the Mahalanobis distance statistic for the solution pair of the pure GNSS positioning solution and the fully fused positioning solution. This represents the Mahalanobis distance statistic of the solution pair formed by combining a pure GNSS positioning solution and a time-filtered fused positioning solution. This represents the Mahalanobis distance statistic of the solution pair combining the fully fused localization solution and the time-filtered fused localization solution.

[0063] The joint consistency statistic, the three-dimensional position difference, and the velocity difference are used as the check results.

[0064] In this preferred embodiment, the verification result was obtained by performing a joint consistency check on the pure GNSS positioning solution, the fully fused positioning solution, and the time-filtered fused positioning solution.

[0065] In another preferred embodiment, the final positioning result for the current epoch is determined based on the check result and the valid low-Earth orbit observation data, including: The maximum three-dimensional position difference and the maximum velocity difference are extracted from the verification results. Specifically, the maximum three-dimensional position difference and the maximum velocity difference can be obtained based on the following formulas: In the formula, This represents the maximum three-dimensional position difference in epoch k. This represents the three-dimensional position difference between the solution pair obtained from the combination of the pure GNSS positioning solution and the fully fused positioning solution at epoch k. This represents the three-dimensional position difference of the solution pair at epoch k, which is the combination of the pure GNSS positioning solution and the time-filtered fused positioning solution. This represents the three-dimensional position difference between the solution pairs obtained at epoch k, which are the combination of the fully fused localization solution and the time-filtered fused localization solution. This represents the maximum velocity difference at epoch k. This represents the velocity difference between the solution pair of the pure GNSS positioning solution and the fully fused positioning solution at epoch k. This represents the velocity difference between the pure GNSS positioning solution and the time-filtered fused positioning solution at epoch k. This represents the speed difference between the solution pairs of the fully fused localization solution and the time-filtered fused localization solution at epoch k.

[0066] Based on the effective low-Earth orbit observation data, determine the number of effective low-Earth orbit observations for the current epoch; Specifically, the above quantities can be determined using the following formula: In the formula, This represents the number of valid low-orbit observations for epoch k.

[0067] The credibility level is determined based on the joint consistency statistics, the maximum three-dimensional position difference, the maximum velocity difference, and the quantity, resulting in a credibility determination result. The final positioning result is then determined based on the credibility determination result, the pure GNSS positioning solution, and the time-filtered fusion positioning solution.

[0068] In this preferred embodiment, based on the verification results and valid low-Earth orbit observation data, joint consistency statistics, maximum three-dimensional position difference, maximum velocity difference, and quantity that can be used for reliable determination are determined, which facilitates further determination of the final positioning result.

[0069] In another preferred embodiment, a trust level is determined based on the joint consistency statistics, the maximum three-dimensional position difference, the maximum velocity difference, and the quantity, resulting in a trust determination result, including: Based on the first preset effective observation quantity threshold, the first preset consistency threshold, the first preset position difference threshold, the first preset velocity difference threshold, the second preset effective observation quantity threshold, the second preset consistency threshold, the second preset position difference threshold, the second preset velocity difference threshold, the third preset consistency threshold, and the effective determination result of the pure GNSS positioning solution, the first judgment condition, the second judgment condition, and the third judgment condition are constructed. If the first judgment condition is met, the trust determination result is a precise trust level; If the second judgment condition is met, the trust determination result is a normal trust level; If the third judgment condition is met, the trust determination result is a downgraded availability level; If none of the first judgment condition, the second judgment condition, and the third judgment condition are met, the reliability determination result is a failure alarm level. Wherein, the first preset effective observation number threshold is not less than the second preset effective observation number threshold, and the second preset effective observation number threshold is not less than 1; the first preset consistency threshold is less than the second preset consistency threshold, and the second preset consistency threshold is less than the third preset consistency threshold; the first preset position difference threshold is less than the second preset position difference threshold; the first preset speed difference threshold is less than the second preset speed difference threshold. The first judgment condition is: the quantity is not less than the first preset effective observation quantity threshold, the joint consistency statistic is not greater than the first preset consistency threshold, the maximum three-dimensional position difference is not greater than the first preset position difference threshold, and the maximum velocity difference is not greater than the first preset velocity difference threshold; The second judgment condition is: the quantity is not less than the second preset effective observation quantity threshold, the joint consistency statistic is not greater than the second preset consistency threshold, the maximum three-dimensional position difference is not greater than the second preset position difference threshold, and the maximum velocity difference is not greater than the second preset velocity difference threshold; The third judgment condition is: the joint consistency statistic is not greater than the third preset consistency threshold, and the pure GNSS positioning solution is valid; wherein, the valid judgment result of the pure GNSS positioning solution is determined based on the number of pure GNSS positioning solutions and the number of original GNSS observations.

