Joint positioning method, system and device based on unmanned aerial vehicle, and storage medium

Abstract

The invention relates to the technical field of satellite positioning, and particularly provides a combined positioning method, system and device based on an unmanned aerial vehicle, and a storage medium, and the method comprises the steps: obtaining the position coordinates of the unmanned aerial vehicle through receiving a satellite signal; obtaining distances between the plurality of unmanned aerial vehicles and a target point location through a laser ranging technology; and solving the position coordinates of the target point location based on the position coordinates of the plurality of unmanned aerial vehicles and the distances between the plurality of unmanned aerial vehicles and the target point location. According to the invention, the accuracy of fire point position determination is improved.

Description

Technical Field

[0001] The present invention belongs to the field of satellite positioning technology, and specifically relates to a joint positioning method, system, equipment and storage medium based on unmanned aerial vehicle. Background Art

[0002] When a forest fire occurs, accurately determining the fire location is a key prerequisite for rapid rescue operations. However, the complexity and variability of the forest environment, such as dense trees, changing terrain and unstable weather conditions, pose challenges to the positioning of drones and the location of fire points. Especially in fire danger situations, drones need to perform tasks quickly and effectively in dangerous environments, ensuring operational safety while confirming the fire location as quickly as possible.

[0003] Existing drones can be equipped with GNSS receivers to collect satellite signals and confirm the drone’s own location. However, in emergencies such as forest fire prevention, it is impossible to deploy GNSS receivers at the fire site in advance and accurately, and it is impossible to accurately obtain the coordinate information of the fire site. This brings many difficulties and challenges to forest fire prevention and control work. Summary of the invention

[0004] In view of the above-mentioned deficiencies in the prior art, the present invention provides a joint positioning method, system, device and storage medium based on drones to solve the above-mentioned technical problems.

[0005] In a first aspect, the present invention provides a joint positioning method based on a drone, comprising: Obtain the location coordinates of the drone by receiving satellite signals; Obtaining the distances between the plurality of drones and target points by laser ranging technology; The position coordinates of the target point are solved based on the position coordinates of the multiple drones and the distances between the multiple drones and the target point.

[0006] In an optional embodiment, the position coordinates of the drone are obtained by receiving satellite signals, including In pseudorange measurement, the time t when the signal reaches the receiver is directly measured. S The time t at which the signal leaves the satellite R The product of the time difference and the speed of light in vacuum is the pseudorange observation value: , where c is the speed of light; The corrected geometric distance between the drone and the satellite is: , Among them, the error between the satellite clock and the standard GPS time is , the error between the receiver clock and the standard GPS time is ; Considering the ionospheric delay and tropospheric delay, the pseudorange observation equation is obtained as follows: , in, is the geometric distance from the satellite to the receiver, I is the ionospheric delay parameter, and T is the tropospheric delay parameter; Assume that the position coordinates of the satellite are , the position of the receiver in space at the moment of observation is , then the geometric distance from the satellite to the drone is: ; Based on the geometric distance from the satellite to the UAV, the pseudorange observation equation is updated as: ; Obtaining the satellite signal receiving and sending time difference between the UAV and the multiple satellites, and the position coordinates of the multiple satellites, and substituting the satellite signal receiving and sending time difference between the UAV and the multiple satellites, and the position coordinates of the multiple satellites into the updated pseudo-range observation equation to obtain a set of simultaneous equations; The position coordinates of the UAV are obtained by solving the equation group.

[0007] In an optional embodiment, obtaining the position coordinates of the drone by solving the set of equations includes: Assume that the approximate coordinates of the drone's receiver are , start iteration with approximate coordinates as initial coordinates; No. i The coordinates of the satellite are , the pseudorange observation equation is expanded by Taylor series at the receiver coordinates to obtain: ; in, Representative i The distance from the satellite to the approximate coordinates of the drone’s receiver; make , , ,in , , The approximate coordinates to the satellite position The direction cosines of the vector, therefore, the linearized observation equation is written as: ; in, , , are the coordinate increments in the X, Y, and Z directions respectively. is the clock correction term. The linearized observation equation is transformed in one step to obtain: ; If the receiver of the UAV receives the satellite signals of k satellites at the same time at a certain moment, k observation equations can be written from the transformed observation equations, namely: ; After converting the equation into the form of least squares, the k observation equations are equivalent to the matrix form: ; Among them, V is the position increment vector, B is the coefficient matrix, and L is the observation value vector; According to the least squares principle, we can get: ; ; Where P is the weight matrix, is the initial value of the parameter to be estimated. The parameter estimate obtained each time will be used as the initial value In the next iteration, when When each element of satisfies the given threshold, the iteration is terminated and the final parameter estimate is obtained. ; The weight matrix P is determined according to the satellite's altitude angle. The higher the satellite's altitude angle, the greater its weight. The weight matrix P is defined as: ; in , , etc. are the cut-off altitude angles of the satellites; When k ≥ 4, that is, the drone's receiver receives more than 4 satellites at the same time, the receiver lists more than 4 rows of least squares equations, solves the corresponding parameter X, and then obtains the drone's coordinates.

[0008] In an optional embodiment, obtaining the distances between the plurality of drones and target points by laser ranging technology includes: Control the laser ranging sensor of the drone to send laser pulses to the target point and obtain the round-trip time of the laser pulses ; Then the distance between the UAV and the target point is: .

