Unmanned aerial vehicle passive target positioning method and device based on weight coefficient and medium

Abstract

The invention relates to the technical field of passive detection, in particular to an unmanned aerial vehicle passive target positioning method and device based on weight coefficients. The method comprises: based on respective input data of a plurality of observation points from an unmanned aerial vehicle, determining a plurality of target observation point pairs, the input data comprising observation angles of a target object at the observation points and coordinates of the observation points; calculating an observation angle difference value of each target observation point pair, and taking a preset number of target observation point pairs with the maximum observation angle difference value as candidate observation point pairs; calculating the coordinates of the target object according to the respective input data of the two observation points included in the candidate observation points in a preset number to obtain a plurality of target object coordinates; and performing weighted summation calculation on the plurality of target object coordinates to obtain a positioning result of the target object. According to the method, the effect of errors of input data adopted by an existing positioning algorithm is reduced, and the purpose of improving the positioning precision is achieved.

Description

Technical Field

[0001] The present application relates to the technical field of passive detection, and in particular, to a method and device for passive target positioning of an unmanned aerial vehicle based on weight coefficients. Background Art

[0002] With the continuous development of unmanned aerial vehicle technology, the technology of positioning the target position by unmanned aerial vehicles has received more and more extensive attention. Passive positioning refers to the technology of determining the target position by measuring the signals of the target through multiple sensors with good spatial distribution without deploying any equipment on the target. In the prior art, mainly the positioning method based on lateral intersection is adopted. The basic principle of this method is to observe the target multiple times and perform positioning according to the principle that the observation lines intersect at one point. By using the heading angle and roll and pitch attitudes of the unmanned aerial vehicle, as well as the positioning and pitch angle information of the optoelectronic system, the observation angle of the line of sight of the unmanned aerial vehicle pointing to the target in three-dimensional space is calculated, and the target position is solved by using two groups of observation angles and the position of the unmanned aerial vehicle itself. Since the input quantities of this method all come from the sensors of the unmanned aerial vehicle and the optoelectronic system, the errors generated in the information acquisition process of the sensors will accumulate to the final positioning result, resulting in a large positioning error. Summary of the Invention

[0003] The present application provides a method, device, electronic device and computer-readable storage medium for passive target positioning of an unmanned aerial vehicle based on weight coefficients, which can solve the problems of large positioning error and low positioning accuracy existing in passive positioning of unmanned aerial vehicles. The technical solutions are as follows:

[0004] In a first aspect, a method for passive target positioning of an unmanned aerial vehicle based on weight coefficients is provided, and the method includes:

[0005] Based on the input data of each of several observation points from the unmanned aerial vehicle, a plurality of target observation point pairs are determined, and the input data includes the observation angle of the target object at the observation point and the coordinates of the observation point;

[0006] Calculate the observation angle difference of each of the target observation point pairs, and use the first predetermined number of the target observation point pairs with the largest observation angle differences as candidate observation point pairs;

[0007] Calculate the coordinates of the target object based on the input data of the two observation points included in a predetermined number of the candidate observation point pairs, and obtain a plurality of target object coordinates;

[0008] Perform a weighted summation calculation on the plurality of target object coordinates to obtain the positioning result of the target object.

[0009] In a second aspect, a device for passive target positioning of an unmanned aerial vehicle based on weight coefficients is provided, and the device includes:

[0010] An observation point pair determination module, configured to determine a plurality of target observation point pairs based on input data of respective several observation points from a drone, where the input data includes an observation angle of the target object at the observation point and coordinates of the observation point;

[0011] An observation point pair selection module, configured to calculate an observation angle difference of each of the target observation point pairs, and use the top predetermined number of target observation point pairs with the largest observation angle differences as candidate observation point pairs;

[0012] An observation point pair calculation module, configured to calculate coordinates of the target object based on input data of two observation points included in a predetermined number of the candidate observation point pairs, to obtain a plurality of target object coordinates;

[0013] A positioning result determination module, configured to perform a weighted summation calculation on the plurality of target object coordinates to obtain a positioning result of the target object.

[0014] In a third aspect of an embodiment of the present application, an electronic device is disclosed. The electronic device includes a memory, a processor, and a computer program stored in the memory and executable on the processor. When the processor executes the computer program, the steps of the above method are implemented.

[0015] In a fourth aspect of an embodiment of the present application, a computer-readable storage medium is disclosed. The computer-readable storage medium stores a computer program, and when the computer program is executed by a processor, the steps of the above method are implemented.

