Signal source positioning method based on multi-source sensor

Abstract

A signal source positioning method based on a multi-source sensor relates to the technical field of signal source positioning, and comprises the following steps: constructing a three-dimensional triangulation network model of a target service area according to GIS geographic data of the target service area, and according to topographic features of each three-dimensional triangle in the three-dimensional triangulation network model and base station information in the target service area, establishing a three-dimensional triangulation network model; acquiring the layout number and point distribution of the sensor terminals of each three-dimensional triangle; dividing all sensor terminals of each three-dimensional triangle into a plurality of arrival time positioning groups, performing arrival time positioning operation on each arrival time positioning group, and obtaining signal source position coordinates positioned by each arrival time positioning group in each three-dimensional triangle; the signal source position coordinates positioned by the arrival time positioning groups in the three-dimensional triangles are compared, whether frequency arrival time positioning operation is carried out on the arrival time positioning groups or not is judged according to the comparison result, the accurate signal source position coordinates are obtained, and the signal source positioning accuracy and reliability are remarkably improved.

Description

Technical Field

[0001] The invention relates to the technical field of signal source positioning, and in particular to a signal source positioning method based on multi-source sensors. Background Art

[0002] The prior art CN109655875A "Weak signal source positioning method based on four sensors" arranges four detectors symmetrically, and two opposite detectors among the four detectors form two straight lines; based on the intensity of the radiation source detected by the four detectors, the gamma emission rate of the radiation source is obtained.

[0003] The prior art CN116413750A "Vibration signal source positioning method, system and medium" obtains sensing signals from at least two vibration sensing devices located at different positions, each sensing signal includes a vibration signal generated by vibration from the same vibration signal source; based on the sensing signals, determines the time difference between at least two vibration sensing devices located at different positions receiving the vibration signals; and based on the time difference, determines the position of the vibration signal source.

[0004] Existing technologies mostly use the TDOA method to locate the signal source, but when the signal has both a direct path and a reflected path, the sensor may receive multiple signal copies. The arrival times of these signal copies are different, which will cause the measured time difference (TDOA) to be inaccurate. The signal arrival time of the reflected path will be later than that of the direct path, which will cause the measured time difference to be larger than the actual value, thereby affecting the positioning accuracy. In the TDOA method, the time difference of each sensor will form a hyperbola. The multipath effect will cause these hyperbolas to shift, so that the actual position of the signal source is not at the intersection of these hyperbolas. The frequency arrival time (FOA) method uses the frequency characteristics of the signal to distinguish different path signals. The existing frequency arrival time (FOA) method only converts the signal into a signal spectrum diagram according to a fixed window function length, ignoring the complexity of the signal source positioning process, and does not take into account that as the communication distance gradually increases, the complexity of the noise signal is also increasing. If the signal is still converted into a signal spectrum diagram according to a fixed window function length, the converted signal spectrum diagram cannot fully express the characteristics of noisy speech. How to select different window function lengths as the communication distance gradually increases to fully express the signal and combine the TDOA method and the frequency arrival time (FOA) method to accurately identify the location of the signal source is an urgent problem that we need to solve. Summary of the invention

[0005] In order to solve the above technical problems, the object of the present invention is to provide a signal source positioning method based on a multi-source sensor, comprising the following steps:

[0006] Step s1: construct a 3D triangulated network model of the target service area based on the GIS geographic data of the target service area, and obtain the number of sensor terminals and point distribution of each 3D triangle based on the terrain features of each 3D triangle in the 3D triangulated network model and the base station information in the target service area;

[0007] Step s2: Divide all sensor terminals of each three-dimensional triangle into a number of arrival time positioning groups, perform arrival time positioning operations on the received signals of the sensor terminals of each arrival time positioning group, and obtain the signal source position coordinates positioned by each arrival time positioning group in each three-dimensional triangle;

[0008] Step s3: Compare the signal source position coordinates located by each arrival time positioning group in each three-dimensional triangle, and determine whether to perform frequency arrival time positioning operation on the arrival time positioning group according to the comparison result to obtain accurate signal source position coordinates.