[0009] In an optional embodiment, the laser ranging sensor of the drone is controlled to send a laser pulse to the target point and obtain the round-trip time of the laser pulse. ,include: Obtain infrared scanning images from drones; Identify the point with the highest temperature in the infrared scanning image, and set the point with the highest temperature as the target point; Control the laser ranging sensor of the drone to send laser pulses to the target point and record the time when the laser pulses are sent; The time when the laser ranging sensor of the drone receives the laser pulse reflected by the target point is obtained, and the round-trip time of the laser pulse is calculated based on the receiving time and the sending time.

[0010] In an optional embodiment, solving the position coordinates of the target point based on the position coordinates of multiple drones and the distances between the multiple drones and the target point includes: Get the approximate coordinates of the target point (X 0 ,Y 0 ,Z 0 ), take the approximate coordinates as the initial coordinates of the target point; No. i The coordinates of the drone are , the pseudorange observation equation is expanded by Taylor series at the receiver coordinates to obtain: ; in, Representative i The distance from the drone to the approximate coordinates of the target point; Calculate the approximate coordinates of the target point to the drone position Direction cosines of the vector and linearize the observation equation based on the direction cosines; Based on the position coordinates of multiple UAVs and the linearized observation equations, an observation equation group is established; The observation equations are transformed into the form of least squares, and according to the least squares principle, an iterative equation system including a weight matrix is ​​constructed; Define an inverse proportional function weight determination method, and assume that the weight is expressed as: ; Among them, a and k are constants, and the values ​​of a and k are set according to the distance between the UAV and the target point, the measurement accuracy of the UAV, and the communication signal strength of the UAV; The sum of the weights is calculated as: ; Normalize the weights, and the normalized weights are: ; The matrix of drone weights is represented as: ; When the number of drones is greater than three, list more than three rows of least squares equations to solve the location coordinates of the target point.

[0011] In a second aspect, the present invention provides a joint positioning system based on a drone, comprising: The UAV positioning module is used to obtain the location coordinates of the UAV by receiving satellite signals; A distance detection module is used to obtain the distance between the plurality of drones and the target point by using laser ranging technology; The target positioning module is used to solve the position coordinates of the target point based on the position coordinates of multiple drones and the distances between the multiple drones and the target point.

[0012] In a third aspect, a device is provided, including: A memory for storing a UAV-based joint positioning program; A processor is used to implement the steps of the drone-based joint positioning method provided in the first aspect when executing the drone-based joint positioning program.

[0013] In a fourth aspect, a computer-readable storage medium is provided, on which a UAV-based joint positioning program is stored. When the UAV-based joint positioning program is executed by a processor, the steps of the UAV-based joint positioning method provided in the first aspect are implemented.

[0014] The beneficial effect of the present invention is that the joint positioning method, system, device and storage medium based on drones provided by the present invention utilize multiple drones to perform collaborative operations at different positions in the air, and these drones determine their approximate positions by receiving signals from global navigation satellite system satellites. Multiple drones can observe the fire area from different angles, and through mutual information exchange and data fusion, the accuracy of determining the location of the fire point is improved.

[0015] In addition, the invention has a reliable design principle, a simple structure and a very broad application prospect. BRIEF DESCRIPTION OF THE DRAWINGS

[0016] In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the drawings required for use in the embodiments or the description of the prior art will be briefly introduced below. Obviously, for ordinary technicians in this field, other drawings can be obtained based on these drawings without paying any creative work.

[0017] Figure 1 is a schematic flow chart of a method according to an embodiment of the present invention.

[0018] Figure 2 It is a schematic principle diagram of a method according to an embodiment of the present invention.

[0019] Figure 3 is another schematic flow chart of a method according to an embodiment of the present invention.

[0020] Figure 4 is a schematic block diagram of a system according to an embodiment of the present invention.

[0021] Figure 5 A schematic diagram of the structure of a device provided in an embodiment of the present invention. DETAILED DESCRIPTION

[0022] In order to enable those skilled in the art to better understand the technical solutions in the present invention, the technical solutions in the embodiments of the present invention will be clearly and completely described below in conjunction with the drawings in the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work should fall within the scope of protection of the present invention.

[0023] Unless otherwise defined, all technical and scientific terms used herein have the same meaning as those commonly understood by those skilled in the art of the present invention. The terms used in the specification of the present invention herein are only for the purpose of describing specific embodiments and are not intended to limit the present invention.

[0024] The drone-based joint positioning method provided in the embodiment of the present invention is executed by a computer device, and accordingly, the drone-based joint positioning system runs in the computer device.

[0025] Figure 1 is a schematic flow chart of a method according to an embodiment of the present invention. Figure 1 The execution subject may be a joint positioning system based on a drone. According to different requirements, the order of the steps in the flowchart may be changed, and some may be omitted.

[0026] like Figure 1 As shown, the method includes: S1. Obtain the location coordinates of the drone by receiving satellite signals.

[0027] The receiver on the drone captures and tracks signals from multiple navigation satellites. The received signals contain key information such as the satellite's orbital parameters and time stamps.

[0028] The received satellite signal data is combined with navigation algorithms (such as least squares method, Kalman filter, etc.) to calculate the precise position coordinates of the drone. Taking into account error sources such as atmospheric delay and satellite clock error, necessary error correction is performed.

[0029] The calculated drone position coordinates are output in real time for use in subsequent steps.

[0030] S2. Obtain the distance between the multiple drones and the target point through laser ranging technology.

[0031] The laser rangefinder on the drone emits laser pulses to the target point. The emission time and direction of the laser pulses are precisely controlled by the control system.

