Miniaturized radio signal visual monitoring, positioning and identifying system and method

Abstract

The invention provides a miniaturized visual monitoring, positioning and identifying system for radio signals, and belongs to the technical field of radio monitoring. The miniaturized visual monitoring, positioning and identifying system for the radio signals comprises a plurality of monitoring stations and a server, and the server is internally provided with the following method: acquiring historical monitoring records of each monitoring station in a preset time period; analyzing and determining the original number of historical abnormal signal sources in each historical monitoring direction and the original orientation of each historical abnormal signal source according to the historical monitoring record; according to the original orientation, the original number and the historical monitoring record, analyzing orientation change data and number change data of each historical monitoring direction and each historical abnormal signal source; calculating positioning priority data of each historical monitoring direction according to the azimuth change data and the quantity change data; by adopting the method, the abnormal signal source can be positioned more accurately.

Description

Technical Field

[0001] The present application relates to the technical field of radio monitoring, and in particular to a miniaturized radio signal visualization monitoring, positioning and identification system and method. Background Art

[0002] At present, radio monitoring stations are generally used to monitor radio signals. Radio monitoring stations can be used to monitor, locate and identify abnormal radio signal sources in any direction. When monitoring in any direction, radio monitoring stations will simultaneously record the corresponding monitoring direction and monitoring records. Since radio monitoring stations of the same specifications can achieve the same monitoring coverage in the same monitoring direction, it is possible to determine whether there is an intersection in the monitoring coverage of any two radio monitoring stations through the monitoring directions recorded in the records. If you want to monitor, locate and identify abnormal radio signal sources in another direction, you need to control the rotation direction of the monitoring equipment. Generally speaking, abnormal signal sources change their directions frequently, so it is difficult to capture abnormal signal sources through a single monitoring station. If multiple abnormal signal sources appear, multiple radio monitoring stations are required to work together to capture the abnormal signal sources. Therefore, it is very important to allocate radio monitoring stations for abnormal signal sources. Summary of the invention

[0003] The present application provides a miniaturized radio signal visual monitoring, positioning and identification system and method, which can capture abnormal signal sources by allocating multiple radio monitoring stations, which is conducive to the accurate positioning of abnormal signal sources.

[0004] In a first aspect, the present application provides a miniaturized radio signal visualization monitoring, positioning and identification system. The system includes multiple monitoring stations and a server, and the server is configured with the following method:

[0005] Obtaining historical monitoring records of each monitoring station within a preset time period; the historical monitoring records include azimuth data and quantity data of historical abnormal signal sources corresponding to historical monitoring directions;

[0006] Determine the original number of historical abnormal signal sources in each historical monitoring direction and the original position of each historical abnormal signal source according to the historical monitoring record analysis; the original position is the location data of each historical abnormal signal source appearing for the first time within a preset time period; the original number is the number data of abnormal signal sources captured by the monitoring station when performing monitoring work for the first time in any historical monitoring direction within the preset time period;

[0007] Analyze the azimuth change data and quantity change data of each historical monitoring direction and each historical abnormal signal source according to the original azimuth, the original quantity and the historical monitoring records; the azimuth change data is the azimuth change times data of each historical abnormal signal source; the quantity change data includes quantity increase data and quantity decrease data;

[0008] The positioning priority data of each historical monitoring direction is calculated according to the azimuth change data and the quantity change data; the positioning priority data represents the coordination priority degree of each historical monitoring direction of each monitoring station.

[0009] Furthermore, the server is further configured to, after obtaining the positioning priority data, further include:

[0010] Determine the monitoring station with the highest positioning priority data as the first monitoring station;

[0011] Select two monitoring stations whose positioning priority data is not greater than a preset priority threshold as auxiliary monitoring stations;

[0012] Determine a target monitoring task based on the first monitoring station; the target monitoring task is to perform monitoring work on the historical monitoring direction with the highest positioning priority data according to the first monitoring station;

[0013] The target monitoring task is assigned to two auxiliary monitoring stations.

[0014] Furthermore, the server is further configured such that the calculation of the positioning priority data of each historical monitoring direction according to the position change data and the quantity change data includes:

[0015] Calculate the basic impact data based on the raw quantities mentioned;

[0016] Calculating the orientation impact data according to the orientation change data;

[0017] Calculate quantity impact data based on the quantity change data;

[0018] The positioning priority data of each historical monitoring direction is calculated according to the basic influence data, the azimuth influence data and the quantity influence data.