[0009] Furthermore, the process of constructing a three-dimensional triangulated network model of the target service area based on the GIS geographic data of the target service area includes:

[0010] The GIS geographic data and digital elevation data in the target service area are obtained through GIS means, a plane triangulated network model of the target service area is constructed according to the GIS geographic data, terrain features are given to each triangle in the plane triangulated network model, the elevations on the vertices of each triangle in the plane triangulated network model are set according to the digital elevation data, a three-dimensional triangulated network model of the target service area is obtained, and a three-dimensional coordinate system is constructed based on the three-dimensional triangulated network model.

[0011] Furthermore, according to the terrain features of each three-dimensional triangle in the three-dimensional triangulated network model and the base station information in the target service area, the process of obtaining the number of sensor terminals deployed in each three-dimensional triangle includes:

[0012] A geographic signal interference comparison table is preset, and the geographic signal interference comparison table includes signal attenuation coefficients corresponding to sensor terminals under different terrain feature conditions. The signal attenuation coefficient of each three-dimensional triangle is obtained according to the terrain features of each three-dimensional triangle in the three-dimensional triangulated network model of the target service area and the geographic signal interference comparison table, and the location characteristics, signal transmission power and signal coverage range of each base station in the target service area are obtained. According to the location characteristics of each base station and the location characteristics of each three-dimensional triangle, the comprehensive signal strength of each three-dimensional triangle is obtained, and the importance coefficient of each three-dimensional triangle is obtained according to the signal attenuation coefficient and the comprehensive signal strength of each three-dimensional triangle. According to the importance coefficient, the number of sensor terminals deployed in each three-dimensional triangle is obtained.

[0013] Furthermore, the process of obtaining the point distribution of the sensor terminal of each three-dimensional triangle includes:

[0014] According to the maximum coverage range corresponding to the sensor terminals of each three-dimensional triangle under the terrain characteristics of the three-dimensional triangle and the number of sensor terminals deployed, the comprehensive coverage rate of the sensor terminals of each three-dimensional triangle is obtained, and the comprehensive coverage rate is used as the objective function of the particle swarm algorithm to obtain the optimal deployment position of the sensor terminals within each three-dimensional triangle through the particle swarm algorithm.

[0015] Furthermore, all sensor terminals of each three-dimensional triangle are divided into a plurality of arrival time positioning groups, and an arrival time positioning operation is performed on the received signals of the sensor terminals of each arrival time positioning group. The process of obtaining the signal source position coordinates positioned by each arrival time positioning group in each three-dimensional triangle includes:

[0016] Select any m sensor terminals in the three-dimensional triangle and mark them as an arrival time positioning group, where m≥3, and divide all sensor terminals in the three-dimensional triangle into several arrival time positioning groups;

[0017] Obtaining a timestamp of a signal received by a sensor terminal in the arrival time positioning group, and obtaining a signal arrival time difference between two sensor terminals in the arrival time positioning group according to the timestamp;

[0018] The position coordinates of m sensor terminals in the arrival time positioning group are obtained, and multiple hyperbolic equations are constructed according to the position coordinates of the m sensor terminals in the arrival time positioning group and the signal arrival time difference between any two sensor terminals, and the signal source position coordinates are obtained according to the multiple hyperbolic equations.

[0019] Further, the signal source position coordinates located by each arrival time location group in each three-dimensional triangle are compared, and it is determined whether to perform a frequency arrival time location operation on the arrival time location group according to the comparison result. The process of obtaining the accurate signal source position coordinates includes:

[0020] Compare the signal source position coordinates located by each arrival time positioning group in the three-dimensional triangle, obtain the signal source positioning deviation value between each arrival time positioning group, compare the signal source positioning deviation value with the preset deviation value threshold, if there is no signal source positioning deviation value greater than the deviation value threshold, perform mean processing on the signal source position coordinates located by each arrival time positioning group, obtain the mean signal source position coordinates of the three-dimensional triangle, and mark the mean signal source position coordinates as the precise signal source position coordinates;

[0021] If there is a signal source positioning deviation value greater than the deviation value threshold, two groups of arrival time positioning groups corresponding to the signal source positioning deviation value are obtained, and the two groups of arrival time positioning groups are marked as abnormal arrival time positioning groups. Frequency arrival time positioning operation is performed on the abnormal arrival time positioning groups to obtain precise signal source position coordinates.