[0016] In an embodiment of the present application, a plurality of target observation point pairs are determined based on input data of respective several observation points of a drone flight path, so as to calculate an observation angle difference of each target observation point pair, and then perform screening according to the difference calculation result to obtain candidate observation point pairs, and calculate weighted sums of coordinates of these candidate observation point pairs to obtain a final positioning result. This method of determining a final positioning result by performing weighted summation on positioning results of multiple groups of observation point pairs reduces the error of input data used in the existing positioning algorithm, achieving the purpose of improving positioning accuracy. Description of the Drawings

[0017] In order to more clearly illustrate the technical solutions in the embodiments of the present application, the following will briefly introduce the drawings required for description in the embodiments of the present application.

[0018] Figure 1 It is a schematic structural diagram of a drone passive target positioning method based on a weight coefficient provided by an embodiment of the present application;

[0019] Figure 2Schematic diagram of observing a target object in the flight trajectory of a drone provided by an embodiment of the present application;

[0020] Figure 3 Schematic diagram of the structure of a passive target positioning device for a drone based on weight coefficients provided by an embodiment of the present application. Detailed implementation manners

[0021] The embodiments of the present application will be described in detail below. The examples of the embodiments are shown in the accompanying drawings, where the same or similar reference numerals represent the same or similar elements or elements with the same or similar functions throughout. The embodiments described below with reference to the accompanying drawings are exemplary and are only used to explain the present application and should not be construed as limiting the present application.

[0022] An embodiment of the present application provides a passive target positioning method for a drone based on weight coefficients. As Figure 1 shown, the method includes: step S101 to step S104.

[0023] Step S101: Based on the input data of each of several observation points from the drone, determine a plurality of target observation point pairs. The input data includes the observation angle of the target object at the observation point and the coordinates of the observation point.

[0024] Specifically, each point of the continuous flight track of the drone can be an observation point, or a target observation point pair selected from the observation points determined according to preset conditions on the continuous track. In application, the sampling data of the continuous flight track of the drone can be obtained according to a preset sampling frequency.

[0025] Specifically, the input data of each observation point can be determined according to a pre-constructed three-dimensional coordinate space.

[0026] Step S102: Calculate the observation angle difference of each target observation point pair, and use the top predetermined number of target observation point pairs with the largest observation angle difference as candidate observation point pairs.

[0027] Specifically, the observation angle differences of each target observation point pair can be sorted, and candidate observation point pairs can be selected according to the sorting result.

[0028] Step S103: Calculate the coordinates of the target object based on the input data of the two observation points included in a predetermined number of the candidate observation point pairs, and obtain a plurality of target object coordinates.

[0029] Step S104: Perform a weighted summation calculation on the plurality of target object coordinates to obtain the positioning result of the target object.

[0030] In the embodiments of the present application, multiple target observation point pairs are determined based on the input data of respective observation points of the UAV flight path, so as to calculate the observation angle differences of each target observation point pair, and then screen according to the difference calculation results to obtain candidate observation point pairs, and calculate the coordinates of these candidate observation point pairs and then perform weighted summation to obtain the final positioning result. This method of determining the final positioning result by weighted summation of the positioning results of multiple groups of observation point pairs reduces the error of the input data used in the existing positioning algorithm and achieves the purpose of improving the positioning accuracy.

[0031] In some embodiments, step S101 further includes:

[0032] Store the first observation point in the UAV flight trajectory into a pre-constructed queue;

[0033] Calculate the difference between the observation angle of the first observation point subsequent to the first observation point and the observation angle of the first observation point;

[0034] When the difference is not less than a preset observation angle threshold, perform enqueue processing on the first observation point subsequent to the first observation point, and use the first observation point and the first observation point subsequent to the first observation point as the target observation point pair.

[0035] During application, assume that a queue Q is pre-constructed and the length of the queue Q is specified as W. During the UAV flight, the passive positioning system starts to receive a set of input data P1 and stores it in the queue Q. At this time, the queue length L = 1. To avoid storing a large amount of duplicate data, an angle threshold is set . When the difference between the observation angle value in the subsequent input data and the observation angle value of the previous set of input data is greater than or equal to the threshold 0, store it in the queue Q and record the queue length L. When the difference between the observation angle values is less than the threshold, discard the observation point. If the queue length has reached the upper limit W, the data input at the beginning is removed from the queue to keep the queue length L less than or equal to W.

