A method and system for testing spectrum detection performance of unmanned aerial vehicle

Abstract

The present invention relates to the field of drone testing technology, and specifically discloses a method and system for testing the spectrum detection performance of a drone. The method comprises inserting a preset number of radio transmitters containing a band range into a test area, determining theoretical signals at various points in the test area based on the radio transmitters; determining at least one test path for the drone based on the theoretical signals; collecting information along the determined test path to obtain actual signals at various points; and comparing the actual signals with the theoretical signals to determine the test accuracy. The present invention installs multiple signal transmitters in a test scene, and the combination of the signal transmitters can obtain multiple signals, which are distributed at different locations. The test path of the drone is determined based on the signal distribution, which not only increases the variety of test signals for a single test behavior and is more efficient, but also allows testing of moving drones, which is more consistent with actual conditions and has higher test accuracy.

Description

Technical Field

[0001] The present invention relates to the technical field of unmanned aerial vehicle (UAV) testing, and in particular to a method and system for testing the spectrum detection performance of an UAV. Background Art

[0002] The UAV spectrum detection performance test mainly involves the evaluation of the UAV's radio spectrum detection capabilities under different environments, frequency bands and signal conditions.

[0003] The existing drone spectrum detection process is mostly a single evaluation process. For example, allowing the drone to receive signals in a certain band in a certain state is feasible. The test range is related to the band range of the signal transmitter. The larger the band range of the signal transmitter, the more types of signals can be tested. This also means that a test behavior can only test the signal reception performance within the band range. When it is necessary to test the signal reception performance of different band ranges, a new test behavior is required. In layman's terms, the range corresponding to a single test behavior in the existing technology is very narrow. When multiple ranges need to be tested, multiple test behaviors are required. The efficiency of this test architecture is very low. How to improve the test efficiency is the technical problem that the technical solution of the present invention wants to solve. Summary of the Invention

[0004] The purpose of the present invention is to provide a method and system for testing the spectrum detection performance of an unmanned aerial vehicle (UAV) to solve the problems raised in the above background technology.

[0005] To achieve the above object, the present invention provides the following technical solutions:

[0006] A method and system for testing the spectrum detection performance of an unmanned aerial vehicle, the method comprising:

[0007] Inserting a predetermined number of radio transmitters containing a range of frequency bands within the test area, and determining theoretical signals at various points within the test area based on the radio transmitters;

[0008] Determining at least one test path of the UAV based on the theoretical signal; the process of determining the test path includes at least a signal differentiation evaluation process;

[0009] Install a preset number of radio receivers inside the drone, activate different numbers of radio receivers, collect information along the determined test path, and obtain the actual signal at each point;

[0010] The actual signal is compared with the theoretical signal to determine the test accuracy of each activation number.

[0011] As a further embodiment of the present invention, the step of inserting a preset number of radio transmitters with a band range into the test area and determining theoretical signals at various points in the test area based on the radio transmitters includes:

[0012] Obtain a top view of the test area and insert a grid into the top view according to the preset origin position and grid size;

[0013] Select the target node at the grid node based on the selection probability and insert the radio transmitter containing the band range; each time a grid node is selected, the selection probability of other grid nodes is updated accordingly;

[0014] Randomly determine the output frequency of each radio transmitter and send it to the corresponding radio transmitter;

[0015] A grid node without a radio transmitter installed is selected as a node to be inspected, and a theoretical signal of each node to be inspected is calculated according to the determined output frequency of the radio transmitter.