[0022] Furthermore, the process of performing frequency arrival time positioning operation on the abnormal arrival time positioning group to obtain accurate signal source position coordinates includes:

[0023] The window function length of each sensor terminal in the abnormal arrival time positioning group is obtained, and the signal received by each sensor terminal is Fourier transformed according to the window function length of each sensor terminal in the abnormal arrival time positioning group to obtain a signal spectrum diagram, and the frequency position, amplitude and phase of each peak in the signal spectrum diagram are extracted. The frequency position, amplitude and phase of each peak in the signal spectrum diagram are analyzed by multipath separation using the ESPRIT algorithm, and the received signal of each sensor terminal is separated into a direct path signal and a reflected path signal. The arrival time positioning operation is performed again on the direct path signal received by each sensor terminal to obtain the precise signal source position coordinates.

[0024] Furthermore, the process of obtaining the window function length of each sensor terminal in the abnormal arrival time location group includes:

[0025] The signal source position coordinates located by each arrival time positioning group in the three-dimensional triangle are averaged to obtain the signal source position mean coordinates of the three-dimensional triangle. According to the position coordinates of each sensor terminal in the abnormal arrival time positioning group and the signal source position mean coordinates, the Euclidean distance between each sensor terminal in the abnormal arrival time positioning group and the signal source position mean coordinates is obtained. Meanwhile, a window function length comparison table is preset, wherein the window function comparison table includes window function lengths corresponding to different terrain features and Euclidean distances. According to the Euclidean distance between each sensor terminal in the abnormal arrival time positioning group and the signal source position mean coordinates, the terrain features of the three-dimensional triangle and the window function length comparison table, the window function length of each sensor terminal in the abnormal arrival time positioning group is obtained.

[0026] Compared with the prior art, the present invention has the following beneficial effects:

[0027] 1. High-precision positioning: By combining TOA and FOA methods, the positioning accuracy can be improved in multipath environments, especially when the multipath effect is significant.

[0028] 2. Utilization of three-dimensional geographic information: Using GIS data to construct a three-dimensional triangulated network model makes the sensor layout more scientific and reasonable, and enhances the robustness and adaptability of the system.

[0029] 3. Multi-sensor collaboration: By dividing the sensor terminals into multiple positioning groups, multi-sensor collaboration is achieved, improving the reliability and accuracy of positioning.

[0030] 4. Dynamic adjustment: Dynamically adjust the positioning strategy according to the positioning results, and perform FOA positioning when necessary to cope with the multipath effect in complex environments.

[0031] 5. Strong adaptability: It is suitable for a variety of environments, including complex terrains such as densely populated urban areas and mountainous areas, and can effectively cope with the signal propagation characteristics under different environmental conditions.

[0032] 6. High degree of automation: The whole process is highly automated, which reduces manual intervention and improves efficiency and operability. BRIEF DESCRIPTION OF THE DRAWINGS

[0033] Figure 1 This is a schematic diagram of a signal source localization method based on a multi-source sensor according to an embodiment of the present application. DETAILED DESCRIPTION

[0034] The following is a clear and complete description of the technical solutions in the embodiments of the present application in conjunction with the drawings in the embodiments of the present application. Obviously, the described embodiments are part of the embodiments of the present application, not all of the embodiments. Based on the embodiments in the present application, all other embodiments obtained by those skilled in the art without creative work are within the scope of protection of the present application.

[0035] like Figure 1 As shown, a signal source positioning method based on multi-source sensors includes the following steps:

[0036] Step s1: construct a 3D triangulated network model of the target service area based on the GIS geographic data of the target service area, and obtain the number of sensor terminals and point distribution of each 3D triangle based on the terrain features of each 3D triangle in the 3D triangulated network model and the base station information in the target service area;

[0037] Step s2: Divide all sensor terminals of each three-dimensional triangle into a number of arrival time positioning groups, perform arrival time positioning operations on the received signals of the sensor terminals of each arrival time positioning group, and obtain the signal source position coordinates positioned by each arrival time positioning group in each three-dimensional triangle;

[0038] Step s3: Compare the signal source position coordinates located by each arrival time positioning group in each three-dimensional triangle, and determine whether to perform frequency arrival time positioning operation on the arrival time positioning group according to the comparison result to obtain accurate signal source position coordinates.

