Unmanned aerial vehicle positioning method and device, terminal equipment and storage medium

Abstract

The invention discloses an unmanned aerial vehicle positioning method and device, terminal equipment and a storage medium, and the method comprises the steps: carrying out the position calculation according to an RTK correction number source list when determining that the RTK correction number source list is available, and obtaining an RTK positioning result; performing PPP positioning calculation according to the original observation data, the satellite-based enhancement correction information and the broadcast ephemeris to obtain a PPP positioning result; the precision of the RTK positioning result is compared with the precision of the PPP positioning result, the positioning result with the higher precision is selected as the final positioning result, a correction number is calculated according to the positioning result and coded, and coded information obtained after coding is broadcasted, so that the unmanned aerial vehicle in the area carries out positioning according to the coded information after receiving the coded information. According to the invention, when the unmanned aerial vehicle is far away from the base station or enters a communication blind area to cause RTK positioning failure or precision reduction, the PPP technology can provide positioning information, so that the positioning reliability of the unmanned aerial vehicle is effectively improved.

Description

Technical Field

[0001] The present invention relates to the field of unmanned aerial vehicles, and in particular to a method, device, terminal equipment and storage medium for positioning an unmanned aerial vehicle. Background Art

[0002] At present, high-precision positioning technologies represented by real-time kinematic (RTK) are widely used, but their technical implementation relies on the ground-based Global Navigation Satellite System (GNSS) base station and communication network. As a result, during the RTK positioning process, if the drone is far away from the base station, the drone is beyond the service range of the communication network, or the drone does not support RTK technology, the positioning accuracy will be greatly reduced or no positioning results can be obtained. Summary of the invention

[0003] The present invention provides a method, device, terminal equipment and storage medium for positioning a UAV. The method obtains an RTK positioning result and a PPP positioning result by solving the method, and compares the accuracy of the RTK positioning result with the accuracy of the PPP positioning result, and takes the positioning result with higher accuracy as the final positioning result, so that the positioning accuracy can be effectively improved during subsequent UAV positioning.

[0004] An embodiment of the present invention provides a method for positioning a drone, comprising:

[0005] Receive raw GNSS satellite signals and the RTK correction source list provided by the CORS server;

[0006] Decoding the original GNSS satellite signal to obtain original observation data, satellite-based augmentation correction information and broadcast ephemeris;

[0007] When it is determined that the distances between the positions of the sources in the RTK correction source list and the position of the UAV are all less than a preset threshold, performing RTK position calculation according to the RTK correction source list to obtain an RTK positioning result;

[0008] Perform PPP positioning solution according to the original observation data, the satellite-based augmentation correction number information and the broadcast ephemeris to obtain a PPP positioning result;

[0009] Compare the accuracy of the RTK positioning result with the accuracy of the PPP positioning result, and select the positioning result with higher accuracy as the final positioning result;

[0010] According to the positioning result, the corresponding satellite orbit, satellite clock error, satellite hardware delay and atmospheric delay error correction number are calculated and encoded to obtain corresponding coded information; the coded information is broadcast so that after receiving the coded information, the drones in the area can perform positioning according to the coded information.

[0011] Further, performing PPP positioning solution according to the original observation data, the satellite-based augmentation correction number information and the broadcast ephemeris to obtain a PPP positioning result includes:

[0012] Decoding the satellite-based augmentation correction information to obtain a plurality of correction information; wherein the correction information includes a satellite mask, a satellite orbit correction number, a user ranging accuracy index, an inter-code deviation correction number, and a clock error correction number; each correction information includes a data version information;

[0013] Match the data version information corresponding to each correction information to obtain a matching result;

[0014] According to the matching result, it is determined whether it is necessary to update the message corresponding to the satellite-based augmentation correction number information,

[0015] If yes, then according to the correction information, the message corresponding to the satellite-based augmentation correction number information is updated to obtain the target message,

[0016] If not, the message corresponding to the satellite-based augmentation correction number information is kept unchanged, and the message corresponding to the satellite-based augmentation correction number information is used as the target message;

[0017] Calculate the satellite high-precision orbit correction number and satellite clock error information according to the target message and the broadcast ephemeris;

[0018] Determining an optimization model for improving the PPP position solution speed based on a preset scene detection classifier and the original observation data;

[0019] The PPP position solution is performed according to the satellite high-precision orbit correction number, the satellite clock error information, the original observation data and the optimization model to obtain the PPP positioning result.

[0020] Furthermore, the optimization model for improving the PPP position solution speed is determined according to the preset scene detection classifier and the original observation data, including:

[0021] Obtaining an observation value error corresponding to the original observation data;

[0022] Determine a scene detection result indicating the environment in which the drone is located according to the scene detection classifier and the original observation data; wherein the scene detection result includes a selected environmental scene and an empirical noise value and a random model corresponding to the selected environmental scene;

[0023] Determining a noise level according to the observation value error and the empirical noise value;

[0024] Adjusting the parameters of the stochastic model according to the original observation data and the noise level;

[0025] The adjusted random model is used as the optimization model for improving the PPP position solution speed.