[0036] Specifically, during the data enqueue process, point pair selection is performed on the enqueued data in real time. Starting from the second data stored, every time an observation point data is stored in the queue Q, a point pair selection is performed, and the observation angle differences of all point pairs in the queue Q are sorted in descending order, and the first L / 2 groups of point pairs with the largest observation angle differences are selected.

[0037] In some embodiments, step S101 further includes: when the difference between the observation angle of the first observation point subsequent to the first observation point and the observation angle of the first observation point is less than a preset observation angle threshold, discarding the first observation point subsequent to the first observation point, and performing the step of calculating the difference between the observation angle of the first observation point subsequent to the first observation point and the observation angle of the first observation point on the second observation point subsequent to the first observation point, and performing corresponding processing on the second observation point subsequent to the first observation point according to the calculation result.

[0038] During application, the observation angle difference of the data to be queued is calculated with the data that was last queued in the queue, and the data to be queued with an observation angle difference less than the preset observation angle threshold is discarded to judge the next data to be queued.

[0039] In some embodiments, step S103 further includes:

[0040] Calculating each pair of candidate observation points based on a preset lateral intersection positioning algorithm to obtain multiple target object coordinates.

[0041] During application, as Figure 2 shown, the unmanned aerial vehicle observes a target at a pair of observation points A and B in a group, and obtains observation angles (a 1 , β 1 ), (a 2 , β 2 ). The three-dimensional coordinates of point A and point B are (x, y, z) and (x 2 , y, z), then according to the direction-finding intersection positioning method, the three-dimensional coordinates of the target (x, y, z) can be expressed as:

[0042]

[0043] In some embodiments, step S104 further includes:

[0044] Step S1041 (not shown in the figure): Based on the weight coefficients corresponding to different preset observation angles, performing a weighted summation calculation on the multiple target object coordinates to obtain a positioning result of the target object.

[0045] Specifically, the weight coefficients corresponding to different observation angles are different.

[0046] Assume the positioning result is: (Q 1 , Q 2 ,..., Qn), and the weight coefficient is: The result of weighted positioning is: Where m is an adjustment parameter.

[0047] When applying, various flight trajectory strategies corresponding to different positioning scenarios can be preset. When the input positioning scenario of the user is detected, the corresponding flight trajectory strategy is determined. For example, in a positioning scenario with large terrain undulations in a mountainous environment, the altitude of the UAV generally needs to change continuously. The corresponding flight trajectory strategy can be a strategy where the flight altitude needs to change. Since the distance to the target may be relatively close and the pitch angle is larger during observation in this positioning scenario. Therefore, different weight coefficients should be set for different positioning scenarios.

[0048] In some embodiments, step S104 further includes:

[0049] Based on the weight coefficient comparison tables corresponding to various flight trajectories, determine the target weight coefficient comparison table corresponding to the current flight trajectory of the UAV;

[0050] According to the target weight coefficient comparison table, determine the weight coefficients corresponding to different observation angles.

[0051] Specifically, the flight trajectory can include a straight flight trajectory, a circular flight trajectory, etc. Among them, the straight flight trajectory is suitable for environmental scenarios without obvious target occlusion such as plains and sandy lands, as well as battlefield environments where reconnaissance can only be carried out on one side of the target considering safety factors, and its path planning is relatively simple. The circular flight trajectory is suitable for environmental scenarios without serious occlusion and battlefield environments with high safety factors, which are convenient for multi-directional reconnaissance of the target. According to the principle of the direction-finding intersection algorithm, under the condition that the data input error range is fixed, the observation lines of each observation point are within a fan-shaped area determined according to the error range. Then, the intersection point of the observation lines of two observation points is within the overlapping quadrilateral determined by the two fan-shaped areas, which is called the positioning ambiguity area. The area of the ambiguity area can be used as an index to measure the positioning accuracy. If the included angle between the observation lines of two observation points is too small or too large, the area of the ambiguity area will become larger. Therefore, at the same flight speed, to achieve the same positioning accuracy, the range of the included angle of the observation lines flown by the UAV is the same. The flight distance of the circular flight trajectory is shorter, and the positioning efficiency is higher than that of the straight flight trajectory. In actual use, a suitable flight path should be selected according to the battlefield environment, positioning accuracy, and efficiency requirements to achieve the purpose of track sampling.