[0039] It should be further explained that, in the specific implementation process, the process of constructing a three-dimensional triangulated network model of the target service area based on the GIS geographic data of the target service area includes:

[0040] The GIS geographic data and digital elevation data in the target service area are obtained through GIS means, a plane triangulated network model of the target service area is constructed according to the GIS geographic data, terrain features are given to each triangle in the plane triangulated network model, the elevations on the vertices of each triangle in the plane triangulated network model are set according to the digital elevation data, a three-dimensional triangulated network model of the target service area is obtained, and a three-dimensional coordinate system is constructed based on the three-dimensional triangulated network model.

[0041] It should be further explained that, in the specific implementation process, according to the terrain features of each three-dimensional triangle in the three-dimensional triangulated network model and the base station information in the target service area, the process of obtaining the number of sensor terminals deployed in each three-dimensional triangle includes:

[0042] A geographic signal interference comparison table is preset, wherein the geographic signal interference comparison table includes signal attenuation coefficients corresponding to sensor terminals under different terrain feature conditions, and the signal attenuation coefficients of each three-dimensional triangle are obtained according to the terrain features of each three-dimensional triangle in the three-dimensional triangulated network model of the target service area and the geographic signal interference comparison table, and the location features, signal transmission power and signal coverage of each base station in the target service area are obtained; the comprehensive signal strength of each three-dimensional triangle is obtained according to the location features of each base station and the location features of each three-dimensional triangle, and the importance coefficient of each three-dimensional triangle is obtained according to the signal attenuation coefficient and the comprehensive signal strength of each three-dimensional triangle; the number of sensor terminals deployed for each three-dimensional triangle is obtained according to the importance coefficient, and the number of sensor terminals deployed for each three-dimensional triangle is at least six.

[0043] It should be further explained that, in the specific implementation process, the calculation formula for obtaining the comprehensive signal strength and importance coefficient of each three-dimensional triangle is:

[0044] ef i =δ∑ j∈M(i) def j *sd j ;

[0045]

[0046] Among them, ef i represents the integrated signal strength of the three-dimensional triangle i, def j represents the signal transmission power of base station j, sd j represents the signal coverage of base station j within the three-dimensional triangle i, M(i) represents the set of base stations whose signal coverage includes the three-dimensional triangle i, tg irepresents the signal attenuation coefficient of the three-dimensional triangle i, ω1 and ω2 represent weight factors, and δ represents the conversion coefficient.

[0047] It should be further explained that, in a specific implementation process, the process of obtaining the point distribution of the sensor terminal of each three-dimensional triangle includes:

[0048] According to the maximum coverage range corresponding to the sensor terminals of each three-dimensional triangle under the terrain characteristics of the three-dimensional triangle and the number of sensor terminals deployed, the comprehensive coverage rate of the sensor terminals of each three-dimensional triangle is obtained, and the comprehensive coverage rate is used as the objective function of the particle swarm algorithm to obtain the optimal deployment position of the sensor terminals within each three-dimensional triangle through the particle swarm algorithm.

[0049] It should be further explained that, in the specific implementation process, the process of obtaining the optimal layout position of the sensor terminal within each three-dimensional triangle range by using the particle swarm algorithm is as follows:

[0050] According to the maximum coverage range of the sensor terminals of each three-dimensional triangle under the terrain characteristics of the three-dimensional triangle and the number of sensor terminals deployed, the comprehensive coverage rate of the sensor terminals of each three-dimensional triangle is obtained. The comprehensive coverage rate is used as the objective function of the particle swarm algorithm. The calculation formula of the comprehensive coverage rate is:

[0051]

[0052] Among them, ed represents the comprehensive coverage rate, s represents the maximum coverage range of the sensor terminal, d represents the Euclidean distance from the sensor terminal to the geometric center of the three-dimensional triangle, and sv represents the coverage range of the three-dimensional triangle;

[0053] Determine the size of the particle swarm, randomly generate the initial position and speed for each particle (representing a deployment plan), set the parameters, and then perform the optimization process. After multiple iterations, determine the optimal solution, that is, the optimal position of the group gbest, which represents the optimal deployment position of the sensor terminal. The calculation formula of the optimization process is:

[0054] v k (n+1)=ω·v k (n)+c1·r1·(pbest k -x k (n))+c2·r2·

[0055] (gbest-x k (n));

[0056] x k (n+1)=x k (n+1)+v k (n+1);

[0057] Among them, ω represents the inertia weight; c1 and c2 represent the acceleration coefficients, which are used to weight the optimal position of the particle itself and the optimal position of the group respectively; v k (n) represents the velocity of particle k at the current iteration n; x k (n) represents the position of particle k at the current iteration n; r1 and r2 are random numbers between 0 and 1; pbest k represents the optimal position of particle k itself.