[0019] Furthermore, the server is further configured such that the method for calculating the positioning priority data includes:

[0020] S=B×K1+P×K2+M×K3

[0021] Wherein, S is the positioning priority data, B is the basic influence data, P is the azimuth influence data, and M is the quantity influence data; K1, K2, and K3 are the first preset weight, the second preset weight, and the third preset weight, respectively.

[0022] Furthermore, the server is further configured as K1+K2+K3=1.

[0023] In a second aspect, the present application provides a miniaturized radio signal visualization monitoring, positioning and identification method, the method comprising:

[0024] Obtaining historical monitoring records of each monitoring station within a preset time period; the historical monitoring records include azimuth data and quantity data of historical abnormal signal sources corresponding to historical monitoring directions;

[0025] Determine the original number of historical abnormal signal sources in each historical monitoring direction and the original position of each historical abnormal signal source according to the historical monitoring record analysis; the original position is the location data of each historical abnormal signal source appearing for the first time within a preset time period; the original number is the number data of abnormal signal sources captured by the monitoring station when performing monitoring work for the first time in any historical monitoring direction within the preset time period;

[0026] Analyze the azimuth change data and quantity change data of each historical monitoring direction and each historical abnormal signal source according to the original azimuth, the original quantity and the historical monitoring records; the azimuth change data is the azimuth change times data of each historical abnormal signal source; the quantity change data includes quantity increase data and quantity decrease data;

[0027] The positioning priority data of each historical monitoring direction is calculated according to the azimuth change data and the quantity change data; the positioning priority data represents the coordination priority degree of each historical monitoring direction of each monitoring station.

[0028] Further, after obtaining the positioning priority data, the method further includes:

[0029] Determine the monitoring station with the highest positioning priority data as the first monitoring station;

[0030] Select two monitoring stations whose positioning priority data is not greater than a preset priority threshold as auxiliary monitoring stations;

[0031] Determine a target monitoring task based on the first monitoring station; the target monitoring task is to perform monitoring work on the historical monitoring direction with the highest positioning priority data according to the first monitoring station;

[0032] The target monitoring task is assigned to two auxiliary monitoring stations.

[0033] Further, the calculating of the positioning priority data of each historical monitoring direction according to the position change data and the quantity change data includes:

[0034] Calculate the basic impact data based on the raw quantities mentioned;

[0035] Calculating the orientation impact data according to the orientation change data;

[0036] Calculate quantity impact data based on the quantity change data;

[0037] The positioning priority data of each historical monitoring direction is calculated according to the basic influence data, the azimuth influence data and the quantity influence data.

[0038] Furthermore, the method for calculating the positioning priority data includes:

[0039] S=B×K1+P×K2+M×K3

[0040] Wherein, S is the positioning priority data, B is the basic influence data, P is the azimuth influence data, and M is the quantity influence data; K1, K2, and K3 are the first preset weight, the second preset weight, and the third preset weight, respectively.

[0041] Further, K1+K2+K3=1.

[0042] It should be understood that the contents described in the Summary of the Invention are not intended to limit the key or important features of the embodiments of the present application, nor are they intended to limit the scope of the present application. Other features of the present application will become easily understood through the following description. BRIEF DESCRIPTION OF THE DRAWINGS

[0043] The above and other features, advantages and aspects of the embodiments of the present application will become more apparent with reference to the following detailed description in conjunction with the accompanying drawings. In the accompanying drawings, the same or similar reference numerals represent the same or similar elements, wherein:

[0044] Figure 1 A flow chart of a server execution method in a miniaturized radio signal visual monitoring, positioning and identification system in an embodiment of the present application is shown. DETAILED DESCRIPTION

[0045] In order to make the purpose, technical solution and advantages of the embodiments of the present application clearer, the technical solution in the embodiments of the present application will be clearly and completely described below 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 ordinary technicians in this field without creative work are within the scope of protection of this application.

[0046] In addition, the term "and / or" in this article is only a description of the association relationship between the associated objects, indicating that there can be three relationships. For example, A and / or B can represent: A exists alone, A and B exist at the same time, and B exists alone. In addition, the character " / " in this article generally indicates that the associated objects before and after are in an "or" relationship.

[0047] The present application provides a miniaturized radio signal visual monitoring, positioning and identification system and method, which can more accurately locate the abnormal signal source.