[0016] As a further solution of the present invention: the step of determining at least one test path of the UAV according to the theoretical signal includes:

[0017] Select a node from all the nodes to be inspected as the starting node;

[0018] Calculate the global eigenvalues ​​and local eigenvalues ​​of each adjacent node of the starting node;

[0019] Calculate the evaluation score based on the global eigenvalue and the local eigenvalue, and select the node to be inspected with the largest evaluation score among the adjacent nodes as the next node;

[0020] Take the next node as the starting node, and execute the process of selecting the node to be tested cyclically to obtain the test path;

[0021] Among them, the global eigenvalue is:

[0022] ;

[0023] The local eigenvalues ​​are:

[0024] ;

[0025] The assessment is divided into:

[0026] ;

[0027] Where, For evaluation points, is the global eigenvalue, is the local eigenvalue, and is the preset correction factor, Indicates the total number of nodes selected for inspection. Indicates the node and The difference between the signals of the selected nodes to be tested, Indicates the node and The difference between the signals of the selected nodes to be tested;

[0028] The loop exit condition is: the total number of nodes to be tested in the test path reaches a preset threshold.

[0029] As a further solution of the present invention, the steps of installing a preset number of radio receivers inside the drone, activating different numbers of radio receivers, collecting information along a determined test path, and obtaining actual signals at each point include:

[0030] Installing a predetermined number of radio receivers inside the drone;

[0031] receiving the initial quantity input by the staff as the activation quantity and activating the radio receiver;

[0032] The test path is sent to the UAV, and the actual signal at the node to be tested is collected according to the activated radio receiver, and is used as the actual signal at the currently activated number of nodes to be tested;

[0033] The activation quantity is incremented based on the preset quantity step and executed in a loop; when the activation quantity after the increment reaches the preset quantity threshold, the loop is exited.

[0034] As a further solution of the present invention: the step of comparing the actual signal with the theoretical signal to determine the test accuracy of each activation number includes:

[0035] For any activation quantity, read the actual signal and theoretical signal at each node to be tested in the test path;

[0036] Input the actual signal and the theoretical signal into the preset comparison model to obtain the difference value at each point to be tested;

[0037] The test accuracy of the corresponding activation quantity is calculated according to the difference amount at each to-be-tested point.

[0038] As a further embodiment of the present invention, the method further comprises:

[0039] Sort the test accuracy in increasing order of activation number;

[0040] The difference in test accuracy is calculated to obtain the activation value of each activation quantity.

[0041] The technical solution of the present invention also provides a UAV spectrum detection performance testing system, the system comprising:

[0042] A theoretical signal determination module is used to insert a preset number of radio transmitters with a band range into the test area, and determine the theoretical signal of each point in the test area based on the radio transmitters;

[0043] A test path generation module is configured to determine at least one test path of the UAV based on the theoretical signal; the process of determining the test path includes at least a signal differentiation evaluation process;

[0044] The actual signal acquisition module is used to install a preset number of radio receivers inside the drone, activate different numbers of radio receivers, collect information along the determined test path, and obtain the actual signal at each point;

[0045] The signal comparison module is used to compare the actual signal with the theoretical signal to determine the test accuracy of each activation quantity.

[0046] As a further solution of the present invention: the theoretical signal determination module includes:

[0047] A grid insertion unit is used to obtain a top view of the test area and insert a grid into the top view according to a preset origin position and grid size;

[0048] The transmitter installation unit is used to select a target node at the grid node based on the selection probability and insert a radio transmitter containing a band range; each time a grid node is selected, the selection probability of other grid nodes is updated accordingly;

[0049] an output frequency determination unit, configured to randomly determine the output frequency of each radio transmitter and send the output frequency to the corresponding radio transmitter;

[0050] The theoretical signal calculation unit is used to select a grid node without a radio transmitter installed at the grid node as a node to be detected, and calculate the theoretical signal of each node to be detected according to the determined output frequency of the radio transmitter.