[0070] Specifically, the above-mentioned judgment rule can be expressed based on the following formula: In the formula, This indicates the confidence level used to represent the confidence determination result for epoch k. This represents the first preset consistency threshold. This represents the first preset position difference threshold. This represents the first preset speed difference threshold. This represents the first preset threshold for the number of valid observations, and A represents the precision and reliability level. This represents the second preset consistency threshold. This represents the second preset position difference threshold. This indicates the second preset speed difference threshold. This represents the second preset threshold for the number of valid observations. This represents the third preset consistency threshold. Represents the epoch The pure GNSS positioning solution, where B represents the normal reliability level, C represents the downgraded usability level, and D represents the failure alarm level.

[0071] It should be noted that a valid pure GNSS positioning solution means that the pure GNSS precise point positioning model can complete the filtering calculation in the current epoch and output a finite three-dimensional position vector and the corresponding position covariance matrix; at the same time, the number of original GNSS observations participating in the pure GNSS precise point positioning solution meets the preset minimum observation number requirement, and the position covariance accuracy index corresponding to the pure GNSS positioning solution is not greater than the preset position covariance accuracy threshold.

[0072] Specifically, the validity of a pure GNSS positioning solution can be determined based on the following formula: In the formula, Represents the epoch Valid determination results of time-pure GNSS positioning solutions Represents the epoch Time-pure GNSS positioning solution is valid. Represents the epoch Time-based GNSS positioning solutions are invalid. Represents the epoch The set of raw GNSS observations used in the pure GNSS precise point positioning solution. Represents the epoch The number of raw GNSS observations used in the pure GNSS precise point positioning solution. Represents the epoch Pure GNSS positioning solution at that time Represents the epoch The position covariance matrix corresponding to the time-pure GNSS positioning solution. This represents the position covariance accuracy index of the pure GNSS positioning solution at epoch k. Represents the trace of a matrix. This indicates the preset minimum threshold for the number of GNSS observations. This represents the preset position covariance accuracy threshold.

[0073] Accordingly, the "valid pure GNSS positioning solution" in the third judgment condition above can be expressed as: .when In this case, the pure GNSS positioning solution is not used as a downgraded output result.

[0074] In this preferred embodiment, the credibility level is determined by combining the joint consistency statistics, the maximum three-dimensional position difference, the maximum velocity difference, and the quantity, and a credibility determination result is obtained.

[0075] In another preferred embodiment, the final positioning result is determined based on the credible determination result, the pure GNSS positioning solution, and the time-sensitive fusion positioning solution, including: If the credibility determination result is a precise credibility level or a regular credibility level, the time-sensitive screening and fusion positioning solution will be used as the final positioning result. If the reliability determination result is a downgraded usability level, the pure GNSS positioning solution will be used as the final positioning result; If the reliability determination result is a failure alarm level, then the final location result is a location failure, and a location failure alarm is issued.

[0076] Specifically, the rules for determining the final positioning result can be based on the following formula: In the formula, This represents the final positioning result of epoch k.

[0077] As can be seen from the above formula, when or When, output the timeliness filtering fusion positioning solution; when When, output pure GNSS positioning solution; when If this occurs, no reliable location result will be output and a failure alarm will be triggered.

[0078] Preferably, while retaining the high-precision advantages of BeiDou-3 PPP-B2b / LEO fusion positioning, the present invention further realizes the unified judgment of the effectiveness of low-orbit observation, the consistency between solutions, and the credibility level of the final output, which can effectively improve the reliability, security and availability of real-time positioning results in dynamic UAV scenarios.