[0058] It should be further explained that, in the specific implementation process, all sensor terminals of each three-dimensional triangle are divided into a number of arrival time positioning groups, and the arrival time positioning operation is performed on the received signals of the sensor terminals of each arrival time positioning group. The process of obtaining the signal source position coordinates positioned by each arrival time positioning group in each three-dimensional triangle includes:

[0059] Select any m sensor terminals in the three-dimensional triangle and mark them as an arrival time positioning group, where m≥3, and divide all sensor terminals in the three-dimensional triangle into several arrival time positioning groups;

[0060] Obtaining a timestamp of a signal received by a sensor terminal in the arrival time positioning group, and obtaining a signal arrival time difference between two sensor terminals in the arrival time positioning group according to the timestamp;

[0061] The position coordinates of m sensor terminals in the arrival time positioning group are obtained, and multiple hyperbolic equations are constructed according to the position coordinates of the m sensor terminals in the arrival time positioning group and the signal arrival time difference between any two sensor terminals, and the signal source position coordinates are obtained according to the multiple hyperbolic equations.

[0062] It should be further explained that, in the specific implementation process, the process of constructing the hyperbolic equation and obtaining the signal source position coordinates includes:

[0063] Construct the hyperbolic equation: For any two sensor terminals R in the arrival time positioning group e (x e ,y e , z e ) and R v (x v ,y v , z v ), the signal source position coordinates P(x, y, z) will be located on the hyperbola:

[0064]

[0065] Among them, Δt ev is the sensor terminal R e and Rv The signal arrival time difference between them, c is the speed of light;

[0066] Multiple hypercurve intersections: Since the present invention uses data from three or more receivers, multiple hyperbola equations are constructed, and the signal source position coordinates are the intersections of multiple hyperbola equations.

[0067] It should be further explained that, in the specific implementation process, the signal source position coordinates located by each arrival time positioning group in each three-dimensional triangle are compared, and it is determined whether to perform the frequency arrival time positioning operation on the arrival time positioning group according to the comparison result. The process of obtaining the accurate signal source position coordinates includes:

[0068] Compare the signal source position coordinates located by each arrival time positioning group in the three-dimensional triangle, obtain the signal source positioning deviation value between each arrival time positioning group, compare the signal source positioning deviation value with the preset deviation value threshold, if there is no signal source positioning deviation value greater than the deviation value threshold, perform mean processing on the signal source position coordinates located by each arrival time positioning group, obtain the mean signal source position coordinates of the three-dimensional triangle, and mark the mean signal source position coordinates as the precise signal source position coordinates;

[0069] If there is a signal source positioning deviation value greater than the deviation value threshold, two groups of arrival time positioning groups corresponding to the signal source positioning deviation value are obtained, and the two groups of arrival time positioning groups are marked as abnormal arrival time positioning groups. Frequency arrival time positioning operation is performed on the abnormal arrival time positioning groups to obtain precise signal source position coordinates.

[0070] It should be further explained that, in the specific implementation process, the process of performing frequency arrival time positioning operation on the abnormal arrival time positioning group and obtaining the precise signal source position coordinates includes:

[0071] The window function length of each sensor terminal in the abnormal arrival time positioning group is obtained, and the signal received by each sensor terminal is Fourier transformed according to the window function length of each sensor terminal in the abnormal arrival time positioning group to obtain a signal spectrum diagram, and the frequency position, amplitude and phase of each peak in the signal spectrum diagram are extracted. The frequency position, amplitude and phase of each peak in the signal spectrum diagram are subjected to multipath separation analysis by using the ESPRIT algorithm to separate the received signal of each sensor terminal into a direct path signal and a reflected path signal. Since using the ESPRIT algorithm to separate the received signal of each sensor terminal into a direct path signal and a reflected path signal is a technical means well known to those skilled in the art, the specific steps are not repeated here. The arrival time positioning operation is re-performed on the direct path signal received by each sensor terminal to obtain the precise signal source position coordinates.