[0026] Furthermore, determining the scene detection result according to the preset scene detection classifier and the original observation data includes:

[0027] Preprocessing the original observation data to obtain preprocessed observation data;

[0028] Input the preprocessed observation data into the scene detection classifier, so that the scene detection classifier performs environmental analysis according to the preprocessed observation data to obtain a scene detection result set; wherein the scene detection classifier has several environmental scene types built in; the scene detection result set includes probability values ​​corresponding to each environmental scene type;

[0029] According to the probability value corresponding to the environmental scene, a rationality evaluation of the scene detection result is performed to obtain an evaluation result including the selected environmental scene;

[0030] The evaluation result is used as the scene detection result.

[0031] Further, after evaluating the rationality of the scene detection result according to the probability value corresponding to the environmental scene and obtaining the evaluation result including the selected environmental scene, the method further includes:

[0032] The scene detection result set and the evaluation result are input into the scene detection classifier, so that the scene detection classifier is updated according to the scene detection result set and the evaluation result to obtain an updated scene detection classifier.

[0033] An embodiment of the present invention further provides a UAV positioning device, comprising: a data receiving module, a signal decoding module, an RTK position solving module, a PPP positioning solving module, a positioning result confirmation module and a broadcasting module;

[0034] The data receiving module is used to receive the original GNSS satellite signal and the RTK correction source list provided by the CORS server;

[0035] The signal decoding module is used to decode the original GNSS satellite signal to obtain original observation data, satellite-based augmentation correction information and broadcast ephemeris;

[0036] The RTK position solving module is used to perform RTK position solving according to the RTK correction number source list to obtain the RTK positioning result when it is determined that the distance between the position of each source in the RTK correction number source list and the position of the UAV is less than a preset threshold;

[0037] The PPP positioning solution module is used to perform PPP positioning solution according to the original observation data, the satellite-based augmentation correction number information and the broadcast ephemeris to obtain a PPP positioning result;

[0038] The positioning result confirmation module is used to compare the accuracy of the RTK positioning result and the accuracy of the PPP positioning result, and select the positioning result with higher accuracy as the final positioning result;

[0039] The broadcasting module is used to calculate and encode the corresponding satellite orbit, satellite clock error, satellite hardware delay and atmospheric delay error correction number according to the positioning result to obtain corresponding coded information; broadcast the coded information so that the drones in the area can receive the coded information and perform positioning according to the coded information.

[0040] Further, performing PPP positioning solution according to the original observation data, the satellite-based augmentation correction number information and the broadcast ephemeris to obtain a PPP positioning result includes:

[0041] Decoding the satellite-based augmentation correction information to obtain a plurality of correction information; wherein the correction information includes a satellite mask, a satellite orbit correction number, a user ranging accuracy index, an inter-code deviation correction number, and a clock error correction number; each correction information includes a data version information;

[0042] Match the data version information corresponding to each correction information to obtain a matching result;

[0043] According to the matching result, it is determined whether it is necessary to update the message corresponding to the satellite-based augmentation correction number information,

[0044] If yes, then according to the correction information, the message corresponding to the satellite-based augmentation correction number information is updated to obtain the target message,

[0045] If not, the message corresponding to the satellite-based augmentation correction number information is kept unchanged, and the message corresponding to the satellite-based augmentation correction number information is used as the target message;

[0046] Calculate the satellite high-precision orbit correction number and satellite clock error information according to the target message and the broadcast ephemeris;

[0047] Determining an optimization model for improving the PPP position solution speed based on a preset scene detection classifier and the original observation data;

[0048] The PPP position solution is performed according to the satellite high-precision orbit correction number, the satellite clock error information, the original observation data and the optimization model to obtain the PPP positioning result.

[0049] Furthermore, the optimization model for improving the PPP position solution speed is determined according to the preset scene detection classifier and the original observation data, including:

[0050] Obtaining an observation value error corresponding to the original observation data;

[0051] Determine a scene detection result indicating the environment in which the drone is located according to the scene detection classifier and the original observation data; wherein the scene detection result includes a selected environmental scene and an empirical noise value and a random model corresponding to the selected environmental scene;

[0052] Determining a noise level according to the observation value error and the empirical noise value;

[0053] Adjusting the parameters of the stochastic model according to the original observation data and the noise level;

[0054] The adjusted random model is used as the optimization model for improving the PPP position solution speed.

[0055] The present application also provides a terminal device, including:

[0056] one or more processors;

[0057] A memory, coupled to the processor, for storing one or more programs;

[0058] When the one or more programs are executed by the one or more processors, the one or more processors implement the drone positioning method as described in the above-mentioned embodiment of the invention.

[0059] The present application also provides a storage medium on which a computer program is stored. When the computer program is executed by a processor, the drone positioning method as described in the above-mentioned embodiment of the invention is implemented.