[0032] After the laser pulse reaches the target point, it is reflected back and captured by the receiving device on the drone. By measuring the round-trip time of the laser pulse and combining it with the speed of light, the distance between the drone and the target point is calculated.

[0033] The distance data between multiple drones and target points are recorded for use in subsequent steps.

[0034] S3. Calculate the position coordinates of the target point based on the position coordinates of the multiple drones and the distances between the multiple drones and the target point.

[0035] According to the principle of spatial geometry, a mathematical model containing the position coordinates of multiple drones and their distances from the target point is constructed. The model is usually a set of nonlinear equations, including the unknown coordinates of the target point as unknowns.

[0036] Numerical methods (such as iteration method, optimization algorithm, etc.) are used to solve the above nonlinear equations. In the solution process, the known UAV position coordinates and distance data can be used to approximate the real coordinates of the target point through continuous iteration.

[0037] Verify the obtained target point coordinates to ensure that they meet all known conditions (such as distance constraints, positional relationships, etc.). If necessary, make necessary corrections and adjustments based on the verification results to improve positioning accuracy.

[0038] The final solved target point coordinates are output for subsequent application or analysis.

[0039] Please refer to Figure 2 and Figure 3 , using multiple drones to work together in different locations in the air. These drones determine their approximate location by receiving signals from global navigation satellite system satellites. Multiple drones can observe the fire area from different angles, and through mutual information exchange and data fusion, the accuracy of determining the location of the fire point can be improved.

[0040] On the basis of multi-UAV joint positioning, laser calibration is introduced. UAVs may be equipped with laser rangefinders and other equipment, which can accurately measure the distance between the UAV and ground targets (including possible fire points) by emitting lasers to the ground and receiving reflected signals. The coordinates of unknown points are then calculated through distance intersection. Laser calibration can also be used to further correct and improve positioning accuracy, reducing positioning inaccuracies caused by satellite signal errors, UAV positioning errors, and other factors.

[0041] In an embodiment of the present invention, based on step S1, a possible embodiment is given below to illustrate its specific implementation scheme in a non-limiting manner.

[0042] Range resection methods include: Assume there are three known points A, B, and C, whose coordinates are , , . From three known points A, B, and C, measure their distances to point P respectively. The distances from point P to points A, B, and C are dA, dB, and dC respectively. The coordinates of point P are recorded as , then dA can be expressed as follows: ; Similarly, the distance from point P to point B and point C can also be calculated in this way, and can also be expressed as: ; When the coordinates of points A, B, and C are known, the unique solution for the position of point P can be calculated through iterative calculation. However, this calculation process is also full of errors. The position coordinates of points A, B, and C are not accurate, which results in the limited solution accuracy of point P, which is greatly affected by points A, B, and C.

[0043] When using a computer to solve, since the above equations are nonlinear, they can be solved by numerical methods such as iteration. In the solution process, first assume an initial coordinate of point P , and substitute it into the equations to get a set of approximate distance values. Then adjust the coordinates of point P according to the difference between the actual measured distance value and the approximate distance value, and repeat this process until a certain accuracy requirement is met.

[0044] The receiver on the ground can receive the electromagnetic waves sent by the satellite, and subtract the time when the satellite sends the electromagnetic wave from the time when the receiver receives the signal, so as to obtain the signal propagation time. Then, by multiplying the signal propagation time by the propagation speed, the distance from the receiver to the satellite can be obtained. The electromagnetic wave signal sent by the satellite is a pseudo-random noise code. The receiver records the time by simulating this noise code. Due to the errors of the satellite clock and the receiver clock, as well as the delay of the satellite signal in the ionosphere and troposphere, the distance obtained is not equal to the geometric distance from the satellite to the receiver. Therefore, the distance between the satellite and the receiver measured in this way is called pseudo-range.

[0045] A receiver on the ground can observe multiple satellites at the same time and receive a variety of satellite signals, which means that the receiver can obtain the distance to multiple satellites at the same time. The position of the satellite can be calculated using the satellite's orbital formula, which can be regarded as a known quantity here. Based on the distance resection mentioned above, the specific position of the receiver can be calculated using the pseudo-range between the receiver and the satellite.

[0046] Since there is a clock difference between the receiver and the satellite, which is counted as an additional variable, at least four satellites are needed to achieve basic positioning requirements.

[0047] In pseudorange measurement, the time difference between the time tS when the signal arrives at the receiver and the time tR when the signal leaves the satellite is directly measured. The product of the time difference and the speed of light in vacuum is the pseudorange observation value: , where c is the speed of light; When the satellite clock and the receiver clock are strictly synchronized, the above formula is the exact satellite signal propagation time. However, since the manufacturing and factory information of the satellite clock and the receiver clock cannot be strictly consistent, there will inevitably be errors, resulting in the inability to strictly synchronize the time between the two, and the value of this error time cannot be measured manually. The corrected geometric distance between the drone and the satellite is: , Among them, the error between the satellite clock and the standard GPS time is , the error between the receiver clock and the standard GPS time is ; Considering the ionospheric delay and tropospheric delay, the pseudorange observation equation is obtained as follows: , in, is the geometric distance from the satellite to the receiver, I is the ionospheric delay parameter, and T is the tropospheric delay parameter; Assume that the position coordinates of the satellite are , the position of the receiver in space at the moment of observation is , then the geometric distance from the satellite to the drone is: ; Based on the geometric distance from the satellite to the UAV, the pseudorange observation equation is updated as: ; Obtain the satellite signal reception and transmission time difference between the UAV and multiple satellites, as well as the position coordinates of the multiple satellites, substitute the satellite signal reception and transmission time difference between the UAV and multiple satellites, as well as the position coordinates of the multiple satellites into the updated pseudo-range observation equation to obtain a set of simultaneous equations; and obtain the position coordinates of the UAV by solving the set of equations.