[0072] It should be further explained that, in the specific implementation process, the process of obtaining the window function length of each sensor terminal in the abnormal arrival time positioning group includes:

[0073] The signal source position coordinates located by each arrival time positioning group in the three-dimensional triangle are averaged to obtain the signal source position mean coordinates of the three-dimensional triangle, and the Euclidean distance between each sensor terminal in the abnormal arrival time positioning group and the signal source position mean coordinates is obtained according to the position coordinates of each sensor terminal in the abnormal arrival time positioning group and the signal source position mean coordinates, and a window function length comparison table is preset at the same time, the window function comparison table includes window function lengths corresponding to different terrain features and Euclidean distances, and the window function lengths of each sensor terminal in the abnormal arrival time positioning group are obtained according to the Euclidean distance between each sensor terminal in the abnormal arrival time positioning group and the signal source position mean coordinates, the terrain features of the three-dimensional triangle and the window function length comparison table;

[0074] It should be further explained that, in the specific implementation process, the signal received by each sensor terminal is subjected to Fourier transform, and the process of obtaining the signal spectrum diagram includes: presetting the frame parameters, the window function type and the initial window function length, the frame parameters include the average frame length and the average frame shift, dividing the signal into several frames according to the frame parameters, and windowing each frame according to the window function, and then converting the signal of each frame into a frequency signal through Fourier transform.

[0075] The above embodiments are only used to illustrate the technical method of the present invention rather than to limit it. Although the present invention has been described in detail with reference to the preferred embodiments, those skilled in the art should understand that the technical method of the present invention may be modified or replaced by equivalents without departing from the spirit and scope of the technical method of the present invention.

Claims

1. A signal source positioning method based on multi-source sensors, characterized in that: The following steps are involved: Step s1: construct a 3D triangulated network model of the target service area based on the GIS geographic data of the target service area, and obtain the number of sensor terminals and point distribution of each 3D triangle based on the terrain features of each 3D triangle in the 3D triangulated network model and the base station information in the target service area; Step s2: Divide all sensor terminals of each three-dimensional triangle into a number of arrival time positioning groups, perform arrival time positioning operations on the received signals of the sensor terminals of each arrival time positioning group, and obtain the signal source position coordinates positioned by each arrival time positioning group in each three-dimensional triangle; Step s3: Compare the signal source position coordinates located by each arrival time positioning group in each three-dimensional triangle, and determine whether to perform frequency arrival time positioning operation on the arrival time positioning group according to the comparison result to obtain accurate signal source position coordinates.

2. The signal source localization method based on multi-source sensors according to claim 1, characterized in that: The process of constructing a 3D triangulated network model of the target service area based on the GIS geographic data of the target service area includes: The GIS geographic data and digital elevation data in the target service area are obtained through GIS means, a plane triangulated network model of the target service area is constructed according to the GIS geographic data, terrain features are given to each triangle in the plane triangulated network model, the elevations on the vertices of each triangle in the plane triangulated network model are set according to the digital elevation data, a three-dimensional triangulated network model of the target service area is obtained, and a three-dimensional coordinate system is constructed based on the three-dimensional triangulated network model.

3. The signal source localization method based on multi-source sensors according to claim 2 is characterized in that: According to the terrain features of each three-dimensional triangle in the three-dimensional triangulated network model and the base station information in the target service area, the process of obtaining the number of sensor terminals deployed in each three-dimensional triangle includes: A geographic signal interference comparison table is preset, and the geographic signal interference comparison table includes signal attenuation coefficients corresponding to sensor terminals under different terrain feature conditions. The signal attenuation coefficient of each three-dimensional triangle is obtained according to the terrain features of each three-dimensional triangle in the three-dimensional triangulated network model of the target service area and the geographic signal interference comparison table, and the location characteristics, signal transmission power and signal coverage range of each base station in the target service area are obtained. According to the location characteristics of each base station and the location characteristics of each three-dimensional triangle, the comprehensive signal strength of each three-dimensional triangle is obtained, and the importance coefficient of each three-dimensional triangle is obtained according to the signal attenuation coefficient and the comprehensive signal strength of each three-dimensional triangle. According to the importance coefficient, the number of sensor terminals deployed in each three-dimensional triangle is obtained.