[0060] The following beneficial effects are achieved by implementing the present invention:

[0061] The present invention provides a method, device, terminal equipment and storage medium for positioning a drone. When it is determined that the distance between the position of each source in the RTK correction number source list and the position of the drone is less than a preset threshold, the method performs RTK position solution according to the RTK correction number source list to obtain an RTK positioning result; and performs PPP positioning solution according to the original observation data, the satellite-based augmented correction number information and the broadcast ephemeris to obtain a PPP positioning result; the accuracy of the RTK positioning result and the accuracy of the PPP positioning result are compared, and the positioning result with higher accuracy is selected as the final positioning result; thus, by comparing the positioning accuracy of the RTK and PPP technologies in real time, the most accurate positioning result in the current environment can be dynamically selected; in addition, PPP positioning does not need to rely on a large number of reference stations, and the drone can enjoy free real-time PPP services without the help of network communication and commercial services. Therefore, when the RTK positioning of the drone fails or the accuracy decreases due to being far away from the base station or entering a communication blind spot, the PPP technology can continue to provide stable services. This dual positioning mechanism enables the system to maintain high positioning performance under different environmental conditions, thereby enhancing the reliability of drone positioning. BRIEF DESCRIPTION OF THE DRAWINGS

[0062] In order to more clearly illustrate the technical solution of the present application, the drawings required for use in the implementation manner will be briefly introduced below. Obviously, the drawings described below are only some implementation manners of the present application. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying any creative work.

[0063] Figure 1 It is a flowchart of a method for positioning a drone provided in a certain embodiment of the present application;

[0064] Figure 2 This is a flow chart of the PPPB2b satellite-based enhanced precise point positioning algorithm provided in a certain embodiment of the present application;

[0065] Figure 3 is a flowchart of a scene adaptive detection technology provided by a certain embodiment of the present application;

[0066] Figure 4 is a flow chart of positioning result determination provided by a certain embodiment of the present application;

[0067] Figure 5 is a structural schematic diagram of a drone positioning device provided in a certain embodiment of the present application;

[0068] Figure 6 It is a structural diagram of a terminal device provided in a certain embodiment of the present application. DETAILED DESCRIPTION

[0069] In order to make the purpose, technical solutions and advantages of this application clearer, the technical solutions in this application will be clearly and completely described below in conjunction with the drawings in the embodiments of this application. Obviously, the described embodiments are part of the embodiments of this application, not all of them. Based on the embodiments in this application, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of this application.

[0070] Unless otherwise defined, all technical and scientific terms used herein have the same meaning as commonly understood by technicians in the technical field to which this application belongs; the terms used herein are only for the purpose of describing specific embodiments and are not intended to limit this application; the terms "including" and "having" in the specification and claims of this application and the above-mentioned figure descriptions and any variations thereof are intended to cover non-exclusive inclusions.

[0071] In the description of the embodiments of the present application, the technical terms "first", "second", etc. are only used to distinguish different objects, and cannot be understood as indicating or implying relative importance or implicitly indicating the number, specific order or primary and secondary relationship of the indicated technical features. In the description of the embodiments of the present application, the meaning of "multiple" is more than two, unless otherwise clearly and specifically defined.

[0072] Reference to "embodiments" herein means that a particular feature, structure, or characteristic described in conjunction with the embodiments may be included in at least one embodiment of the present application. The appearance of the phrase in various locations in the specification does not necessarily refer to the same embodiment, nor is it an independent or alternative embodiment that is mutually exclusive with other embodiments. It is explicitly and implicitly understood by those skilled in the art that the embodiments described herein may be combined with other embodiments.

[0073] In the description of the embodiments of the present application, the term "and / or" is only a description of the association relationship of the associated objects, indicating that there may be three relationships. For example, A and / or B can represent: A exists alone, A and B exist at the same time, and B exists alone. In addition, the character " / " in this article generally indicates that the associated objects before and after are in an "or" relationship.

[0074] In the description of the embodiments of the present application, the term "multiple" refers to more than two (including two). Similarly, "multiple groups" refers to more than two groups (including two groups), and "multiple pieces" refers to more than two pieces (including two pieces).

[0075] In the description of the embodiments of the present application, unless otherwise clearly specified and limited, technical terms such as "installed", "connected", "connected", "fixed" and the like should be understood in a broad sense. For example, it can be a fixed connection, a detachable connection, or an integral connection; it can be a mechanical connection or an electrical connection; it can be a direct connection or an indirect connection through an intermediate medium, and it can be the internal connection of two elements or the interaction relationship between two elements. For those of ordinary skill in the art, the specific meanings of the above terms in the embodiments of the present application can be understood according to the specific circumstances.