[0052] When the UAV performs reconnaissance and positioning tasks in typical scenarios such as mountainous, hilly, and urban environments, due to different factors such as terrain and environment, the flight routes and flight trajectories of the UAV will form their own characteristics. In the mountainous environment, the terrain undulates greatly, the altitude of the UAV needs to change continuously, the distance to the target may be relatively close during observation, and the pitch angle of the pod is larger. In the hilly environment, the terrain is relatively flat, and the pod can cruise at a constant altitude at a sufficient height. In the urban environment, the buildings are dense, the terrain is generally flat, but affected by the occlusion of buildings, the aircraft may need to make large-angle maneuvers. For different flight trajectories, different weight coefficients should be considered for selection.

[0053] The following takes the flight process of a drone from Figure 2 the position point A to the position point B shown as an example for illustration. After the first data is stored in the queue Q, during the process of enqueuing the second data, calculate the difference in the observed angle values between the second data and the first data. Since the target is between A and B, therefore, during the flight from point A towards the target, the pitch angle gradually increases, and after flying past the target, the pitch angle gradually decreases. Therefore, the difference in the pitch angle can be used as the selection criterion when selecting point pairs. For example, in the flight trajectory starting from point A, the first data is the observed angle of A (a 1 , β 1 ). Flying towards the target (shown as a dot) from A, that is, in the direction from A to B, assume the second data is B1 (a 2 , β 2 ). The observed angle difference C1 of the first point pair is obtained as (β 2 - β 1 ). If the next position point that the drone reaches after flying to the B1 position is between A and B1, then the third data is B2 (a 3 , β 3 ). Then the observed angle difference C2 of the point pair composed of B1 and B2 is less than C1. At this time, discard the third data B2. That is to say, during the process of the drone flying from A to B and collecting data for enqueue storage, calculate the observed angle differences of adjacent two point pairs in real time, so as to ensure that the flight trajectory is in the direction of approaching the target. After the enqueue is completed, perform a descending order sorting according to the observed angle differences of the point pairs calculated in real time, and select the generally front - ranked point pairs for coordinate calculation. Finally, calculate according to step S1041 to obtain the positioning result Q.

[0054] Another embodiment of the present application provides a drone passive target positioning device based on a weight coefficient. As Figure 3 shown, the device 30 includes: an observation point pair determination module 301, an observation point pair selection module 302, an observation point pair calculation module 303, and a positioning result determination module 304.

[0055] The observation point pair determination module is used to determine a plurality of target observation point pairs based on the input data of several observation points from the drone. The input data includes the observed angle of the target object at the observation point pair and the coordinates of the observation point.

[0056] The observation point pair selection module is used to calculate the observed angle differences of each of the target observation point pairs, and use the top predetermined number of target observation point pairs with the largest observed angle differences as candidate observation point pairs.

[0057] An observation point pair calculation module is configured to calculate the coordinates of the target object based on the input data of two observation points included in a predetermined number of candidate observation point pairs, and obtain a plurality of target object coordinates;

[0058] A positioning result determination module is configured to perform a weighted summation calculation on the plurality of target object coordinates to obtain the positioning result of the target object.

[0059] In the embodiment of the present application, a plurality of target observation point pairs are determined based on the input data of several observation points of the UAV flight path, so as to calculate the observation angle difference of each target observation point pair, and then screen according to the difference calculation result to obtain candidate observation point pairs. After calculating the coordinates of these candidate observation point pairs, a weighted summation is performed to obtain the final positioning result. This method of determining the final positioning result by performing a weighted summation on the positioning results of multiple groups of observation point pairs reduces the error of the input data used in the existing positioning algorithm and achieves the purpose of improving the positioning accuracy.

[0060] Further, the observation point pair determination module includes:

[0061] A data enqueue sub-module is configured to store the first observation point in the UAV flight trajectory into a pre-constructed queue;

[0062] An enqueue judgment sub-module is configured to calculate the difference between the observation angle of the first observation point subsequent to the first observation point and the observation angle of the first observation point;

[0063] A point pair determination sub-module is configured to, when the difference is not less than a preset observation angle threshold, enqueue the first observation point subsequent to the first observation point, and use the first observation point and the first observation point subsequent to the first observation point as the target observation point pair.

[0064] Further, the observation point pair determination module further includes:

[0065] A data enqueue processing sub-module is configured to, when the difference between the observation angle of the first observation point subsequent to the first observation point and the observation angle of the first observation point is less than the preset observation angle threshold, discard the first observation point subsequent to the first observation point, and perform the step of calculating the difference between the observation angle of the first observation point subsequent to the first observation point and the observation angle of the first observation point on the second observation point subsequent to the first observation point, and perform corresponding processing on the second observation point subsequent to the first observation point according to the calculation result.