[0048] The position coordinates of the UAV are obtained by solving the equations, including: Assume that the approximate coordinates of the drone's receiver are , start iteration with approximate coordinates as initial coordinates; No. i The coordinates of the satellite are , the pseudorange observation equation is expanded by Taylor series at the receiver coordinates to obtain: ; in, Representative i The distance from the satellite to the approximate coordinates of the drone’s receiver; make , , ,in , , The approximate coordinates to the satellite position The direction cosines of the vector, therefore, the linearized observation equation is written as: ; in, , , are the coordinate increments in the X, Y, and Z directions respectively. is the clock correction term. The linearized observation equation is transformed in one step to obtain: ; If the receiver of the UAV receives the satellite signals of k satellites at the same time at a certain moment, k observation equations can be written from the transformed observation equations, namely: ; After converting the equation into the form of least squares, the k observation equations are equivalent to the matrix form: ; Among them, V is the position increment vector, B is the coefficient matrix, and L is the observation value vector; According to the least squares principle, we can get: ; ; Where P is the weight matrix, is the initial value of the parameter to be estimated. The parameter estimate obtained each time will be used as the initial value In the next iteration, when When each element of satisfies the given threshold, the iteration is terminated and the final parameter estimate is obtained. ; The weight matrix P is determined according to the satellite's altitude angle. The higher the satellite's altitude angle, the greater its weight. The weight matrix P is defined as: ; in , , etc. are the cut-off altitude angles of the satellites; When k ≥ 4, that is, the drone's receiver receives more than 4 satellites at the same time, the receiver lists more than 4 rows of least squares equations, solves the corresponding parameter X, and then obtains the drone's coordinates.

[0049] In an embodiment of the present invention, based on step S2, a possible embodiment is given below to illustrate its specific implementation scheme in a non-limiting manner.

[0050] S201. Control the laser ranging sensor of the drone to send laser pulses to the target point and obtain the round-trip time of the laser pulses .

[0051] (1) Obtaining infrared scanning images from drones Start infrared scanning: The infrared scanning device on the drone starts to scan the surrounding environment. The infrared scanning device generates infrared images by capturing infrared radiation emitted by objects.

[0052] Image acquisition: The infrared scanning device transmits the collected infrared image data to the data processing system of the UAV. The data processing system pre-processes the received infrared image data, including denoising, contrast enhancement, etc.

[0053] (2) Identify the point with the highest temperature in the infrared scanning image and set the point with the highest temperature as the target point Temperature analysis: The data processing system performs temperature analysis on the pre-processed infrared image and estimates its temperature by calculating the infrared radiation intensity of each pixel. Each pixel in the infrared image corresponds to a temperature value, forming a temperature distribution map.

[0054] Target point identification: The data processing system finds the point with the highest temperature in the temperature distribution map, that is, the pixel with the highest infrared radiation intensity. The point is marked as the target point and its location information (such as coordinates) is recorded.

[0055] (3) Control the laser ranging sensor of the drone to send laser pulses to the target point and record the time when the laser pulses are sent Laser ranging preparation: The laser ranging sensor on the drone is activated and enters standby mode. The data processing system calculates the pointing angle that the laser ranging sensor needs to adjust based on the location information of the target point.

[0056] Sending laser pulses: The laser ranging sensor adjusts its emission direction according to the calculated pointing angle. The data processing system controls the laser ranging sensor to send laser pulses to the target point and records the sending time of the laser pulses.

[0057] (4) Obtain the time when the laser ranging sensor of the drone receives the laser pulse reflected by the target point, and calculate the round-trip time of the laser pulse based on the receiving time and the sending time Receiving laser pulses: After the laser pulse reaches the target point, part of the laser will be reflected back by the target point. The laser ranging sensor of the drone receives the reflected laser pulse and converts it into an electrical signal.

[0058] Time recording: The data processing system records the moment when the laser ranging sensor receives the reflected laser pulse. By comparing the sending time and the receiving time, the round-trip time of the laser pulse is calculated.

[0059] Among them, the laser ranging mode is the pulsed TOF (Time of Flight) method, which is a technology used for depth measurement. It continuously emits light pulses to the observed object, then receives the reflected light pulses, and calculates the distance between the object and the camera by detecting the flight (round-trip) time of the light pulses. The TOF method is divided into two types: pulse modulation and continuous wave modulation according to different modulation methods. In pulse modulation, the distance is calculated based on the time difference between the emission and reception of the light pulse; in continuous wave modulation, the depth information of the object is obtained by using the phase difference between the optical signal and the electrical signal.

[0060] S202. Distance calculation.

[0061] Then the distance between the UAV and the target point is: .

[0062] In an embodiment of the present invention, based on step S3, a possible embodiment is given below to illustrate its specific implementation scheme in a non-limiting manner.

[0063] UAV laser ranging is a method of using a UAV with a known position to emit laser rays to the target position, measure the distance from the UAV to the unknown point, and then calculate the position of the unknown point by resolving the distance between the UAVs.

[0064] The method of generating the observation distance simultaneous equations through distance resection is the same as step S1. The specific process is as follows: Assume that the approximate coordinates of the unknown point are: (X0, Y0, Z0), and use this as the initial coordinates to start the iteration.