[0076] The following are the professional terms and known technical contents involved in the embodiments of the present invention:

[0077] Precise Point Positioning (PPP), as an indispensable technology for information-based high-precision BDS-3 navigation and positioning, does not rely on a large number of reference stations, has the potential for stable decimeter-level positioning worldwide, and has a low cost, making it more suitable for the mass consumer navigation market. With the release of Beidou satellite-based augmentation BDS BAS-B1C and PPP-B2b signals and the disclosure of interfaces, mass users can enjoy free real-time PPP services in China and surrounding areas without the need for network communications and commercial services. Through the broadcast of satellite-based augmentation corrections in the B2b frequency signal by Beidou-3's geosynchronous orbit satellites, including satellite orbit corrections, satellite clock corrections, user ranging accuracy, and satellite hardware delay corrections, users can also obtain high-precision positioning services in areas without networks using satellite-based PPP algorithms.

[0078] See also Figure 1 , is a flow chart of a method for positioning a drone provided by an embodiment of the present invention, comprising:

[0079] S1, receiving the original GNSS satellite signals and the RTK correction source list provided by the CORS server;

[0080] S2. Decode the original GNSS satellite signal to obtain original observation data, satellite-based augmentation correction information and broadcast ephemeris;

[0081] Specifically, first, the original GNSS satellite signals are received and decoded to obtain the original observation data, broadcast ephemeris and satellite-based augmentation correction information, and the RTK correction source list provided by the CORS server is received through Wi-Fi or communication network.

[0082] S3. When it is determined that the distances between the positions of the sources in the RTK correction source list and the position of the UAV are all less than a preset threshold, perform RTK position calculation according to the RTK correction source list to obtain an RTK positioning result;

[0083] Specifically, the RTK correction source list is received through a communication network, and then based on the RTK correction source list, a GNSS single-difference / double-difference model is used to perform RTK position solution to obtain an RTK positioning result.

[0084] S4, performing PPP positioning solution according to the original observation data, the satellite-based augmentation correction information and the broadcast ephemeris to obtain a PPP positioning result;

[0085] In a preferred embodiment, performing PPP positioning solution according to the original observation data, the satellite-based augmentation correction number information and the broadcast ephemeris to obtain the PPP positioning result includes:

[0086] Decoding the satellite-based augmentation correction information to obtain a plurality of correction information; wherein the correction information includes a satellite mask, a satellite orbit correction number, a user ranging accuracy index, an inter-code deviation correction number, and a clock error correction number; each correction information includes a data version information;

[0087] Match the data version information corresponding to each correction information to obtain a matching result;

[0088] According to the matching result, it is determined whether it is necessary to update the message corresponding to the satellite-based augmentation correction number information,

[0089] If yes, then according to the correction information, the message corresponding to the satellite-based augmentation correction number information is updated to obtain the target message,

[0090] If not, the message corresponding to the satellite-based augmentation correction number information is kept unchanged, and the message corresponding to the satellite-based augmentation correction number information is used as the target message;

[0091] Calculate the satellite high-precision orbit correction number and satellite clock error information according to the target message and the broadcast ephemeris;

[0092] Determining an optimization model for improving the PPP position solution speed based on a preset scene detection classifier and the original observation data;

[0093] Perform PPP position solution according to the satellite high-precision orbit correction number, the satellite clock error information, the original observation data and the optimization model to obtain a PPP positioning result;

[0094] Specifically, see Figure 2 , using the satellite mask in the correction information as information type 1, using the satellite orbit correction number and the user ranging accuracy index in the correction information as information type 2, using the inter-code deviation correction number in the correction information as information type 3, and using the clock correction number in the correction information as information type 4;

[0095] First, match the IOD SSR information in information type 1 with the IOD SSR information in information types 2, 3, and 4. If they are inconsistent, information types 2, 3, and 4 will not be updated. If they are consistent, continue matching:

[0096] (1) determining whether the IODN of information type 2 matches the IOD BRDC in the broadcast ephemeris. If not, no subsequent processing is performed. If they match, the orbit correction number and user ranging accuracy index contained in the message corresponding to the satellite-based augmentation correction number information are updated.

[0097] (2) When it is known that the IOD SSR of information type 3 matches the IOD SSR of information type 1, the inter-code deviation correction number contained in the message corresponding to the satellite-based augmentation correction number information is directly updated;

[0098] (3) Determine whether the IODP in information type 4 matches the IODP in information type 1, and whether the IOD Corr in information type 4 matches the IOD Corr in information type 2. If both match, update the satellite clock error information contained in the message corresponding to the satellite-based augmentation correction number information; otherwise, do not perform subsequent processing.

[0099] Indicatively, according to the target message and the broadcast ephemeris, a satellite high-precision orbit correction number and satellite clock error information are calculated; and according to the correction information, the original observation data is corrected to obtain the corrected observation data;

[0100] Specifically, after the matching and updating are completed, the broadcast ephemeris, the satellite orbit correction number of information type 2 in the target message, and the satellite clock correction number of information type 4 in the target message can be used to jointly calculate the high-precision orbit and clock correction information of the current satellite; and the inter-code deviation correction number of information type 3 in the target message can be used to correct the inter-code deviation error in the original observation data.