[0051] As a further solution of the present invention: the test path generation module includes:

[0052] A node selection unit is used to select a node from all nodes to be inspected as a starting node;

[0053] An eigenvalue calculation unit, used to calculate the global eigenvalue and local eigenvalue of each adjacent node of the starting node;

[0054] A selection determination unit is configured to calculate an evaluation score based on the global eigenvalue and the local eigenvalue, and select a node to be inspected with the largest evaluation score among adjacent nodes as the next node;

[0055] The first loop execution unit is used to take the next node as the starting node and cyclically execute the selection process of the node to be tested to obtain a test path;

[0056] Among them, the global eigenvalue is:

[0057] ;

[0058] The local eigenvalues ​​are:

[0059] ;

[0060] The assessment is divided into:

[0061] ;

[0062] Where, For evaluation points, is the global eigenvalue, is the local eigenvalue, and is the preset correction factor, Indicates the total number of nodes selected for inspection. Indicates the node and The difference between the signals of the selected nodes to be tested, Indicates the node and The difference between the signals of the selected nodes to be tested;

[0063] The loop exit condition is: the total number of nodes to be tested in the test path reaches a preset threshold.

[0064] As a further solution of the present invention: the actual signal acquisition module includes:

[0065] a receiver installation unit for installing a preset number of radio receivers inside the UAV;

[0066] The receiver activation unit is used to receive an initial quantity input by a staff member as an activation quantity and activate the radio receiver;

[0067] The acquisition execution unit is used to send the test path to the UAV, and collect the actual signals at the nodes to be tested according to the activated radio receivers as the actual signals at the currently activated number of nodes to be tested;

[0068] The second loop execution unit is used to perform a self-increment operation on the activation quantity based on a preset quantity step and execute the loop; when the activation quantity after the self-increment reaches a preset quantity threshold, the loop is jumped out.

[0069] Compared with the prior art, the present invention has the following beneficial effects:

[0070] The present invention installs multiple signal transmitters in the test scene. The combination of signal transmitters can obtain multiple signals. These signals are distributed at different positions. The test path of the drone is determined according to the signal distribution. On the one hand, the types of test signals for a single test behavior are increased, and the efficiency is higher. On the other hand, this test is performed on a moving drone, which is more consistent with the actual situation and has higher test accuracy. BRIEF DESCRIPTION OF THE DRAWINGS

[0071] In order to more clearly illustrate the technical solutions in the embodiments of the present invention, the following briefly introduces the drawings required for use in the embodiments or the description of the prior art. Obviously, the drawings described below are only some embodiments of the present invention.

[0072] Figure 1 The overall flow chart of the UAV spectrum detection performance testing method is shown.

[0073] Figure 2 The structural diagram of the UAV spectrum detection performance test system is shown. DETAILED DESCRIPTION

[0074] In order to make the technical problems, technical solutions and beneficial effects to be solved by the present invention more clearly understood, the present invention is further described in detail below with reference to the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are only used to explain the present invention and are not intended to limit the present invention.

[0075] Figure 1 The following is a general flow chart of a method and system for testing the spectrum detection performance of a UAV. In an embodiment of the present invention, a method for testing the spectrum detection performance of a UAV is provided, and the method includes:

[0076] Step S100: inserting a preset number of radio transmitters with a band range into the test area, and determining theoretical signals at various points in the test area based on the radio transmitters;

[0077] The test area refers to the test scenario of the drone, such as an indoor test space. Some radio transmitters are installed in the test area. The band range of these radio transmitters is known and determined by the model of the radio transmitter. It is determined at the time of leaving the factory. Based on the installed radio transmitters, the theoretical signals at different points in the test area can be determined. The theoretical signal is what the signal at each point should be under theoretical circumstances. This is a conventional signal propagation superposition calculation process, and the calculation process is known.

[0078] Step S200: determining at least one test path of the UAV based on the theoretical signal; the process of determining the test path at least includes a signal differentiation evaluation process;

[0079] The importance of each point is determined based on the theoretical signal of each point, and then at least one test path composed of the points is determined. After the test path is sent to the drone, the drone will run along the test path to obtain the actual signal, and then determine the accuracy of the actual signal based on the theoretical signal to obtain the test result; in this process, the difference in the theoretical signals of the points on the test path should be as large as possible, so that the drone can test more different signals; it is worth mentioning that the signals of each point in this application are actually the superimposed signals of all radio transmitters. The band range of each radio transmitter is fixed, and this band range may be very small, but after multiple radio transmitters are superimposed, there will be a lot of signal types at each point. Even if some extremely low-cost radio transmitters are used, they can be superimposed on each other to combine a wide range of signal types, thereby improving the comprehensiveness of the testing process.