[0079] In this preferred embodiment, the final positioning result is determined based on the credible determination result, the pure GNSS positioning solution, and the time-filtered fusion positioning solution.

[0080] Based on the above method embodiments, the present invention provides corresponding apparatus embodiments.

[0081] like Figure 2 As shown, one embodiment of the present invention provides a UAV positioning device based on low-orbit observation effectiveness determination, comprising: The system includes a signal acquisition module, a parameter correction module, an observation data extraction module, a comparison data calculation module, a data comparison module, a positioning calculation module, and a positioning determination module. The signal acquisition module is used to acquire the BeiDou-3 PPP-B2b signal, GNSS satellite signal and low-orbit satellite navigation enhancement signal in the current epoch; The parameter correction module is used to correct the GNSS broadcast ephemeris parameters in the GNSS satellite signal according to the BeiDou-3 PPP-B2b signal, so as to obtain the corrected GNSS satellite orbit vector and GNSS satellite clock error parameters. The observation data extraction module is used to extract the observation data of each low-orbit satellite from the low-orbit satellite navigation enhancement signal; The comparison data calculation module is used to calculate the observation time age, orbital state update time age, consecutive loss of lock count, carrier-to-noise ratio, multipath error and observation residual of each low-orbit satellite based on the observation data. The data comparison module is used to take the observation data corresponding to low-Earth orbit satellites whose observation time age is not greater than a preset observation time age threshold, whose orbit state update time age is not greater than a preset orbit state update time age threshold, whose consecutive loss count is not greater than a preset consecutive loss count threshold, whose carrier-to-noise ratio is not less than a preset carrier-to-noise ratio threshold, whose multipath error is not greater than a preset multipath error threshold, and whose absolute value of the observation residual is not greater than a preset observation residual threshold as valid low-Earth orbit observation data. The positioning calculation module is used to perform parallel filtering positioning calculations based on GNSS satellite signals, corrected GNSS satellite orbit vectors, corrected GNSS satellite clock error parameters, observation data, and effective low-orbit observation data to obtain pure GNSS positioning solutions, fully fused positioning solutions, and time-filtered fused positioning solutions. The positioning determination module is used to perform a joint consistency check on the pure GNSS positioning solution, the fully fused positioning solution, and the time-filtered fused positioning solution to obtain the check result; and to determine the final positioning result for the current epoch based on the check result and the effective low-orbit observation data.

[0082] It should be noted that the device embodiments described above are merely illustrative. The modules described as separate components may or may not be physically separate, and the components shown as modules may or may not be physical modules; that is, they may be located in one place or distributed across multiple network units. Some or all of the modules can be selected to achieve the purpose of this embodiment according to actual needs. Furthermore, in the accompanying drawings of the device embodiments provided by this invention, the connection relationship between modules indicates that they have a communication connection, which can be implemented as one or more communication buses or signal lines. Those skilled in the art can understand and implement this without creative effort. The above schematic diagram is merely an example of a UAV positioning device based on the effectiveness determination of low-orbit observation and does not constitute a limitation on a UAV positioning device based on the effectiveness determination of low-orbit observation. It may include more or fewer components than shown, or combine certain components, or use different components.

[0083] Based on the above method embodiments, the present invention provides corresponding terminal device embodiments.

[0084] Another embodiment of the present invention provides a terminal device, including a processor, a memory, and a computer program stored in the memory and configured to be executed by the processor. When the processor executes the computer program, it implements the UAV positioning method based on low-orbit observation effectiveness determination described in any embodiment of the present invention.