[0065] No. i The coordinates of the UAV are assumed to be The pseudorange observation equation is expanded by Taylor series at the receiver coordinates to obtain: ; in, Representative i The distance from the drone to the approximate coordinates of the unknown point.

[0066] make , , , it can be seen , , The approximate position of the station to the drone position The direction cosines of the vector. Therefore, the linearized observation equation can be written as: ; in, , , are the coordinate increments in the X, Y, and Z directions respectively. is the clock correction term. By transforming the above formula one step, we can get: ; Assuming that there are k drones participating in laser ranging of the target point, k observation equations can be written from the above formula, namely: ; After converting the equation into the form of least squares, the above equation can be equivalent to matrix form: ; According to the least squares principle, we can get: ; ; in is the initial value of the parameter to be estimated. The parameter estimate obtained each time will be used as the initial value In the next iteration, when When each element of satisfies the given threshold, the iteration is terminated and the final parameter estimate is obtained. .

[0067] Next, we determine the weight according to the distance between the UAV and the point to be measured, and determine the matrix P. The distance between the UAV and the point to be measured is also an important factor in determining the positioning effect, so we define an inverse proportional function weight determination method, and set the weight expression as: ; Among them, a and k are constants, and their values ​​can be adjusted according to the actual situation to ensure that the weight is within a reasonable range. The closer the distance, the greater the weight should be. Then the weight is normalized. First, the corresponding weights of all drones and the points to be measured are calculated, and then the sum of all weights is calculated to get a total value. Finally, each weight is divided by the sum of weights to achieve normalization. The calculation method of the sum of weights is: ; Then normalize the weights, and the normalized weights are: ; In practical applications, the parameters in the weight function can be dynamically adjusted according to different scenarios and requirements. For example, if the measurement environment is complex, or if the data of drones that are closer are given more attention, the k value in the inverse proportional function can be increased to increase the weight of drones that are closer.

[0068] Although the weight is mainly determined by distance, other factors can also be considered to fine-tune the weight. For example, if the signal strength of a drone is good, its weight can be appropriately increased; or if the measurement accuracy of a drone is high, a certain weight bonus can be given.

[0069] Taking the above into consideration, the weight matrix belonging to the drone matrix is ​​as follows: ; When k ≥ 3, that is, the number of drones is greater than three, more than three rows of least squares equations can be listed, the corresponding parameter X can be solved, and then the position coordinates of the target point can be obtained.

[0070] Here is a Python code example using the scipy.optimize.least_squares function (based on the trust region method) to solve a nonlinear system of equations: import numpy as np from scipy.optimize import least_squares # Define drone position and target point observation distance (sample data) U = np.array([[1, 0, 0], [0, 1, 0], [0, 0,1]]) # Drone position d = np.array([np.sqrt(2), np.sqrt(2), np.sqrt(2)]) # Observation distance # Define a nonlinear system of equations (residual function) def residuals(X): x, y, z = X return np.sqrt((x - U[:, 0])**2 + (y - U[:, 1])**2 + (z - U[:, 2])**2) - d # Initial guess value X0= np.array([0.5, 0.5, 0.5]) # Solve using least_squares function result = least_squares(residuals, X0) # Output the solution print("Target point location coordinates:", result.x).

[0071] In some embodiments, the UAV-based joint positioning system may include multiple functional modules composed of computer program segments. The computer programs of each program segment in the UAV-based joint positioning system may be stored in a memory of a computer device and executed by at least one processor to perform (see Figure 1 Description) The function of joint positioning based on drones.

[0072] In this embodiment, the UAV-based joint positioning system can be divided into multiple functional modules according to the functions it performs, such as Figure 4 As shown. The functional modules of the system 400 may include: a drone positioning module 410, a distance detection module 420 and a target positioning module 430. The module referred to in the present invention refers to a series of computer program segments that can be executed by at least one processor and can complete fixed functions, which are stored in a memory. In this embodiment, the functions of each module will be described in detail in subsequent embodiments.

[0073] The UAV positioning module is used to obtain the location coordinates of the UAV by receiving satellite signals; A distance detection module is used to obtain the distance between the plurality of drones and the target point by using laser ranging technology; The target positioning module is used to solve the position coordinates of the target point based on the position coordinates of multiple drones and the distances between the multiple drones and the target point.

[0074] Optionally, as an embodiment of the present invention, the position coordinates of the drone are obtained by receiving satellite signals, including: In pseudorange measurement, the time t when the signal reaches the receiver is directly measured. S The time t at which the signal leaves the satellite R The product of the time difference and the speed of light in vacuum is the pseudorange observation value: , where c is the speed of light; The corrected geometric distance between the drone and the satellite is: , Among them, the error between the satellite clock and the standard GPS time is , the error between the receiver clock and the standard GPS time is ; Considering the ionospheric delay and tropospheric delay, the pseudorange observation equation is obtained as follows: , in, is the geometric distance from the satellite to the receiver, I is the ionospheric delay parameter, and T is the tropospheric delay parameter; Assume that the position coordinates of the satellite are , the position of the receiver in space at the moment of observation is , then the geometric distance from the satellite to the drone is: ; Based on the geometric distance from the satellite to the UAV, the pseudorange observation equation is updated as: ; Obtaining the satellite signal receiving and sending time difference between the UAV and the multiple satellites, and the position coordinates of the multiple satellites, and substituting the satellite signal receiving and sending time difference between the UAV and the multiple satellites, and the position coordinates of the multiple satellites into the updated pseudo-range observation equation to obtain a set of simultaneous equations; The position coordinates of the UAV are obtained by solving the equation group.