4. The signal source localization method based on multi-source sensors according to claim 3 is characterized in that: The process of obtaining the point distribution of the sensor terminal of each three-dimensional triangle includes: According to the maximum coverage range corresponding to the sensor terminals of each three-dimensional triangle under the terrain characteristics of the three-dimensional triangle and the number of sensor terminals deployed, the comprehensive coverage rate of the sensor terminals of each three-dimensional triangle is obtained, and the comprehensive coverage rate is used as the objective function of the particle swarm algorithm to obtain the optimal deployment position of the sensor terminals within each three-dimensional triangle through the particle swarm algorithm.

5. The signal source localization method based on multi-source sensors according to claim 4 is characterized in that: The process of dividing all sensor terminals of each three-dimensional triangle into a plurality of arrival time positioning groups, performing arrival time positioning operations on the received signals of the sensor terminals of each arrival time positioning group, and obtaining the signal source position coordinates of each arrival time positioning group in each three-dimensional triangle includes: Select any m sensor terminals in the three-dimensional triangle and mark them as an arrival time positioning group, where m≥3, and divide all sensor terminals in the three-dimensional triangle into several arrival time positioning groups; Obtaining a timestamp of a signal received by a sensor terminal in the arrival time positioning group, and obtaining a signal arrival time difference between two sensor terminals in the arrival time positioning group according to the timestamp; The position coordinates of m sensor terminals in the arrival time positioning group are obtained, and multiple hyperbolic equations are constructed according to the position coordinates of the m sensor terminals in the arrival time positioning group and the signal arrival time difference between any two sensor terminals, and the signal source position coordinates are obtained according to the multiple hyperbolic equations.

6. The signal source localization method based on multi-source sensors according to claim 5, characterized in that: The signal source position coordinates located by each arrival time positioning group in each three-dimensional triangle are compared, and according to the comparison result, it is determined whether to perform the frequency arrival time positioning operation on the arrival time positioning group. The process of obtaining the accurate signal source position coordinates includes: Compare the signal source position coordinates located by each arrival time positioning group in the three-dimensional triangle, obtain the signal source positioning deviation value between each arrival time positioning group, compare the signal source positioning deviation value with the preset deviation value threshold, if there is no signal source positioning deviation value greater than the deviation value threshold, perform mean processing on the signal source position coordinates located by each arrival time positioning group, obtain the mean signal source position coordinates of the three-dimensional triangle, and mark the mean signal source position coordinates as the precise signal source position coordinates; If there is a signal source positioning deviation value greater than the deviation value threshold, two groups of arrival time positioning groups corresponding to the signal source positioning deviation value are obtained, and the two groups of arrival time positioning groups are marked as abnormal arrival time positioning groups. Frequency arrival time positioning operation is performed on the abnormal arrival time positioning groups to obtain precise signal source position coordinates.

7. The signal source localization method based on multi-source sensors according to claim 6, characterized in that: The process of performing frequency arrival time location operation on the abnormal arrival time location group and obtaining accurate signal source position coordinates includes: The window function length of each sensor terminal in the abnormal arrival time positioning group is obtained, and the signal received by each sensor terminal is Fourier transformed according to the window function length of each sensor terminal in the abnormal arrival time positioning group to obtain a signal spectrum diagram, and the frequency position, amplitude and phase of each peak in the signal spectrum diagram are extracted. The frequency position, amplitude and phase of each peak in the signal spectrum diagram are analyzed by multipath separation using the ESPRIT algorithm, and the received signal of each sensor terminal is separated into a direct path signal and a reflected path signal. The arrival time positioning operation is performed again on the direct path signal received by each sensor terminal to obtain the precise signal source position coordinates.

8. The signal source localization method based on multi-source sensors according to claim 7, characterized in that: The process of obtaining the window function length of each sensor terminal in the abnormal arrival time location group includes: The signal source position coordinates located by each arrival time positioning group in the three-dimensional triangle are averaged to obtain the signal source position mean coordinates of the three-dimensional triangle. According to the position coordinates of each sensor terminal in the abnormal arrival time positioning group and the signal source position mean coordinates, the Euclidean distance between each sensor terminal in the abnormal arrival time positioning group and the signal source position mean coordinates is obtained. Meanwhile, a window function length comparison table is preset, wherein the window function comparison table includes window function lengths corresponding to different terrain features and Euclidean distances. According to the Euclidean distance between each sensor terminal in the abnormal arrival time positioning group and the signal source position mean coordinates, the terrain features of the three-dimensional triangle and the window function length comparison table, the window function length of each sensor terminal in the abnormal arrival time positioning group is obtained.

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