[0101] Schematically, an optimization model for improving the PPP position solution speed is determined based on a preset scene detection classifier and the original observation data;

[0102] In a preferred embodiment, the determining of an optimization model for improving the PPP position solution speed based on a preset scene detection classifier and the original observation data includes:

[0103] Obtaining an observation value error corresponding to the original observation data;

[0104] Determine a scene detection result indicating the environment in which the drone is located according to the scene detection classifier and the original observation data; wherein the scene detection result includes a selected environmental scene and an empirical noise value and a random model corresponding to the selected environmental scene;

[0105] Determining a noise level according to the observation value error and the empirical noise value;

[0106] Adjusting the parameters of the stochastic model according to the original observation data and the noise level;

[0107] The adjusted random model is used as the optimization model for improving the PPP position solution speed;

[0108] Specifically, the residual corresponding to the original satellite observation data is obtained, and this residual is used as the observation value error, denoted as A;

[0109] After determining the scene detection result and obtaining the selected environmental scene, the noise level information is jointly determined in a weighted average manner according to the empirical noise value corresponding to the selected environmental scene and the observation value error; for example, the weight of the empirical noise value corresponding to the selected environmental scene is set to a, and the weight of the observation value error is set to b, where a+b=1;

[0110] According to the original observation data and the noise level, the parameters of the random model are adjusted. In this process, the observation value error is used as real-time information and the noise level is used together as the input value of the random model. The random model updates the output result of the current random model of the selected environment scene according to the input value;

[0111] Specifically, after obtaining the current random model, the noise level B corresponding to the current random model can be obtained at the same time. The parameter adjustment process is to obtain a new parameter through some calculation of A and B, recorded as C, such as C = A*B^2, etc.; then use the calculated C to replace the value of the parameter C in the original random model to achieve the update effect;

[0112] To better illustrate the connection between the selected environment scenario and the stochastic model, an example is given below:

[0113] When the environmental scene is an open scene, the altitude angle + signal-to-noise ratio joint weighting model can be used as the random model; when the environmental scene is an urban canyon scene, because the low-altitude angle satellite is blocked, the signal-to-noise ratio weighting model can be used as the random model; when the environmental scene is a unilateral data occlusion scene, because part of the area is blocked, the azimuth angle + altitude angle + signal-to-noise ratio weighting model is used as the random model.

[0114] In a preferred embodiment, determining the scene detection result according to the preset scene detection classifier and the original observation data includes:

[0115] Preprocessing the original observation data to obtain preprocessed observation data;

[0116] Input the preprocessed observation data into the scene detection classifier, so that the scene detection classifier performs environmental analysis according to the preprocessed observation data to obtain a scene detection result set; wherein the scene detection classifier has several environmental scene types built in; the scene detection result set includes probability values ​​corresponding to each environmental scene type;

[0117] According to the probability value corresponding to the environmental scene, the rationality of the scene detection result is evaluated to obtain an evaluation result including the selected environmental scene;

[0118] Using the evaluation result as a scene detection result;

[0119] Schematically, the original observation data is preprocessed to obtain preprocessed observation data;

[0120] Specifically, the original observation data is subjected to gross error elimination by setting a threshold;

[0121] Specifically, the scene detection classifier is a pre-trained model with multiple built-in environmental scene types (such as open environment, urban canyon environment, one-sided tree occlusion environment, two-sided tree occlusion environment, urban elevated environment, and tunnel environment, etc.); these scene types are obtained by training with a large amount of labeled data, and can identify features in the input data and classify them into matching environmental scene types;

[0122] Specifically, the original observation data includes but is not limited to: pseudorange residual, carrier residual, signal-to-noise ratio, altitude angle, azimuth angle, number of satellites and DOP value;

[0123] Specifically, the preprocessed observation data is input into the scene detection classifier, which analyzes the data according to the built-in environmental scene types and outputs a scene detection result set, which contains the probability values ​​corresponding to each environmental scene type, indicating the possibility that the input data belongs to each scene type;

[0124] Then, the rationality of the scene transition process is evaluated. For example, from an urban canyon to a double-sided tree occlusion and then to an open environment is a reasonable transition path, but directly from an urban canyon to an open environment (without an intermediate transition) may be relatively rare. An example is given below:

[0125] Assume that the results of a scene classification are as follows: 50% probability of urban canyon, 30% probability of double-sided tree occlusion, 10% probability of single-sided tree occlusion, 5% probability of open scene, 4% probability of viaduct scene, and 1% probability of tunnel scene. If this happens, the current scene is considered to be an urban canyon scene; however, if the previous scene was a single-sided tree occlusion environment, considering the rationality of scene switching, the current environment is considered to be a double-sided tree occlusion environment;

[0126] The probability values ​​in the scene detection result set are used to calculate the transition probabilities between different scenes; the calculated scene transition probabilities are compared with the predefined scene transition rules to evaluate the rationality of the detection results. If the scene transitions in the detection results do not conform to the predefined rules or the probability is extremely low, the results are considered to be unreasonable; finally, after completing the rationality evaluation of the scene detection results, an evaluation result containing the selected environmental scene is output; and the evaluation result containing the selected environmental scene is used as the scene detection result.