[0048] refer to Figure 1 In the first aspect, the present application provides a miniaturized radio signal visualization monitoring, positioning and identification system. The system includes a plurality of monitoring stations and a server, wherein the server is configured with the following method: obtaining the historical monitoring records of each monitoring station within a preset time period; the historical monitoring records include the azimuth data and quantity data of the corresponding historical abnormal signal sources under the historical monitoring direction; analyzing and determining the original number of historical abnormal signal sources in each historical monitoring direction and the original azimuth of each historical abnormal signal source according to the historical monitoring records; the original azimuth is the location data of each historical abnormal signal source appearing for the first time within the preset time period; the original quantity is the quantity data of the abnormal signal source captured by the monitoring station when performing the monitoring work for the first time in any historical monitoring direction within the preset time period; analyzing the azimuth change data and quantity change data of each historical monitoring direction and each historical abnormal signal source according to the original azimuth, the original quantity and the historical monitoring records; the azimuth change data is the azimuth change times data of each historical abnormal signal source; the quantity change data includes quantity increase data and quantity decrease data; calculating the positioning priority data of each historical monitoring direction according to the azimuth change data and quantity change data; the positioning priority data represents the coordination priority degree of each historical monitoring direction of each monitoring station.

[0049] In the system of this solution, the specifications of all monitoring stations are consistent, and any two monitoring stations can cooperate to achieve the intersection of the monitoring coverage range in one monitoring direction, and any three monitoring stations can cooperate to achieve the precise positioning of abnormal signal sources within the range where the monitoring coverage ranges of the three monitoring stations can intersect.

[0050] It can be understood that the monitoring direction here refers to the monitoring equipment of the monitoring station. In which direction the monitoring equipment faces, it can receive abnormal radio signals within a certain distance and range in that direction, thereby capturing the source of the abnormal signal. Therefore, the monitoring direction mentioned in this scheme is a monitoring direction in the conventional sense that conforms to the performance and working nature of the monitoring equipment; the monitoring direction recorded in the historical monitoring records is recorded based on the direction of the monitoring equipment. In this way, the monitoring direction in the historical monitoring records of each monitoring station can be accurately positioned; for example, the monitoring equipment of monitoring station A recorded in the historical monitoring records faces the southeast direction, and the monitoring equipment of monitoring station B faces the northwest direction, etc.

[0051] It is understandable that in actual monitoring work, the monitoring station generally adjusts the direction of the monitoring equipment periodically. Therefore, in the historical monitoring records, there will be a monitoring station that monitors multiple historical monitoring directions, thereby obtaining the corresponding direction and number of historical abnormal signal sources monitored; the direction data of the historical abnormal signal source here generally refers to the direction and approximate distance of the signal source, such as more than 200 meters in the southeast direction. Because one monitoring station can only monitor the direction and approximate distance of the signal source, it is impossible to accurately locate the specific position of the signal source. Therefore, three monitoring stations are required to cooperate with each other, because three straight lines can determine an accurate point in space. Therefore, in this scheme, through the analysis of the historical monitoring records of each monitoring station, the situation of the historical abnormal signal source in the historical monitoring direction corresponding to each monitoring station is determined, thereby determining the historical abnormal signal source with higher priority that needs to be urgently and accurately located.

[0052] It is understandable that the historical monitoring direction mentioned in the solution of the present application is bound to each monitoring station, such as the southeast direction of monitoring station A. Therefore, after obtaining the historical monitoring records, it is necessary to conduct a specific analysis of the historical monitoring records.

[0053] In the scheme of the present application, historical monitoring records within a preset time period are analyzed, and the preset time period here generally takes the current time node as the end point of the time period, and historical monitoring records within the preset time length close to the current time node are selected; since the abnormal signal source will frequently change its direction, when the abnormal signal source is detected, even if a processing strategy is taken in time, it is difficult to ensure that the abnormal signal source can be captured in time, so it is necessary to continuously monitor the abnormal signal source. Therefore, there are multiple abnormal signal sources that are not captured within the preset time length. By analyzing the number and direction changes of the abnormal signal sources, the monitoring priority of the abnormal signal source in the monitoring direction can be determined.

[0054] In actual monitoring work, after an abnormal signal source is detected, it will be marked so that it can be identified when it appears again. Therefore, the original number of historical abnormal signal sources in each historical monitoring direction and the original direction of each historical abnormal signal source can be determined through historical monitoring records.