[0080] Step S300: Install a preset number of radio receivers inside the drone, activate different numbers of radio receivers, collect information along the determined test path, and obtain actual signals at each point;

[0081] A preset number of radio receivers are installed inside the drone. During each test, different numbers of radio receivers are activated in turn, the activation command is determined, and sent to the drone. At the same time, the test path is sent to the drone. The drone will activate a certain number of radio receivers according to the activation command, and then move along the test path to collect actual signals based on the activated radio receivers. It is worth mentioning that the number of installed radio receivers is different from the number of activated radio receivers. Assuming that a drone has five radio receivers installed, the preset number is five, and the activation number is one to five. For example, first activate one radio receiver and perform a test, then activate two radio receivers and perform a test, and so on to realize the detection process.

[0082] Step S400: comparing the actual signal with the theoretical signal to determine the test accuracy of each activation quantity;

[0083] In an example of the technical solution of the present invention, after the drone obtains the actual signal, it compares the actual signal with the theoretical signal. The signal comparison process itself is also an existing solution for calculating the similarity. The simplest way is to compare the integral within a signal period, and the integral difference is the difference. This process is not complicated. Since each group of actual signals is an actual signal of an activation number, the comparison result also corresponds to the test accuracy of the activation number. The test accuracy of different activation numbers obtained can be used as the detection result.

[0084] Regarding step S100, the step of inserting a preset number of radio transmitters with a band range into the test area and determining theoretical signals at various points in the test area based on the radio transmitters includes:

[0085] Obtain a top view of the test area and insert a grid into the top view according to the preset origin position and grid size;

[0086] Select the target node at the grid node based on the selection probability and insert the radio transmitter containing the band range; each time a grid node is selected, the selection probability of other grid nodes is updated accordingly;

[0087] Randomly determine the output frequency of each radio transmitter and send it to the corresponding radio transmitter;

[0088] A grid node without a radio transmitter installed is selected as a node to be inspected, and a theoretical signal of each node to be inspected is calculated according to the determined output frequency of the radio transmitter.

[0089] In the technical solution of the present invention, a top view of the test area is obtained, and a grid is established with a corner point of the top view as the origin position. The units in the grid are rectangular and have a preset size. The grid function is a conventional function in existing editing software, and the origin position is generally the corner point in the lower left corner. After the grid is determined, the nodes of the grid will become the locations where radio transmitters are installed and the locations to be tested. Some radio transmitters are installed at the nodes, and the remaining grid nodes serve as nodes to be tested. Since the size and position of the grid are fixed, the distance between any radio transmitter and any node to be tested is also fixed. Combined with the determined output frequency of the radio transmitter (taken in the band range), the theoretical signal of each node to be tested can be calculated.

[0090] It should be noted that the process of determining the output frequency of each radio transmitter is randomly determined. Once determined, it is fixed in a test behavior. The random method can adopt a determination process based on random numbers. For example, a random number between 0 and 1 is determined and then mapped to the band range.

[0091] Regarding step S200, the step of determining at least one test path of the drone based on the theoretical signal includes:

[0092] Select a node from all the nodes to be inspected as the starting node;

[0093] Calculate the global eigenvalues ​​and local eigenvalues ​​of each adjacent node of the starting node;

[0094] Calculate the evaluation score based on the global eigenvalue and the local eigenvalue, and select the node to be inspected with the largest evaluation score among the adjacent nodes as the next node;

[0095] The next node is taken as the starting node, and the process of selecting the node to be tested is executed cyclically to obtain the test path.