[0127] In a preferred embodiment, after evaluating the rationality of the scene detection result according to the probability value corresponding to the environmental scene and obtaining the evaluation result including the selected environmental scene, the method further includes:

[0128] The scene detection result set and the evaluation result are input into the scene detection classifier, so that the scene detection classifier is updated according to the scene detection result set and the evaluation result to obtain an updated scene detection classifier.

[0129] S5, comparing the accuracy of the RTK positioning result with the accuracy of the PPP positioning result, and selecting the positioning result with higher accuracy as the final positioning result;

[0130] Specifically, before the comparison, since the geodetic reference frame of RTK positioning is different from that of satellite-based PPP, the positioning result needs to be converted into a frame reference. After the frame alignment, the accuracy of the RTK positioning result and the accuracy of the PPP positioning result are compared, and the positioning result with higher accuracy is selected as the final positioning result.

[0131] S6. Calculate and encode the corresponding satellite orbit, satellite clock error, satellite hardware delay and atmospheric delay error correction number according to the positioning result to obtain corresponding coded information; broadcast the coded information so that the UAVs in the area can perform positioning according to the coded information after receiving the coded information;

[0132] Specifically, after determining the final positioning result, the current satellite orbit correction number, satellite clock correction number, satellite code deviation correction number and atmospheric delay error correction number and other information are obtained through calculation, and the above information is encoded. Through the Ntrip caster service and broadcasting equipment, the encoded information is broadcast to the surrounding drones, so that the drones can perform positioning according to the encoded information after receiving the encoded information.

[0133] See also Figure 5 , is a UAV positioning device provided by a certain embodiment of the present application, comprising: a data receiving module, a signal decoding module, an RTK position solving module, a PPP positioning solving module, a positioning result confirmation module and a broadcasting module;

[0134] The data receiving module is used to receive the original GNSS satellite signal and the RTK correction source list provided by the CORS server;

[0135] The signal decoding module is used to decode the original GNSS satellite signal to obtain original observation data, satellite-based augmentation correction information and broadcast ephemeris;

[0136] The RTK position solving module is used to perform RTK position solving according to the RTK correction number source list to obtain the RTK positioning result when it is determined that the distance between the position of each source in the RTK correction number source list and the position of the UAV is less than a preset threshold;

[0137] The PPP positioning solution module is used to perform PPP positioning solution according to the original observation data, the satellite-based augmentation correction number information and the broadcast ephemeris to obtain a PPP positioning result;

[0138] The positioning result confirmation module is used to compare the accuracy of the RTK positioning result and the accuracy of the PPP positioning result, and select the positioning result with higher accuracy as the final positioning result;

[0139] The broadcasting module is used to calculate and encode the corresponding satellite orbit, satellite clock error, satellite hardware delay and atmospheric delay error correction number according to the positioning result to obtain corresponding coded information; broadcast the coded information so that the drones in the area can receive the coded information and perform positioning according to the coded information.

[0140] In a preferred embodiment, performing PPP positioning solution according to the original observation data, the satellite-based augmentation correction number information and the broadcast ephemeris to obtain the PPP positioning result includes:

[0141] Decoding the satellite-based augmentation correction information to obtain a plurality of correction information; wherein the correction information includes a satellite mask, a satellite orbit correction number, a user ranging accuracy index, an inter-code deviation correction number, and a clock error correction number; each correction information includes a data version information;

[0142] Match the data version information corresponding to each correction information to obtain a matching result;

[0143] According to the matching result, it is determined whether it is necessary to update the message corresponding to the satellite-based augmentation correction number information,

[0144] If yes, then according to the correction information, the message corresponding to the satellite-based augmentation correction number information is updated to obtain the target message,

[0145] If not, the message corresponding to the satellite-based augmentation correction number information is kept unchanged, and the message corresponding to the satellite-based augmentation correction number information is used as the target message;

[0146] Calculate the satellite high-precision orbit correction number and satellite clock error information according to the target message and the broadcast ephemeris;

[0147] Determining an optimization model for improving the PPP position solution speed based on a preset scene detection classifier and the original observation data;

[0148] The PPP position solution is performed according to the satellite high-precision orbit correction number, the satellite clock error information, the original observation data and the optimization model to obtain the PPP positioning result.

[0149] In a preferred embodiment, the determining of an optimization model for improving the PPP position solution speed based on a preset scene detection classifier and the original observation data includes:

[0150] Obtaining an observation value error corresponding to the original observation data;

[0151] Determine a scene detection result indicating the environment in which the drone is located according to the scene detection classifier and the original observation data; wherein the scene detection result includes a selected environmental scene and an empirical noise value and a random model corresponding to the selected environmental scene;

[0152] Determining a noise level according to the observation value error and the empirical noise value;

[0153] Adjusting the parameters of the stochastic model according to the original observation data and the noise level;

[0154] The adjusted random model is used as the optimization model for improving the PPP position solution speed.