[0055] After obtaining the original quantity and original position, the quantity change data and position change data can be determined.

[0056] Specifically, the analysis method of the quantity change data here is, for any historical monitoring direction in the historical monitoring records, the quantity difference is obtained by subtracting the smallest quantity recorded in the historical monitoring record in the historical monitoring direction; then the basic difference is obtained by subtracting the original quantity from the last recorded quantity within the preset time period; the quantity change data is equal to the basic difference*quantity difference; it can be understood that for the number of abnormal signal sources appearing in the historical monitoring direction, if the last recorded quantity is less than the original quantity, it means that an abnormal signal source has been lost, otherwise it means that the abnormal signal source has increased; if the abnormal signal source is lost, the priority in the historical monitoring direction will be reduced; if the abnormal signal source increases, the priority in the historical monitoring direction will increase; specifically, the calculation method of the quantity change data is, m=d1×d2; where m is the quantity change data, d1 is the basic difference, and d2 is the quantity difference.

[0057] The azimuth change data here refers to the number of azimuth changes of each historical abnormal signal source. Specifically, assume that in the historical monitoring direction a of monitoring station A, n historical abnormal signal sources appear within a preset time period. The number of azimuth changes of each historical abnormal signal source is c. i , then the orientation change data Where p is the azimuth change data.

[0058] In an embodiment of the present application, after obtaining the azimuth change data and the quantity change data, the positioning priority data can be calculated; specifically, calculating the positioning priority data of each historical monitoring direction based on the azimuth change data and the quantity change data specifically includes calculating basic influence data based on the original quantity; calculating azimuth influence data based on the azimuth change data; calculating quantity influence data based on the quantity change data; calculating the positioning priority data of each historical monitoring direction based on the basic influence data, the azimuth influence data and the quantity influence data.

[0059] Specifically, the calculation method of basic influence data includes, B=o×k1+b1; wherein B is the basic influence data, o is the original quantity, k1 is the preset first conversion coefficient, and b1 is the preset first correction coefficient; the calculation method of azimuth influence data includes, P=p×k2+b2; wherein P is the azimuth influence data, p is the azimuth change data, k2 is the preset second conversion coefficient, and b2 is the preset second correction coefficient; the calculation method of quantity influence data includes, M=m×k3+b3; wherein, M is the quantity influence data, m is the quantity change data, k3 is the preset third conversion coefficient, and b3 is the preset third correction coefficient.

[0060] Furthermore, the calculation method of the positioning priority data includes:

[0061] S=B×K1+P×K2+M×K3

[0062] In the formula, S is the positioning priority data, B is the basic influence data, P is the azimuth influence data, and M is the quantity influence data; K1, K2, and K3 are the first preset weight, the second preset weight, and the third preset weight, respectively; wherein, K1+K2+K3=1.

[0063] In the scheme of the present application, after obtaining the positioning priority data, the monitoring station with the highest positioning priority data is determined as the first monitoring station; two monitoring stations whose positioning priority data is not greater than a preset priority threshold are selected as auxiliary monitoring stations; the target monitoring task is determined based on the first monitoring station; the target monitoring task is to perform monitoring work on the historical monitoring direction with the highest positioning priority data according to the first monitoring station; and the target monitoring task is allocated to two auxiliary monitoring stations.

[0064] It can be understood that each historical monitoring direction mentioned above is bound to the monitoring station. Therefore, after calculating the positioning priority data of each historical monitoring direction, the auxiliary monitoring station uses the historical monitoring direction of the corresponding monitoring station as a benchmark. When adjusting the monitoring direction, the auxiliary monitoring station needs to consider the relative position of the auxiliary monitoring station and the first monitoring station.

[0065] It can be understood that the method running in the server in the scheme of the present application is actually a machine learning model, which continuously calculates the positioning priority data and continuously trains the corresponding parameters, such as the first preset weight, the second preset weight, the third preset weight, the preset first conversion coefficient, the preset first correction coefficient, the preset second conversion coefficient, the preset second correction coefficient, the preset third conversion coefficient, the preset third correction coefficient, etc.; by continuously training the above parameters, the calculation result of the positioning priority data is more accurate, thereby achieving a more reasonable and precise allocation of the monitoring work of the monitoring stations and improving the accuracy of monitoring of abnormal signal sources.