[0075] Optionally, as an embodiment of the present invention, obtaining the position coordinates of the drone by solving the set of equations includes: Assume that the approximate coordinates of the drone's receiver are , start iteration with approximate coordinates as initial coordinates; No. i The coordinates of the satellite are , the pseudorange observation equation is expanded by Taylor series at the receiver coordinates to obtain: ; in, Representative i The distance from the satellite to the approximate coordinates of the drone’s receiver; make , , ,in , , The approximate coordinates to the satellite position The direction cosines of the vector, therefore, the linearized observation equation is written as: ; in, , , are the coordinate increments in the X, Y, and Z directions respectively. is the clock correction term. The linearized observation equation is transformed in one step to obtain: ; If the receiver of the UAV receives the satellite signals of k satellites at the same time at a certain moment, k observation equations can be written from the transformed observation equations, namely: ; After converting the equation into the form of least squares, the k observation equations are equivalent to the matrix form: ; Among them, V is the position increment vector, B is the coefficient matrix, and L is the observation value vector; According to the least squares principle, we can get: ; ; Where P is the weight matrix, is the initial value of the parameter to be estimated. The parameter estimate obtained each time will be used as the initial value In the next iteration, when When each element of satisfies the given threshold, the iteration is terminated and the final parameter estimate is obtained. ; The weight matrix P is determined according to the satellite's altitude angle. The higher the satellite's altitude angle, the greater its weight. The weight matrix P is defined as: ; in , , etc. are the cut-off altitude angles of the satellites; When k ≥ 4, that is, the drone's receiver receives more than 4 satellites at the same time, the receiver lists more than 4 rows of least squares equations, solves the corresponding parameter X, and then obtains the drone's coordinates.

[0076] Optionally, as an embodiment of the present invention, obtaining the distances between the plurality of drones and target points by laser ranging technology includes: Control the laser ranging sensor of the drone to send laser pulses to the target point and obtain the round-trip time of the laser pulses ; Then the distance between the UAV and the target point is: .

[0077] Optionally, as an embodiment of the present invention, the laser ranging sensor of the drone is controlled to send a laser pulse to the target point, and the round-trip time of the laser pulse is obtained. ,include: Obtain infrared scanning images from drones; Identify the point with the highest temperature in the infrared scanning image, and set the point with the highest temperature as the target point; Control the laser ranging sensor of the drone to send laser pulses to the target point and record the time when the laser pulses are sent; The time when the laser ranging sensor of the drone receives the laser pulse reflected by the target point is obtained, and the round-trip time of the laser pulse is calculated based on the receiving time and the sending time.

[0078] Optionally, as an embodiment of the present invention, solving the position coordinates of the target point based on the position coordinates of multiple drones and the distances between the multiple drones and the target point includes: Get the approximate coordinates of the target point (X 0 ,Y 0 ,Z 0 ), take the approximate coordinates as the initial coordinates of the target point; No. i The coordinates of the drone are , the pseudorange observation equation is expanded by Taylor series at the receiver coordinates to obtain: ; in, Representative i The distance from the drone to the approximate coordinates of the target point; Calculate the approximate coordinates of the target point to the drone position Direction cosines of the vector and linearize the observation equation based on the direction cosines; Based on the position coordinates of multiple UAVs and the linearized observation equations, an observation equation group is established; The observation equations are transformed into the form of least squares, and according to the least squares principle, an iterative equation system including a weight matrix is ​​constructed; Define an inverse proportional function weight determination method, and assume that the weight is expressed as: ; Among them, a and k are constants, and the values ​​of a and k are set according to the distance between the UAV and the target point, the measurement accuracy of the UAV, and the communication signal strength of the UAV; The sum of the weights is calculated as: ; Normalize the weights, and the normalized weights are: ; The matrix of drone weights is represented as: ; When the number of drones is greater than three, list more than three rows of least squares equations to solve the location coordinates of the target point.

[0079] Figure 5 The drone-based joint positioning method provided for the embodiment of the present application can be applied to the device. Those skilled in the art will understand that the device structure involved in the embodiment of the present invention does not constitute a limitation on the device, and the device may include more or fewer components than shown, or combine certain components, or arrange different components. In an embodiment of the present invention, the device includes but is not limited to a laptop computer, a desktop computer, a workbench, a personal digital assistant, a server, a blade server, a mainframe computer, and other suitable computers. The device may also represent various forms of mobile devices, such as personal digital processing, cellular phones, smart phones, wearable devices, and other similar computing devices. The components shown herein, their connections and relationships, and their functions are merely examples and are not intended to limit the implementation of the embodiments of the present application described and / or required herein.

[0080] The device 500 may include: a processor 510, a memory 520 and a communication unit 530. These components communicate via one or more buses. Those skilled in the art will appreciate that the server structure shown in the figure does not limit the present invention, and it may be a bus structure or a star structure, and may include more or fewer components than shown in the figure, or combine certain components, or arrange components differently.

[0081] The memory 520 may be used to store the execution instructions of the processor 510, and the memory 520 may be implemented by any type of volatile or non-volatile storage device or a combination thereof, such as static random access memory (SRAM), electrically erasable programmable read-only memory (EEPROM), erasable programmable read-only memory (EPROM), programmable read-only memory (PROM), read-only memory (ROM), magnetic memory, flash memory, magnetic disk or optical disk. When the execution instructions in the memory 520 are executed by the processor 510, the device 500 is enabled to perform some or all of the steps in the following method embodiments.