[0085] For example, in this embodiment, the computer program can be divided into one or more modules, which are stored in the memory and executed by the processor to complete the present invention. The one or more modules may be a series of computer program instruction segments capable of performing a specific function, which describe the execution process of the computer program in the device. The aforementioned terminal devices may be computing devices such as desktop computers, laptops, handheld computers, and cloud servers. These devices may include, but are not limited to, processors and memory. The processor can be a Central Processing Unit (CPU), or other general-purpose processors, digital signal processors (DSPs), application-specific integrated circuits (ASICs), field-programmable gate arrays (FPGAs), or other programmable logic devices, discrete gate or transistor logic devices, discrete hardware components, etc. A general-purpose processor can be a microprocessor or any conventional processor. This processor is the control center of the device, connecting various parts of the device via various interfaces and lines. The aforementioned memory can be used to store the aforementioned computer programs and / or modules. The aforementioned processor implements various functions of the aforementioned device by running or executing the computer programs and / or modules stored in the aforementioned memory, and by calling data stored in the memory. The aforementioned memory may mainly include a program storage area and a data storage area, wherein the program storage area may store the operating system, at least one application program required for a function, etc. In addition, the memory may include high-speed random access memory, and may also include non-volatile memory, such as hard disk, memory, plug-in hard disk, smart media card (SMC), secure digital (SD) card, flash card, at least one disk storage device, flash memory device, or other volatile solid-state storage device.

[0086] Based on the above method embodiments, the present invention provides corresponding storage medium embodiments.

[0087] Another embodiment of the present invention provides a storage medium including a stored computer program, wherein, when the computer program is running, it controls the device where the storage medium is located to execute the UAV positioning method based on low-orbit observation validity determination described in any embodiment of the present invention.

[0088] In this embodiment, the storage medium is a computer-readable storage medium, and the computer program includes computer program code, which may be in the form of source code, object code, executable file, or some intermediate form. The computer-readable medium may include any entity or device capable of carrying the computer program code, recording media, USB flash drive, portable hard drive, magnetic disk, optical disk, computer memory, read-only memory (ROM), random access memory (RAM), electrical carrier signals, telecommunication signals, and software distribution media, etc.

[0089] The above are preferred embodiments of the present invention. It should be noted that, for those skilled in the art, several improvements and modifications can be made without departing from the principle of the present invention, and these improvements and modifications are also considered to be within the scope of protection of the present invention.

Claims

1. A UAV positioning method based on low-orbit observation validity determination, characterized in that, include: Acquire the BeiDou-3 PPP-B2b signal, GNSS satellite signal, and low-orbit satellite navigation enhancement signal for the current epoch; Based on the BeiDou-3 PPP-B2b signal, the GNSS broadcast ephemeris parameters in the GNSS satellite signal are corrected to obtain the corrected GNSS satellite orbit vector and GNSS satellite clock error parameters. The observation data of each low-Earth orbit satellite are extracted from the low-Earth orbit satellite navigation enhancement signal; Based on the observation data, the observation time age, orbital state update time age, consecutive loss of lock count, carrier-to-noise ratio, multipath error, and observation residual of each low-orbit satellite were calculated. The observation data corresponding to low-Earth orbit satellites whose observation time age is not greater than a preset observation time age threshold, whose orbit state update time age is not greater than a preset orbit state update time age threshold, whose consecutive loss of lock count is not greater than a preset consecutive loss of lock count threshold, whose carrier-to-noise ratio is not less than a preset carrier-to-noise ratio threshold, whose multipath error is not greater than a preset multipath error threshold, and whose absolute value of the observation residual is not greater than a preset observation residual threshold are taken as valid low-Earth orbit observation data. Based on GNSS satellite signals, corrected GNSS satellite orbit vectors, corrected GNSS satellite clock error parameters, observation data, and effective low-Earth orbit observation data, parallel filtering positioning solutions are performed to obtain pure GNSS positioning solutions, fully fused positioning solutions, and time-filtered fused positioning solutions. The pure GNSS positioning solution, the fully fused positioning solution, and the time-filtered fused positioning solution are jointly checked for consistency to obtain the check results; Based on the verification results and the valid low-Earth orbit observation data, the final positioning result for the current epoch is determined.

2. The UAV positioning method based on low-orbit observation validity determination according to claim 1, characterized in that, Based on the BeiDou-3 PPP-B2b signal, the GNSS broadcast ephemeris parameters in the GNSS satellite signal are corrected to obtain the corrected GNSS satellite orbit vector and GNSS satellite clock bias parameters, including: The BeiDou-3 PPP-B2b signal was decoded to obtain the equivalent orbit correction vector and clock correction number of each GNSS satellite; The GNSS satellite signals are demodulated to obtain the orbit vectors and clock bias parameters of each GNSS satellite in the GNSS broadcast ephemeris parameters; For each GNSS satellite, the difference between the orbit vector and the equivalent orbit correction vector is calculated to obtain the corrected GNSS satellite orbit vector; The difference between the clock bias parameter and the clock bias correction is calculated to obtain the corrected GNSS satellite clock bias parameter.