[0096] The test path generation process is also based on grid generation. A node is randomly selected from all the nodes to be tested as the starting node, and the next node is selected around the starting node. Then the next node is selected based on the next node, and so on. Finally, multiple nodes are obtained, and the multiple nodes obtained by fitting are used to obtain the test path. Among them, the process of selecting the next node at each node needs to be determined by two parameters, namely the global eigenvalue and the local eigenvalue. The evaluation score is determined by these two parameters, and the adjacent node with the largest evaluation score is selected as the next node. In addition, the selected nodes are no longer calculated to prevent the path backtracking problem.

[0097] Among them, the global eigenvalue is:

[0098] ;

[0099] The local eigenvalues ​​are:

[0100] ;

[0101] The assessment is divided into:

[0102] ;

[0103] Where, For evaluation points, is the global eigenvalue, is the local eigenvalue, and is the preset correction factor, Indicates the total number of nodes selected for inspection. Indicates the node and The difference between the signals of the selected nodes to be tested, Indicates the node and The difference between the signals of the selected nodes to be tested.

[0104] The above calculation process limits the calculation process of the evaluation score. For a node, when selecting the next node around it, it is necessary to first determine a range, such as an eight-neighborhood. For any node in the eight-neighborhood, a calculation process is performed once; the signal difference (difference amount) between the node and the selected node is calculated, and then the sum is added to obtain the global eigenvalue, and the difference between it and the current node (the first node) is calculated. The signal difference of each node is used as the local eigenvalue. Finally, the global eigenvalue and the local eigenvalue are summed together with the weights preset by the staff to obtain the evaluation score.

[0105] In addition, the process of generating the test path is a process of continuously looping and selecting the next node, and the loop exit condition may be: the total number of nodes to be tested in the test path reaches a preset threshold.

[0106] Regarding step S300, the steps of installing a preset number of radio receivers inside the drone, activating different numbers of radio receivers, collecting information along the determined test path, and obtaining actual signals at each point include:

[0107] Installing a predetermined number of radio receivers inside the drone;

[0108] receiving the initial quantity input by the staff as the activation quantity and activating the radio receiver;

[0109] The test path is sent to the UAV, and the actual signal at the node to be tested is collected according to the activated radio receiver, and is used as the actual signal at the currently activated number of nodes to be tested;

[0110] The activation quantity is incremented based on the preset quantity step and executed in a loop; when the activation quantity after the increment reaches the preset quantity threshold, the loop is exited.

[0111] A preset number of radio receivers are installed inside the drone, which is determined when the drone is put into use. The installation number is fixed, and the activation number is determined from one to the installation number. For each activation number, the activation number of radio receivers is selected and activated (the selection itself can be in sequence or randomly), and the test path is sent to the drone. The actual signal at the node to be tested is collected based on the activated radio receivers. This means that the drone only collects actual signals at the node to be tested in the test path. After the drone completes the movement along the test path, a group of actual signals is obtained; then increase the activation number by one, and collect once in a cycle to obtain another group of actual signals. When the activation number is the same as the installation number (quantity threshold), the loop is exited. At this time, multiple groups of actual signals are obtained.

[0112] Regarding step S500, the step of comparing the actual signal with the theoretical signal to determine the test accuracy of each activation number includes:

[0113] For any activation quantity, read the actual signal and theoretical signal at each node to be tested in the test path;

[0114] Input the actual signal and the theoretical signal into the preset comparison model to obtain the difference value at each point to be tested;

[0115] The test accuracy of the corresponding activation quantity is calculated according to the difference amount at each to-be-tested point.

[0116] For each actual signal in a group of actual signals of each activation number, the theoretical signal at the same node to be tested is read, and the actual signal and the theoretical signal are input into a preset comparison model to obtain the difference amount at each point to be tested. Since the comparison process belongs to the existing solution, this application will not go into details; each actual signal in a group of actual signals can obtain a difference amount, all the difference amounts are accumulated, and the test accuracy is calculated as the final test result; the test accuracy is a numerical value, which is inversely proportional to the mean of the difference amounts at each point to be tested, indicating that the greater the difference, the smaller the test accuracy, and is inversely proportional to the standard deviation of the difference amounts at each point to be tested, indicating that the greater the fluctuation, the smaller the test accuracy.