[0082] The processor 510 is the control center of the storage device, and uses various interfaces and lines to connect various parts of the entire electronic device. It runs or executes software programs and / or modules stored in the memory 520, and calls data stored in the memory to perform various functions of the electronic device and / or process data. The processor can be composed of an integrated circuit (IC), for example, it can be composed of a single packaged IC, or it can be composed of a plurality of packaged ICs with the same or different functions. For example, the processor 510 can include only a central processing unit (CPU). In an embodiment of the present invention, the CPU can be a single computing core or multiple computing cores.

[0083] The communication unit 530 is used to establish a communication channel so that the storage device can communicate with other devices, receive user data sent by other devices or send user data to other devices.

[0084] The present invention also provides a computer storage medium, wherein the computer storage medium may store a program, and when the program is executed, the program may include some or all of the steps in each embodiment provided by the present invention. The storage medium may be a magnetic disk, an optical disk, a read-only memory (ROM) or a random access memory (RAM).

[0085] Those skilled in the art can clearly understand that the technology in the embodiments of the present invention can be implemented by means of software plus a necessary general hardware platform. Based on this understanding, the technical solution in the embodiments of the present invention, in essence, or the part that contributes to the prior art, can be embodied in the form of a software product, which is stored in a storage medium such as a USB flash drive, a mobile hard disk, a read-only memory (ROM), a random access memory (RAM), a disk or an optical disk, and other media that can store program codes, including several instructions for enabling a computer device (which can be a personal computer, a server, or a second device, a network device, etc.) to perform all or part of the steps of the method described in each embodiment of the present invention.

[0086] In this specification, the same or similar parts between the various embodiments can be referred to each other. In particular, for the device embodiment, since it is basically similar to the method embodiment, the description is relatively simple, and the relevant parts can be referred to the description in the method embodiment.

[0087] In the several embodiments provided by the present invention, it should be understood that the disclosed systems and methods can be implemented in other ways. For example, the system embodiments described above are only schematic. For example, the division of the modules is only a logical function division. There may be other division methods in actual implementation, such as multiple modules or components can be combined or integrated into another system, or some features can be ignored or not executed. Another point is that the mutual coupling or direct coupling or communication connection shown or discussed can be through some interfaces, indirect coupling or communication connection of systems or modules, which can be electrical, mechanical or other forms.

[0088] The modules described as separate components may or may not be physically separated, and the components shown as modules may or may not be physical modules, that is, they may be located in one place or distributed on multiple network modules. Some or all of the modules may be selected according to actual needs to achieve the purpose of the solution of this embodiment.

[0089] In addition, each functional module in each embodiment of the present invention may be integrated into one processing module, or each module may exist physically separately, or two or more modules may be integrated into one module.

[0090] Although the present invention has been described in detail with reference to the accompanying drawings and in combination with the preferred embodiments, the present invention is not limited thereto. Without departing from the spirit and essence of the present invention, a person of ordinary skill in the art may make various equivalent modifications or substitutions to the embodiments of the present invention, and these modifications or substitutions shall be within the scope of the present invention. Any person of ordinary skill in the art may easily think of changes or substitutions within the technical scope disclosed by the present invention, and these shall be within the scope of protection of the present invention.

Claims

1. A joint positioning method based on drones, characterized in that: include: Obtain the location coordinates of the drone by receiving satellite signals; Obtaining the distances between the plurality of drones and target points by laser ranging technology; The position coordinates of the target point are solved based on the position coordinates of the multiple drones and the distances between the multiple drones and the target point.

2. The method according to claim 1, characterized in that: Obtain the location coordinates of the drone by receiving satellite signals, including In pseudorange measurement, the time t when the signal reaches the receiver is directly measured. S The time t at which the signal leaves the satellite R The product of the time difference and the speed of light in vacuum is the pseudorange observation value, which is expressed as: , where c is the speed of light; Considering the clock error of the satellite and the receiver, the corrected pseudo-range expression between the UAV and the satellite is: ， Among them, the error between the satellite clock and the standard GPS time is , the error between the receiver clock and the standard GPS time is ; Considering the ionospheric delay and tropospheric delay, the pseudorange observation equation is obtained as follows: ， in, is the geometric distance from the satellite to the receiver, I is the ionospheric delay parameter, and T is the tropospheric delay parameter; Assume that the position coordinates of the satellite are , the position of the receiver in space at the moment of observation is , then the geometric distance from the satellite to the drone is: ； Based on the geometric distance from the satellite to the UAV, the pseudorange observation equation is updated as: ； Obtaining the satellite signal receiving and sending time difference between the UAV and the multiple satellites, and the position coordinates of the multiple satellites, and substituting the satellite signal receiving and sending time difference between the UAV and the multiple satellites, and the position coordinates of the multiple satellites into the updated pseudo-range observation equation to obtain a set of simultaneous equations; The position coordinates of the UAV are obtained by solving the equation group.