[0066] It should be noted that, for the aforementioned method embodiments, for the sake of simplicity of description, they are all expressed as a series of action combinations, but those skilled in the art should be aware that the present application is not limited by the described order of actions, because according to the embodiments of the present application, certain steps can be performed in other orders or simultaneously. Secondly, those skilled in the art should also be aware that the embodiments described in the specification are all optional embodiments, and the actions and modules involved are not necessarily required by the present application.

[0067] In the second aspect, the present application provides a miniaturized radio signal visualization monitoring, positioning and identification method. The method is applied to a server; the method specifically includes obtaining the historical monitoring records of each monitoring station within a preset time period; the historical monitoring records include the azimuth data and quantity data of the corresponding historical abnormal signal sources under the historical monitoring direction; according to the historical monitoring records, the original number of historical abnormal signal sources in each historical monitoring direction and the original azimuth of each historical abnormal signal source are determined; the original azimuth is the location data of the first appearance of each historical abnormal signal source within the preset time period; the original quantity is the quantity data of abnormal signal sources captured by the monitoring station when performing monitoring work in any historical monitoring direction for the first time within the preset time period; according to the original azimuth, the original quantity and the historical monitoring records, the azimuth change data and quantity change data of each historical monitoring direction and each historical abnormal signal source are analyzed; the azimuth change data is the azimuth change times data of each historical abnormal signal source; the quantity change data includes quantity increase data and quantity decrease data; according to the azimuth change data and quantity change data, the positioning priority data of each historical monitoring direction is calculated; the positioning priority data represents the coordination priority degree of each historical monitoring direction of each monitoring station.

[0068] Furthermore, after obtaining the positioning priority data, it also includes: determining the monitoring station with the highest positioning priority data as the first monitoring station; selecting two monitoring stations whose positioning priority data is not greater than a preset priority threshold as auxiliary monitoring stations; determining the target monitoring task based on the first monitoring station; the target monitoring task is to perform monitoring work on the historical monitoring direction with the highest positioning priority data according to the first monitoring station; and allocating the target monitoring task to two auxiliary monitoring stations.

[0069] Furthermore, the calculation of the positioning priority data of each historical monitoring direction based on the azimuth change data and the quantity change data includes: calculating basic influence data based on the original quantity; calculating azimuth influence data based on the azimuth change data; calculating quantity influence data based on the quantity change data; calculating the positioning priority data of each historical monitoring direction based on the basic influence data, the azimuth influence data and the quantity influence data.

[0070] Furthermore, the method for calculating the positioning priority data includes:

[0071] S=B×K1+P×K2+M×K3

[0072] In the formula, S is the positioning priority data, B is the basic influence data, P is the azimuth influence data, and M is the quantity influence data; K1, K2, and K3 are the first preset weight, the second preset weight, and the third preset weight, respectively; wherein, K1+K2+K3=1.

[0073] Those skilled in the art can clearly understand that, for the convenience and brevity of description, the specific working process of the described device can refer to the corresponding process in the aforementioned method embodiment, and will not be repeated here.

[0074] The above description is only a preferred embodiment of the present application and an explanation of the technical principles used. Those skilled in the art should understand that the scope of disclosure involved in the present application is not limited to the technical solution formed by a specific combination of the above technical features, but should also cover other technical solutions formed by any combination of the above technical features or their equivalent features without departing from the aforementioned disclosed concept. For example, the above features are replaced with the technical features with similar functions disclosed in this application (but not limited to) by each other to form a technical solution.

Claims

1. A miniaturized radio signal visualization monitoring, positioning and identification system, comprising a plurality of monitoring stations and a server, characterized in that: The server is configured with the following methods: Obtaining historical monitoring records of each monitoring station within a preset time period; the historical monitoring records include azimuth data and quantity data of historical abnormal signal sources corresponding to historical monitoring directions; Determine the original number of historical abnormal signal sources in each historical monitoring direction and the original position of each historical abnormal signal source according to the historical monitoring records; The original position is the location data of each historical abnormal signal source appearing for the first time within a preset time period; The original quantity is the number of abnormal signal sources captured by the monitoring station when performing monitoring work for the first time in any historical monitoring direction within a preset time period; Analyze the azimuth change data and quantity change data of each historical monitoring direction and each historical abnormal signal source according to the original azimuth, the original quantity and the historical monitoring records; the azimuth change data is the azimuth change times data of each historical abnormal signal source; the quantity change data includes quantity increase data and quantity decrease data; The positioning priority data of each historical monitoring direction is calculated according to the azimuth change data and the quantity change data; the positioning priority data represents the coordination priority degree of each historical monitoring direction of each monitoring station.