[0066] Further, the observation point pair calculation module includes:

[0067] A lateral intersection calculation sub-module, configured to calculate each of the candidate observation points based on a preset lateral intersection positioning algorithm to obtain multiple target object coordinates.

[0068] Further, the positioning result determination module includes:

[0069] A coordinate weighting processing sub-module, configured to perform weighted summation calculation on the multiple target object coordinates based on weight coefficients respectively corresponding to preset different observation angles to obtain the positioning result of the target object.

[0070] Further, the positioning result determination module further includes:

[0071] A trajectory weight coefficient determination sub-module, configured to determine a target weight coefficient look-up table corresponding to the current flight trajectory of the UAV based on a comparison of weight coefficients respectively corresponding to multiple flight trajectories;

[0072] An angle weight coefficient determination sub-module, configured to determine weight coefficients respectively corresponding to different observation angles according to the target weight coefficient look-up table.

[0073] The UAV passive target positioning device based on weight coefficients in this embodiment can execute the UAV passive target positioning method shown in Embodiment 1 of the present application, and its implementation principle is similar, which will not be elaborated here.

[0074] Another embodiment of the present application provides a terminal, including: a memory, a processor, and a computer program stored on the memory and executable on the processor, and when the processor executes the computer program, the above method is implemented.

[0075] Specifically, the processor may be a CPU, a general-purpose processor, a DSP, an ASIC, an FPGA, or other programmable logic devices, transistor logic devices, hardware components, or any combination thereof. It can implement or execute various exemplary logical blocks, modules, and circuits described in combination with the disclosure of the present application. The processor may also be a combination that implements computing functions, such as a combination of one or more microprocessors, a combination of a DSP and a microprocessor, etc.

[0076] Specifically, the processor is connected to the memory through a bus, and the bus may include a path for transmitting information. The bus may be a PCI bus or an EISA bus, etc. The bus may be divided into an address bus, a data bus, a control bus, etc.

[0077] The memory may be a ROM or other types of static storage devices that can store static information and instructions, a RAM or other types of dynamic storage devices that can store information and instructions, or an EEPROM, a CD-ROM, or other optical disc storage, optical disc storage (including compact discs, laser discs, optical discs, digital versatile discs, Blu-ray discs, etc.), magnetic disk storage media, or other magnetic storage devices, or any other medium that can be used to carry or store the desired program code in the form of instructions or data structures and can be accessed by a computer, but is not limited thereto.

[0078] Optionally, the memory is used to store the code of the computer program for executing the solution of this application and is controlled by the processor for execution. The processor is used to execute the application program code stored in the memory to implement the actions of the drone passive target positioning device based on the weight coefficient provided in the above embodiments.

[0079] Another embodiment of this application provides a computer-readable storage medium, on which a computer program is stored, and when the program is executed by a processor, the above method is implemented.

[0080] The device embodiments described above are merely illustrative. The units described as separate components may or may not be physically separated, that is, they may be located in one place or distributed to multiple network units. Some or all of the modules can be selected according to actual needs to achieve the purpose of the solution of this embodiment.

[0081] Those of ordinary skill in the art will understand that all or some of the steps and systems disclosed in the above methods can be implemented as software, firmware, hardware, and their appropriate combinations. Some physical components or all physical components can be implemented as software executed by a processor, such as a central processing unit, a digital signal processor, or a microprocessor, or can be implemented as hardware, or can be implemented as an integrated circuit, such as an application specific integrated circuit. Such software can be distributed on a computer-readable medium, which can include a computer storage medium (or non-transitory medium) and a communication medium (or transitory medium). As is well known to those of ordinary skill in the art, the term computer storage medium includes volatile and non-volatile, removable and non-removable media implemented in any method or technology for storing information, such as computer-readable instructions, data structures, program modules, or other data. Computer storage media includes, but is not limited to, RAM, ROM, EEPROM, flash memory or other memory technologies, CD-ROM, digital versatile disks (DVD) or other optical disk storage, magnetic cassettes, tapes, magnetic disk storage or other magnetic storage devices, or any other medium that can be used to store the desired information and can be accessed by a computer. In addition, it is well known to those of ordinary skill in the art that a communication medium typically contains computer-readable instructions, data structures, program modules, or other data in a modulated data signal such as a carrier wave or other transmission mechanism, and can include any information delivery medium.

[0082] The above is a specific description of the preferred embodiments of the present application. However, the present application is not limited to the above embodiments. Those skilled in the art can make various equivalent deformations or substitutions without departing from the spirit of the present application. These equivalent deformations or substitutions are all included within the scope defined by the claims of the present application.