[0155] See also Figure 6 , a certain embodiment of the present application further provides a terminal device, including:

[0156] one or more processors;

[0157] A memory, coupled to the processor, for storing one or more programs;

[0158] When the one or more programs are executed by the one or more processors, the one or more processors implement the drone positioning method as described above.

[0159] The processor is used to control the overall operation of the terminal device to complete all or part of the steps of the above-mentioned drone positioning method. The memory is used to store various types of data to support the operation of the terminal device, and these data may include, for example, instructions for any application or method used to operate on the terminal device, as well as application-related data. The memory can be implemented by any type of volatile or non-volatile storage device or a combination thereof, such as static random access memory (Static Random Access Memory, referred to as SRAM), electrically erasable programmable read-only memory (Electrically Erasable Programmable Read-Only Memory, referred to as EEPROM), erasable programmable read-only memory (Erasable Programmable Read-Only Memory, referred to as EPROM), programmable read-only memory (Programmable Read-Only Memory, referred to as PROM), read-only memory (Read-Only Memory, referred to as ROM), magnetic memory, flash memory, disk or optical disk.

[0160] In an exemplary embodiment, the terminal device can be implemented by one or more application specific integrated circuits (ASIC), digital signal processors (DSP), digital signal processing devices (DSPD), programmable logic devices (PLD), field programmable gate arrays (FPGA), controllers, microcontrollers, microprocessors or other electronic components to execute the drone positioning method described in any of the above embodiments and achieve the same technical effect as the above method.

[0161] In another exemplary embodiment, a computer-readable storage medium including a computer program is also provided, and when the computer program is executed by a processor, the steps of the method for positioning a drone as described in any of the above embodiments are implemented. For example, the computer-readable storage medium may be the above-mentioned memory including the computer program, and the above-mentioned computer program may be executed by a processor of a terminal device to complete the method for positioning a drone as described in any of the above embodiments, and achieve the same technical effect as the above-mentioned method.

[0162] The above is a preferred embodiment of the present invention. It should be pointed out that a person skilled in the art can make several improvements and modifications without departing from the principle of the present invention. These improvements and modifications are also considered to be within the scope of protection of the present invention.

Claims

1. A method for positioning a drone, characterized in that: include: Receive raw GNSS satellite signals and the RTK correction source list provided by the CORS server; Decoding the original GNSS satellite signal to obtain original observation data, satellite-based augmentation correction information and broadcast ephemeris; When it is determined that the distances between the positions of the sources in the RTK correction source list and the position of the UAV are all less than a preset threshold, performing RTK position calculation according to the RTK correction source list to obtain an RTK positioning result; Perform PPP positioning solution according to the original observation data, the satellite-based augmentation correction number information and the broadcast ephemeris to obtain a PPP positioning result; Compare the accuracy of the RTK positioning result with the accuracy of the PPP positioning result, and select the positioning result with higher accuracy as the final positioning result; According to the positioning result, the corresponding satellite orbit, satellite clock error, satellite hardware delay and atmospheric delay error correction number are calculated and encoded to obtain corresponding coded information; The coded information is broadcasted so that after receiving the coded information, the drones in the area can perform positioning according to the coded information.

2. The method for positioning a drone as claimed in claim 1, wherein: The performing PPP positioning solution according to the original observation data, the satellite-based augmentation correction number information and the broadcast ephemeris to obtain the PPP positioning result includes: Decoding the satellite-based augmentation correction information to obtain a plurality of correction information; wherein the correction information includes a satellite mask, a satellite orbit correction number, a user ranging accuracy index, an inter-code deviation correction number, and a clock error correction number; each correction information includes a data version information; Match the data version information corresponding to each correction information to obtain a matching result; According to the matching result, it is determined whether it is necessary to update the message corresponding to the satellite-based augmentation correction number information, If yes, then according to the correction information, the message corresponding to the satellite-based augmentation correction number information is updated to obtain the target message, If not, the message corresponding to the satellite-based augmentation correction number information is kept unchanged, and the message corresponding to the satellite-based augmentation correction number information is used as the target message; Calculate the satellite high-precision orbit correction number and satellite clock error information according to the target message and the broadcast ephemeris; Determining an optimization model for improving the PPP position solution speed based on a preset scene detection classifier and the original observation data; The PPP position solution is performed according to the satellite high-precision orbit correction number, the satellite clock error information, the original observation data and the optimization model to obtain the PPP positioning result.