2. The miniaturized radio signal visual monitoring, positioning and identification system according to claim 1 is characterized in that: The server is further configured to, after obtaining the positioning priority data, further include: Determine the monitoring station with the highest positioning priority data as the first monitoring station; Select two monitoring stations whose positioning priority data is not greater than a preset priority threshold as auxiliary monitoring stations; Determine a target monitoring task based on the first monitoring station; the target monitoring task is to perform monitoring work on the historical monitoring direction with the highest positioning priority data according to the first monitoring station; The target monitoring task is assigned to two auxiliary monitoring stations.

3. The miniaturized radio signal visual monitoring, positioning and identification system according to claim 2 is characterized in that: The server is further configured to calculate the positioning priority data of each historical monitoring direction according to the position change data and the quantity change data, including: Calculate the basic impact data based on the raw quantities mentioned; Calculating the orientation impact data according to the orientation change data; Calculate quantity impact data based on the quantity change data; The positioning priority data of each historical monitoring direction is calculated according to the basic influence data, the azimuth influence data and the quantity influence data.

4. The miniaturized radio signal visual monitoring, positioning and identification system according to claim 3 is characterized in that: The server is further configured such that the method for calculating the positioning priority data includes: S=B×K1+P×K2+M×K3 Wherein, S is the positioning priority data, B is the basic influence data, P is the azimuth influence data, and M is the quantity influence data; K1, K2, and K3 are the first preset weight, the second preset weight, and the third preset weight, respectively.

5. The miniaturized radio signal visual monitoring, positioning and identification system according to claim 4 is characterized in that: The server is further configured as follows: K1+K2+K3=1.

6. A miniaturized radio signal visual monitoring, positioning and identification method, applied to the server described in claims 1-5, characterized in that: include: Obtain historical monitoring records of each monitoring station within a preset time period; The historical monitoring records include the azimuth data and quantity data of the historical abnormal signal sources corresponding to the historical monitoring directions; Determine the original number of historical abnormal signal sources in each historical monitoring direction and the original position of each historical abnormal signal source according to the historical monitoring records; The original position is the location data of each historical abnormal signal source appearing for the first time within a preset time period; The original quantity is the number of abnormal signal sources captured by the monitoring station when performing monitoring work for the first time in any historical monitoring direction within a preset time period; Analyze the azimuth change data and quantity change data of each historical monitoring direction and each historical abnormal signal source according to the original azimuth, the original quantity and the historical monitoring records; the azimuth change data is the azimuth change times data of each historical abnormal signal source; the quantity change data includes quantity increase data and quantity decrease data; The positioning priority data of each historical monitoring direction is calculated according to the azimuth change data and the quantity change data; the positioning priority data represents the coordination priority degree of each historical monitoring direction of each monitoring station.

7. The miniaturized radio signal visual monitoring, positioning and identification method according to claim 6 is characterized in that: After obtaining the positioning priority data, the method further includes: Determine the monitoring station with the highest positioning priority data as the first monitoring station; Select two monitoring stations whose positioning priority data is not greater than a preset priority threshold as auxiliary monitoring stations; Determine a target monitoring task based on the first monitoring station; the target monitoring task is to perform monitoring work on the historical monitoring direction with the highest positioning priority data according to the first monitoring station; The target monitoring task is assigned to two auxiliary monitoring stations.

8. The miniaturized radio signal visual monitoring, positioning and identification method according to claim 7 is characterized in that: The calculating of the positioning priority data of each historical monitoring direction according to the azimuth change data and the quantity change data comprises: Calculate the basic impact data based on the raw quantities mentioned; Calculating the orientation impact data according to the orientation change data; Calculate quantity impact data based on the quantity change data; The positioning priority data of each historical monitoring direction is calculated according to the basic influence data, the azimuth influence data and the quantity influence data.

9. The miniaturized radio signal visual monitoring, positioning and identification method according to claim 8 is characterized in that: The calculation method of the positioning priority data includes: S=B×K1+P×K2+M×K3 Wherein, S is the positioning priority data, B is the basic influence data, P is the azimuth influence data, and M is the quantity influence data; K1, K2, and K3 are the first preset weight, the second preset weight, and the third preset weight, respectively.

10. The miniaturized radio signal visual monitoring, positioning and identification method according to claim 9 is characterized in that: K1+K2+K3=1.

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