3. The UAV positioning method based on low-orbit observation validity determination according to claim 2, characterized in that, Based on GNSS satellite signals, corrected GNSS satellite orbit vectors, corrected GNSS satellite clock bias parameters, observation data, and effective low-Earth orbit observation data, parallel filtering positioning solutions are performed to obtain pure GNSS positioning solutions, fully fused positioning solutions, and time-filtered fused positioning solutions, including: The GNSS satellite signals are demodulated to obtain raw GNSS observations; Based on the corrected GNSS satellite orbit vectors and the corrected GNSS satellite clock error parameters, a pure GNSS precise point positioning model is constructed. Based on the observation data, the corrected GNSS satellite orbit vector, and the corrected GNSS satellite clock error parameters, a fully fused precise point positioning model is constructed. Based on the corrected GNSS satellite orbit vector, the corrected GNSS satellite clock error parameters, and effective low-Earth orbit observation data, a time-sensitive fusion precise single-point positioning model is constructed. Using the raw GNSS observations as input to the pure GNSS precise point positioning model, the raw GNSS observations and observation data as input to the fully fused precise point positioning model, and the raw GNSS observations and effective low-orbit observation data as input to the time-filtered fused precise point positioning model, extended Kalman filtering is performed to obtain the pure GNSS positioning solution, the fully fused positioning solution, and the time-filtered fused positioning solution.

4. The UAV positioning method based on low-orbit observation validity determination according to claim 3, characterized in that, A joint consistency check is performed on the pure GNSS positioning solution, the fully fused positioning solution, and the time-filtered fused positioning solution to obtain the check results, including: The pure GNSS positioning solution, the fully fused positioning solution, and the time-filtered fused positioning solution are paired up to obtain several solution pairs; Calculate the Mahalanobis distance statistic, three-dimensional position difference, and velocity difference for each solution pair; From the Mahalanobis distance statistics of all solution pairs, the largest Mahalanobis distance statistic is extracted and used as the joint consistency statistic for the current epoch. The joint consistency statistic, the three-dimensional position difference, and the velocity difference are used as the check results.

5. The UAV positioning method based on low-orbit observation validity determination according to claim 4, characterized in that, Based on the verification results and the valid low-Earth orbit observation data, the final positioning result for the current epoch is determined, including: The maximum three-dimensional position difference and the maximum velocity difference are extracted from the verification results. Based on the effective low-Earth orbit observation data, determine the number of effective low-Earth orbit observations for the current epoch; The credibility level is determined based on the joint consistency statistics, the maximum three-dimensional position difference, the maximum velocity difference, and the quantity, resulting in a credibility determination result. The final positioning result is then determined based on the credibility determination result, the pure GNSS positioning solution, and the time-filtered fusion positioning solution.

6. The UAV positioning method based on low-orbit observation validity determination according to claim 5, characterized in that, The credibility level is determined based on the joint consistency statistics, maximum three-dimensional position difference, maximum velocity difference, and quantity, resulting in a credibility determination result, including: Based on the first preset effective observation quantity threshold, the first preset consistency threshold, the first preset position difference threshold, the first preset velocity difference threshold, the second preset effective observation quantity threshold, the second preset consistency threshold, the second preset position difference threshold, the second preset velocity difference threshold, the third preset consistency threshold, and the effective determination result of the pure GNSS positioning solution, the first judgment condition, the second judgment condition, and the third judgment condition are constructed. If the first judgment condition is met, the trust determination result is a precise trust level; If the second judgment condition is met, the trust determination result is a normal trust level; If the third judgment condition is met, the trust determination result is a downgraded availability level; If none of the first judgment condition, the second judgment condition, and the third judgment condition are met, the reliability determination result is a failure alarm level. Wherein, the first preset effective observation number threshold is not less than the second preset effective observation number threshold, and the second preset effective observation number threshold is not less than 1; the first preset consistency threshold is less than the second preset consistency threshold, and the second preset consistency threshold is less than the third preset consistency threshold; the first preset position difference threshold is less than the second preset position difference threshold; the first preset speed difference threshold is less than the second preset speed difference threshold. The first judgment condition is: the quantity is not less than the first preset effective observation quantity threshold, the joint consistency statistic is not greater than the first preset consistency threshold, the maximum three-dimensional position difference is not greater than the first preset position difference threshold, and the maximum velocity difference is not greater than the first preset velocity difference threshold; The second judgment condition is: the quantity is not less than the second preset effective observation quantity threshold, the joint consistency statistic is not greater than the second preset consistency threshold, the maximum three-dimensional position difference is not greater than the second preset position difference threshold, and the maximum velocity difference is not greater than the second preset velocity difference threshold; The third judgment condition is: the joint consistency statistic is not greater than the third preset consistency threshold, and the pure GNSS positioning solution is valid; wherein, the valid judgment result of the pure GNSS positioning solution is determined based on the pure GNSS positioning solution and the number of original GNSS observations.