3. The method for positioning a drone as claimed in claim 2, wherein: The step of determining an optimization model for improving the PPP position solution speed based on a preset scene detection classifier and the original observation data includes: Obtaining an observation value error corresponding to the original observation data; Determine a scene detection result indicating the environment in which the drone is located according to the scene detection classifier and the original observation data; wherein the scene detection result includes a selected environmental scene and an empirical noise value and a random model corresponding to the selected environmental scene; Determining a noise level according to the observation value error and the empirical noise value; Adjusting the parameters of the stochastic model according to the original observation data and the noise level; The adjusted random model is used as the optimization model for improving the PPP position solution speed.

4. The method for positioning a UAV according to claim 3, wherein: The step of determining the scene detection result according to the preset scene detection classifier and the original observation data includes: Preprocessing the original observation data to obtain preprocessed observation data; Input the preprocessed observation data into the scene detection classifier, so that the scene detection classifier performs environmental analysis according to the preprocessed observation data to obtain a scene detection result set; wherein the scene detection classifier has several environmental scene types built in; the scene detection result set includes probability values ​​corresponding to each environmental scene type; According to the probability value corresponding to the environmental scene, a rationality evaluation of the scene detection result is performed to obtain an evaluation result including the selected environmental scene; The evaluation result is used as the scene detection result.

5. The method for positioning a UAV according to claim 4, wherein: After evaluating the rationality of the scene detection result according to the probability value corresponding to the environmental scene and obtaining the evaluation result including the selected environmental scene, the method further includes: The scene detection result set and the evaluation result are input into the scene detection classifier, so that the scene detection classifier is updated according to the scene detection result set and the evaluation result to obtain an updated scene detection classifier.

6. A drone positioning device, characterized in that: include: Data receiving module, signal decoding module, RTK position solution module, PPP positioning solution module, positioning result confirmation module and broadcast module; The data receiving module is used to receive the original GNSS satellite signal and the RTK correction source list provided by the CORS server; The signal decoding module is used to decode the original GNSS satellite signal to obtain original observation data, satellite-based augmentation correction information and broadcast ephemeris; The RTK position solving module is used to perform RTK position solving according to the RTK correction number source list to obtain the RTK positioning result when it is determined that the distance between the position of each source in the RTK correction number source list and the position of the UAV is less than a preset threshold; The PPP positioning solution module is used to perform PPP positioning solution according to the original observation data, the satellite-based augmentation correction number information and the broadcast ephemeris to obtain a PPP positioning result; The positioning result confirmation module is used to compare the accuracy of the RTK positioning result and the accuracy of the PPP positioning result, and select the positioning result with higher accuracy as the final positioning result; The broadcast module is used to calculate and encode the corresponding satellite orbit, satellite clock error, satellite hardware delay and atmospheric delay error correction number according to the positioning result to obtain corresponding coded information; The coded information is broadcasted so that after receiving the coded information, the drones in the area can perform positioning according to the coded information.

7. The unmanned aerial vehicle positioning device according to claim 6, characterized in that: The performing PPP positioning solution according to the original observation data, the satellite-based augmentation correction number information and the broadcast ephemeris to obtain the PPP positioning result includes: Decoding the satellite-based augmentation correction information to obtain a plurality of correction information; wherein the correction information includes a satellite mask, a satellite orbit correction number, a user ranging accuracy index, an inter-code deviation correction number, and a clock error correction number; each correction information includes a data version information; Match the data version information corresponding to each correction information to obtain a matching result; According to the matching result, it is determined whether it is necessary to update the message corresponding to the satellite-based augmentation correction number information, If yes, then according to the correction information, the message corresponding to the satellite-based augmentation correction number information is updated to obtain the target message, If not, the message corresponding to the satellite-based augmentation correction number information is kept unchanged, and the message corresponding to the satellite-based augmentation correction number information is used as the target message; Calculate the satellite high-precision orbit correction number and satellite clock error information according to the target message and the broadcast ephemeris; Determining an optimization model for improving the PPP position solution speed based on a preset scene detection classifier and the original observation data; The PPP position solution is performed according to the satellite high-precision orbit correction number, the satellite clock error information, the original observation data and the optimization model to obtain the PPP positioning result.

8. The unmanned aerial vehicle positioning device according to claim 7, characterized in that: The step of determining an optimization model for improving the PPP position solution speed based on a preset scene detection classifier and the original observation data includes: Obtaining an observation value error corresponding to the original observation data; Determine a scene detection result indicating the environment in which the drone is located according to the scene detection classifier and the original observation data; wherein the scene detection result includes a selected environmental scene and an empirical noise value and a random model corresponding to the selected environmental scene; Determining a noise level according to the observed value error and the empirical noise value; Adjusting the parameters of the stochastic model according to the original observation data and the noise level; The adjusted random model is used as the optimization model for improving the PPP position solution speed.

9. A terminal device, characterized in that: include: one or more processors; A memory, coupled to the processor, for storing one or more programs; When the one or more programs are executed by the one or more processors, the one or more processors implement the drone positioning method as described in any one of claims 1-5.

10. A storage medium having a computer program stored thereon, characterized in that: When the computer program is executed by a processor, the drone positioning method according to any one of claims 1 to 5 is implemented.

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