3. The method according to claim 1, characterized in that: The position coordinates of the UAV are obtained by solving the equations, including: Assume that the approximate coordinates of the drone's receiver are , start iteration with approximate coordinates as initial coordinates; No. i The coordinates of the satellite are , the pseudorange observation equation is expanded by Taylor series at the receiver coordinates to obtain: ； in, Representative i The distance from the satellite to the approximate coordinates of the drone’s receiver; make , , ,in , , The approximate coordinates to the satellite position The direction cosines of the vector, therefore, the linearized observation equation is written as: ； in, , , are the coordinate increments in the X, Y, and Z directions respectively. is the clock correction term. The linearized observation equation is transformed in one step to obtain: ； If the receiver of the UAV receives the satellite signals of k satellites at the same time at a certain moment, k observation equations can be written from the transformed observation equations, namely: ； After converting the equation into the form of least squares, the k observation equations are equivalent to the matrix form: ； Among them, V is the position increment vector, B is the coefficient matrix, and L is the observation value vector; According to the least squares principle, we can get: ； ； Where P is the weight matrix, is the initial value of the parameter to be estimated. The parameter estimate obtained each time will be used as the initial value In the next iteration, when When each element of satisfies the given threshold, the iteration is terminated and the final parameter estimate is obtained. ; The weight matrix P is determined according to the satellite's altitude angle. The higher the satellite's altitude angle, the greater its weight. The weight matrix P is defined as: ； in , , etc. are the cut-off altitude angles of the satellites; When k ≥ 4, that is, the drone's receiver receives more than 4 satellites at the same time, the receiver lists more than 4 rows of least squares equations, solves the corresponding parameter X, and then obtains the drone's coordinates.

4. The method according to claim 1, characterized in that The distances between the multiple drones and target points are obtained by laser ranging technology, including: Control the laser ranging sensor of the drone to send laser pulses to the target point and obtain the round-trip time of the laser pulses ; Then the distance between the UAV and the target point is: 。 5. The method according to claim 4, characterized in that Control the laser ranging sensor of the drone to send laser pulses to the target point and obtain the round-trip time of the laser pulses ,include: Obtain infrared scanning images from drones; Identify the point with the highest temperature in the infrared scanning image, and set the point with the highest temperature as the target point; Control the laser ranging sensor of the drone to send laser pulses to the target point and record the time when the laser pulses are sent; The time when the laser ranging sensor of the drone receives the laser pulse reflected by the target point is obtained, and the round-trip time of the laser pulse is calculated based on the receiving time and the sending time.

6. The method according to claim 1, characterized in that Solving the position coordinates of the target point based on the position coordinates of the plurality of drones and the distances between the plurality of drones and the target point includes: Get the approximate coordinates of the target point (X 0 ,Y 0 ,Z 0 ), and use the approximate coordinates as the initial coordinates of the target point; No. i The coordinates of the drone are , the pseudorange observation equation is expanded by Taylor series at the receiver coordinates to obtain: ； in, Representative i The distance from the drone to the approximate coordinates of the target point; Calculate the approximate coordinates of the target point to the drone position Direction cosines of the vector and linearize the observation equation based on the direction cosines; Based on the position coordinates of multiple UAVs and the linearized observation equations, an observation equation group is established; The observation equations are transformed into the form of least squares, and according to the least squares principle, an iterative equation system including a weight matrix is ​​constructed; Define an inverse proportional function weight determination method, and assume that the weight is expressed as: ； Among them, a and k are constants, and the values ​​of a and k are set according to the distance between the UAV and the target point, the measurement accuracy of the UAV, and the communication signal strength of the UAV; The sum of the weights is calculated as: ； Normalize the weights, and the normalized weights are: ； The matrix of drone weights is represented as: ； When the number of drones is greater than three, list more than three rows of least squares equations to solve the location coordinates of the target point.

7. A joint positioning system based on drones, characterized in that: include: The UAV positioning module is used to obtain the location coordinates of the UAV by receiving satellite signals; A distance detection module is used to obtain the distance between the plurality of drones and the target point by using laser ranging technology; The target positioning module is used to solve the position coordinates of the target point based on the position coordinates of multiple drones and the distances between the multiple drones and the target point.

8. The method according to claim 7, characterized in that The UAV positioning module includes: In pseudorange measurement, the time t when the signal reaches the receiver is directly measured. S The time t at which the signal leaves the satellite R The product of the time difference and the speed of light in vacuum is the pseudorange observation value: , where c is the speed of light; The corrected geometric distance between the drone and the satellite is: ， Among them, the error between the satellite clock and the standard GPS time is , the error between the receiver clock and the standard GPS time is ; Considering the ionospheric delay and tropospheric delay, the pseudorange observation equation is obtained as follows: ， in, is the geometric distance from the satellite to the receiver, I is the ionospheric delay parameter, and T is the tropospheric delay parameter; Assume that the position coordinates of the satellite are , the position of the receiver in space at the moment of observation is , then the geometric distance from the satellite to the drone is: ； Based on the geometric distance from the satellite to the UAV, the pseudorange observation equation is updated as: ； Obtaining the satellite signal receiving and sending time difference between the UAV and the multiple satellites, and the position coordinates of the multiple satellites, and substituting the satellite signal receiving and sending time difference between the UAV and the multiple satellites, and the position coordinates of the multiple satellites into the updated pseudo-range observation equation to obtain a set of simultaneous equations; The position coordinates of the UAV are obtained by solving the equation group.

9. A device, characterized in that: include: A memory for storing a UAV-based joint positioning program; A processor is used to implement the steps of the drone-based joint positioning method as described in any one of claims 1-6 when executing the drone-based joint positioning program.

10. A computer-readable storage medium storing a computer program, characterized in that: The readable storage medium stores a UAV-based joint positioning program, and when the UAV-based joint positioning program is executed by the processor, the steps of the UAV-based joint positioning method as described in any one of claims 1-6 are implemented.

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