[0117] As a preferred embodiment of the technical solution of the present invention, the method further includes:

[0118] Sort the test accuracy in increasing order of activation number;

[0119] The difference in test accuracy is calculated to obtain the activation value of each activation quantity.

[0120] In one example of the technical solution of the present invention, the test results are expanded to provide a parameter called activation value. The test accuracy is sorted in ascending order of the number of activations. Assuming that the number of installations is five, and the number of activations is one, two, three, four, and five, respectively, each number of activations can have a test accuracy. Under normal conditions, the more activations there are, the higher the test accuracy (when obtaining the actual signal, the average will be taken, which is more robust). The change (increment) of the test accuracy for each number of activations is calculated, which indicates how much gain can be brought by each increase in the number of activations. This is called the activation value.

[0121] Specifically, the difference calculation process generally uses the difference between the test accuracy of the current activation number and the test accuracy of the previous activation number. When the activation number is one, the activation value is not calculated because it has little practical significance. The activation value essentially reflects the cost utilization rate. The activation value itself is a numerical value that is proportional to the difference.

[0122] As a preferred embodiment of the technical solution of the present invention, a three-dimensional grid can also be inserted based on a three-dimensional graph when inserting a grid. At this time, the present application can be migrated and applied to a three-dimensional scene, which means that the test path of the drone is a three-dimensional path, and the test process is more comprehensive. In fact, the radio transmitter itself propagates in three-dimensional space, and the drone also moves in three-dimensional space. It is more appropriate to conduct tests in a three-dimensional scene.

[0123] Figure 2 The structure diagram of the UAV spectrum detection performance test system is shown. In a preferred embodiment of the technical solution of the present invention, a UAV spectrum detection performance test system is also provided. The system 10 includes:

[0124] Theoretical signal determination module 11 is used to insert a preset number of radio transmitters with a band range into the test area, and determine the theoretical signal of each point in the test area based on the radio transmitters;

[0125] A test path generation module 12 is configured to determine at least one test path of the UAV based on the theoretical signal; the process of determining the test path includes at least a signal differentiation evaluation process;

[0126] The actual signal acquisition module 13 is used to install a preset number of radio receivers inside the UAV, activate different numbers of radio receivers, collect information along the determined test path, and obtain the actual signal at each point;

[0127] The signal comparison module 14 is used to compare the actual signal with the theoretical signal to determine the test accuracy of each activation quantity.

[0128] Furthermore, the theoretical signal determination module 11 includes:

[0129] A grid insertion unit is used to obtain a top view of the test area and insert a grid into the top view according to a preset origin position and grid size;

[0130] The transmitter installation unit is used to select a target node at the grid node based on the selection probability and insert a radio transmitter containing a band range; each time a grid node is selected, the selection probability of other grid nodes is updated accordingly;

[0131] an output frequency determination unit, configured to randomly determine the output frequency of each radio transmitter and send the output frequency to the corresponding radio transmitter;

[0132] The theoretical signal calculation unit is used to select a grid node without a radio transmitter installed at the grid node as a node to be detected, and calculate the theoretical signal of each node to be detected according to the determined output frequency of the radio transmitter.

[0133] Specifically, the test path generation module 12 includes:

[0134] A node selection unit is used to select a node from all nodes to be inspected as a starting node;

[0135] An eigenvalue calculation unit, used to calculate the global eigenvalue and local eigenvalue of each adjacent node of the starting node;

[0136] A selection determination unit is configured to calculate an evaluation score based on the global eigenvalue and the local eigenvalue, and select a node to be inspected with the largest evaluation score among adjacent nodes as the next node;

[0137] The first loop execution unit is used to take the next node as the starting node and cyclically execute the selection process of the node to be tested to obtain a test path;

[0138] Among them, the global eigenvalue is:

[0139] ;

[0140] The local eigenvalues ​​are:

[0141] ;

[0142] The assessment is divided into:

[0143] ;

[0144] Where, For evaluation points, is the global eigenvalue, is the local eigenvalue, and is the preset correction factor, Indicates the total number of nodes selected for inspection. Indicates the node and The difference between the signals of the selected nodes to be tested, Indicates the node and The difference between the signals of the selected nodes to be tested;

[0145] The loop exit condition is: the total number of nodes to be tested in the test path reaches a preset threshold.