Claims

1. A method for positioning a passive target of an unmanned aerial vehicle based on a weight coefficient, characterized in that: include: Determine a plurality of target observation point pairs based on input data from respective observation points of the drone, wherein the input data includes observation angles of the target object at the observation points and coordinates of the observation points; Calculating the observation angle difference of each target observation point pair, and taking the first predetermined number of target observation point pairs with the largest observation angle difference as candidate observation point pairs; Calculating the coordinates of the target object according to the input data of each of the two observation points included in the predetermined number of candidate observation point pairs to obtain a plurality of target object coordinates; A weighted sum calculation is performed on the coordinates of the multiple target objects to obtain a positioning result of the target object.

2. The method according to claim 1, characterized in that The method of determining a plurality of target observation point pairs based on respective input data from a plurality of observation points of the drone comprises: Storing the first observation point in the UAV flight trajectory into a pre-constructed queue; Calculate the difference between the observation angle of the first observation point subsequent to the first observation point and the observation angle of the first observation point; When the difference is not less than a preset observation angle threshold, the first observation point following the first observation point is queued, and the first observation point and the first observation point following the first observation point are used as a target observation point pair.

3. The method according to claim 2, characterized in that The method of determining a plurality of target observation point pairs based on respective input data from a plurality of observation points of the drone further includes: When the difference between the observation angle of the first observation point subsequent to the first observation point and the observation angle of the first observation point is less than a preset observation angle threshold, the first observation point subsequent to the first observation point is discarded, and the step of calculating the difference between the observation angle of the first observation point subsequent to the first observation point and the observation angle of the first observation point is performed on the second observation point subsequent to the first observation point, and the second observation point subsequent to the first observation point is processed accordingly based on the calculation result.

4. The method according to claim 1, characterized in that: The step of calculating the coordinates of the target object based on the input data of the two observation points included in the predetermined number of candidate observation point pairs to obtain a plurality of target object coordinates includes: Based on a preset lateral cross positioning algorithm, each of the candidate observation points is calculated to obtain multiple target object coordinates.

5. The method according to claim 1, characterized in that The step of performing weighted sum calculation on the coordinates of the plurality of target objects to obtain the positioning result of the target object includes: Based on the preset weight coefficients corresponding to the different observation angles, a weighted sum calculation is performed on the coordinates of the multiple target objects to obtain the positioning result of the target object.

6. The method according to claim 5, characterized in that The step of performing weighted sum calculation on the coordinates of the plurality of target objects to obtain the positioning result of the target object further includes: Based on the comparison of weight coefficients corresponding to the various flight trajectories, a target weight coefficient comparison table corresponding to the current flight trajectory of the UAV is determined; According to the target weight coefficient comparison table, the weight coefficients corresponding to different observation angles are determined.

7. A passive target positioning device for unmanned aerial vehicles based on weight coefficients, characterized in that: include: An observation point pair determination module, configured to determine a plurality of target observation point pairs based on input data from respective observation points of the drone, wherein the input data includes observation angles of the target object at the observation points and coordinates of the observation points; An observation point pair selection module, used to calculate the observation angle difference of each target observation point pair, and select the first predetermined number of target observation point pairs with the largest observation angle difference as candidate observation point pairs; An observation point pair calculation module, used to calculate the coordinates of the target object according to the input data of each of the two observation points included in a predetermined number of candidate observation point pairs, to obtain a plurality of target object coordinates; The positioning result determination module is used to perform weighted sum calculation on the coordinates of the multiple target objects to obtain the positioning result of the target object.

8. The method according to claim 7, characterized in that The observation point pair determination module comprises: A data enqueue submodule, for storing the first observation point in the flight trajectory of the UAV into a pre-built queue; An entry judgment submodule, used for calculating the difference between the observation angle of the first observation point subsequent to the first observation point and the observation angle of the first observation point; The point pair determination submodule is used to queue the first observation point following the first observation point when the difference is not less than a preset observation angle threshold, and to use the first observation point and the first observation point following the first observation point as a target observation point pair.

9. An electronic device, characterized in that: The method comprises a processor and a memory, wherein the memory stores computer-readable instructions, and the processor is used to execute the computer-readable instructions, wherein the computer-readable instructions execute the method according to any one of claims 1 to 7 when executed.

10. A computer-readable storage medium storing computer-executable instructions, wherein the computer-executable instructions are used to execute the method according to any one of claims 1 to 7.

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