7. The UAV positioning method based on low-orbit observation validity determination according to claim 6, characterized in that, Based on the aforementioned reliable determination result, the pure GNSS positioning solution, and the time-sensitive fusion positioning solution, the final positioning result is determined, including: If the credibility determination result is a precise credibility level or a regular credibility level, the time-sensitive screening and fusion positioning solution will be used as the final positioning result. If the reliability determination result is a downgraded usability level, the pure GNSS positioning solution will be used as the final positioning result; If the reliability determination result is a failure alarm level, then the final location result is a location failure, and a location failure alarm is issued.

8. A UAV positioning device based on low-orbit observation validity determination, characterized in that, include: The system includes a signal acquisition module, a parameter correction module, an observation data extraction module, a comparison data calculation module, a data comparison module, a positioning calculation module, and a positioning determination module. The signal acquisition module is used to acquire the BeiDou-3 PPP-B2b signal, GNSS satellite signal and low-orbit satellite navigation enhancement signal in the current epoch; The parameter correction module is used to correct the GNSS broadcast ephemeris parameters in the GNSS satellite signal according to the BeiDou-3 PPP-B2b signal, so as to obtain the corrected GNSS satellite orbit vector and GNSS satellite clock error parameters. The observation data extraction module is used to extract the observation data of each low-orbit satellite from the low-orbit satellite navigation enhancement signal; The comparison data calculation module is used to calculate the observation time age, orbital state update time age, consecutive loss of lock count, carrier-to-noise ratio, multipath error and observation residual of each low-orbit satellite based on the observation data. The data comparison module is used to take the observation data corresponding to low-Earth orbit satellites whose observation time age is not greater than a preset observation time age threshold, whose orbit state update time age is not greater than a preset orbit state update time age threshold, whose consecutive loss count is not greater than a preset consecutive loss count threshold, whose carrier-to-noise ratio is not less than a preset carrier-to-noise ratio threshold, whose multipath error is not greater than a preset multipath error threshold, and whose absolute value of the observation residual is not greater than a preset observation residual threshold as valid low-Earth orbit observation data. The positioning calculation module is used to perform parallel filtering positioning calculations based on GNSS satellite signals, corrected GNSS satellite orbit vectors, corrected GNSS satellite clock error parameters, observation data, and effective low-orbit observation data to obtain pure GNSS positioning solutions, fully fused positioning solutions, and time-filtered fused positioning solutions. The positioning determination module is used to perform a joint consistency check on the pure GNSS positioning solution, the fully fused positioning solution, and the time-filtered fused positioning solution to obtain the check result. Based on the verification results and the valid low-Earth orbit observation data, the final positioning result for the current epoch is determined.

9. A terminal device, characterized in that, The system includes a processor, a memory, and a computer program stored in the memory and configured to be executed by the processor, wherein the processor, when executing the computer program, implements a UAV positioning method based on low-orbit observation validity determination as described in any one of claims 1 to 7.

10. A storage medium, characterized in that, The storage medium includes a stored computer program, wherein, when the computer program is executed, it controls the device where the storage medium is located to execute a UAV positioning method based on low-orbit observation validity determination as described in any one of claims 1 to 7.

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