[0146] Furthermore, the actual signal acquisition module 13 includes:

[0147] a receiver installation unit for installing a preset number of radio receivers inside the UAV;

[0148] The receiver activation unit is used to receive an initial quantity input by a staff member as an activation quantity and activate the radio receiver;

[0149] The acquisition execution unit is used to send the test path to the UAV, and collect the actual signals at the nodes to be tested according to the activated radio receivers as the actual signals at the currently activated number of nodes to be tested;

[0150] The second loop execution unit is used to perform a self-increment operation on the activation quantity based on a preset quantity step and execute the loop; when the activation quantity after the self-increment reaches a preset quantity threshold, the loop is jumped out.

[0151] The above are only preferred embodiments of the present invention and are not intended to limit the patent scope of the present invention. Any equivalent structure or equivalent process transformation made using the contents of the present invention description and drawings, or directly or indirectly applied in other related technical fields, are also included in the patent protection scope of the present invention.

Claims

1. A method for testing the spectrum detection performance of an unmanned aerial vehicle, characterized in that: The method comprises: Inserting a predetermined number of radio transmitters containing a range of frequency bands within the test area, and determining theoretical signals at various points within the test area based on the radio transmitters; Determining at least one test path of the UAV based on the theoretical signal; the process of determining the test path includes at least a signal differentiation evaluation process; Install a preset number of radio receivers inside the drone, activate different numbers of radio receivers, collect information along the determined test path, and obtain the actual signal at each point; Compare the actual signal with the theoretical signal to determine the test accuracy of each activation quantity; The step of determining at least one test path of the UAV according to the theoretical signal comprises: Select a node from all the nodes to be inspected as the starting node; Calculate the global eigenvalues ​​and local eigenvalues ​​of each adjacent node of the starting node; Calculate the evaluation score based on the global eigenvalue and the local eigenvalue, and select the node to be inspected with the largest evaluation score among the adjacent nodes as the next node; Take the next node as the starting node, and execute the process of selecting the node to be tested cyclically to obtain the test path; Among them, the global eigenvalue is: ； The local eigenvalues ​​are: ； The assessment is divided into: ； Where, For evaluation points, is the global eigenvalue, is the local eigenvalue, and is the preset correction factor, Indicates the total number of nodes selected for inspection. Indicates the node and The difference between the signals of the selected nodes to be tested, Indicates the node and The difference between the signals of the selected nodes to be tested; The loop exit condition is: the total number of nodes to be tested in the test path reaches a preset threshold.

2. The UAV spectrum detection performance testing method according to claim 1 is characterized in that: The step of inserting a preset number of radio transmitters with a band range into the test area and determining theoretical signals at various points in the test area based on the radio transmitters includes: Obtain a top view of the test area and insert a grid into the top view according to the preset origin position and grid size; Select the target node at the grid node based on the selection probability and insert the radio transmitter containing the band range; each time a grid node is selected, the selection probability of other grid nodes is updated accordingly; Randomly determine the output frequency of each radio transmitter and send it to the corresponding radio transmitter; A grid node without a radio transmitter installed is selected as a node to be inspected, and a theoretical signal of each node to be inspected is calculated according to the determined output frequency of the radio transmitter.

3. The UAV spectrum detection performance testing method according to claim 1, characterized in that: The steps of installing a preset number of radio receivers inside the drone, activating different numbers of radio receivers, collecting information along a determined test path, and obtaining actual signals at each point include: Installing a predetermined number of radio receivers inside the drone; receiving the initial quantity input by the staff as the activation quantity and activating the radio receiver; The test path is sent to the UAV, and the actual signal at the node to be tested is collected according to the activated radio receiver, and is used as the actual signal at the currently activated number of nodes to be tested; The activation quantity is incremented based on the preset quantity step and executed in a loop; when the activation quantity after the increment reaches the preset quantity threshold, the loop is exited.

4. The UAV spectrum detection performance testing method according to claim 1, characterized in that: The step of comparing the actual signal with the theoretical signal to determine the test accuracy of each activation quantity includes: For any activation quantity, read the actual signal and theoretical signal at each node to be tested in the test path; Input the actual signal and the theoretical signal into the preset comparison model to obtain the difference value at each point to be tested; The test accuracy of the corresponding activation quantity is calculated according to the difference amount at each to-be-tested point.

5. The UAV spectrum detection performance testing method according to claim 4, characterized in that: The method further comprises: Sort the test accuracy in increasing order of activation number; The difference in test accuracy is calculated to obtain the activation value of each activation quantity.

6. A UAV spectrum detection performance test system, characterized in that: The system comprises: A theoretical signal determination module is used to insert a preset number of radio transmitters with a band range into the test area, and determine the theoretical signal of each point in the test area based on the radio transmitters; A test path generation module is configured to determine at least one test path of the UAV based on the theoretical signal; the process of determining the test path includes at least a signal differentiation evaluation process; The actual signal acquisition module is used to install a preset number of radio receivers inside the drone, activate different numbers of radio receivers, collect information along the determined test path, and obtain the actual signal at each point; The signal comparison module is used to compare the actual signal with the theoretical signal to determine the test accuracy of each activation quantity; The test path generation module includes: A node selection unit is used to select a node from all nodes to be inspected as a starting node; An eigenvalue calculation unit, used to calculate the global eigenvalue and local eigenvalue of each adjacent node of the starting node; A selection determination unit is configured to calculate an evaluation score based on the global eigenvalue and the local eigenvalue, and select a node to be inspected with the largest evaluation score among adjacent nodes as the next node; The first loop execution unit is used to take the next node as the starting node and cyclically execute the selection process of the node to be tested to obtain a test path; Among them, the global eigenvalue is: ； The local eigenvalues ​​are: ； The assessment is divided into: ； Where, For evaluation points, is the global eigenvalue, is the local eigenvalue, and is the preset correction factor, Indicates the total number of nodes selected for inspection. Represents the node and The difference between the signals of the selected nodes to be tested, Represents the node and The difference between the signals of the selected nodes to be tested; The loop exit condition is: the total number of nodes to be tested in the test path reaches a preset threshold.

7. The UAV spectrum detection performance test system according to claim 6, characterized in that: The theoretical signal determination module includes: A grid insertion unit is used to obtain a top view of the test area and insert a grid into the top view according to a preset origin position and grid size; The transmitter installation unit is used to select a target node at the grid node based on the selection probability and insert a radio transmitter containing a band range; each time a grid node is selected, the selection probability of other grid nodes is updated accordingly; an output frequency determination unit, configured to randomly determine the output frequency of each radio transmitter and send the output frequency to the corresponding radio transmitter; The theoretical signal calculation unit is used to select a grid node without a radio transmitter installed at the grid node as a node to be detected, and calculate the theoretical signal of each node to be detected according to the determined output frequency of the radio transmitter.

8. The UAV spectrum detection performance test system according to claim 6, characterized in that: The actual signal acquisition module includes: a receiver installation unit for installing a preset number of radio receivers inside the UAV; The receiver activation unit is used to receive an initial quantity input by a staff member as an activation quantity and activate the radio receiver; The acquisition execution unit is used to send the test path to the UAV, and collect the actual signals at the nodes to be tested according to the activated radio receivers as the actual signals at the currently activated number of nodes to be tested; The second loop execution unit is used to perform a self-increment operation on the activation quantity based on a preset quantity step and execute the loop; when the activation quantity after the self-increment reaches a preset quantity threshold, the loop is jumped out.

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