Electromagnetic spectrum map construction method, device and system for realizing EMI blind source separation

Abstract

The invention provides an electromagnetic spectrum map construction method, device and system for realizing EMI blind source separation. Through site environment calibration, signal acquisition, signal processing, blind source separation and electromagnetic spectrum map imaging, a plurality of radiation sources in a VHF frequency band of an EMC experiment electric field radiation emission project are separated and positioned by using an underdetermined blind source separation method, and an electromagnetic spectrum map is generated. The electromagnetic compatibility testing device has the advantages of being high in positioning accuracy, capable of achieving multi-radiation-source separation and enabling electromagnetic compatibility testing results to be more visual.

Description

Technical Field

[0001] The present invention relates to the field of electromagnetic compatibility, and in particular to a method, device and system for constructing an electromagnetic spectrum map for realizing EMI blind source separation. Background Art

[0002] In the field of aviation and aerospace, electromagnetic compatibility (EMC) performance is one of the important evaluation criteria for the quality and reliability of satellites, missiles, and launch vehicles. The extremely small sample characteristics of satellite products determine that their reliability can only be verified and improved through ground tests. Due to the restrictions on the size of the spacecraft by the launch vehicle, its various systems and electronic equipment such as sensor payloads are tightly integrated. As one of the components of spacecraft reliability design, electromagnetic compatibility plays an important role in ensuring the safety of spacecraft on orbit and the high reliability of missions. Electric field radiation emission is a test item in the electromagnetic compatibility experiment of spacecraft. In aerospace stand-alone products, electromagnetic waves often enter electronic equipment through front-door coupling or back-door coupling, causing signal frame loss, telemetry lock loss, and even component damage. In electromagnetic susceptibility (EMS) protection, the probability of EUT sensitivity caused by back-door coupling is higher. For example, when a communication data link product is subject to electromagnetic interference, its data link is blocked or even interrupted, making it difficult to execute mission instructions, and in severe cases, it may even cause the entire satellite to fail.

[0003] Underdetermined Blind Source Separation (UBSS) is to separate the source signal based on the time domain and frequency domain characteristics of the received signal when the parameters and number of source signals are unknown. Blind source separation is divided into overdetermined, positively determined, and underdetermined according to the number of source signals. Under the underdetermined condition, the number of source signals is greater than the number of observed signals. Therefore, the separation and positioning of multiple radiation sources is actually a blind source separation problem.

[0004] Passive signal positioning uses single or distributed antennas, spectrum analyzers and other equipment to receive radiation source signals and analyze the signal's time domain and frequency domain information, thereby effectively locating the radiation source's position, size, distribution and other information. Common passive positioning methods include those based on time of arrival (TOA) measurement, received signal strength (RSSI) measurement, and time difference of arrival (TDOA) measurement.

[0005] Electromagnetic spectrum map is a visualization method to characterize the distribution of electromagnetic spectrum in a region. It can be regarded as a database of radio environment information in a certain space environment. By constructing electromagnetic spectrum map, the location of radiation source can be intuitively seen, and the distribution form of radiation source leakage can be accurately seen by superimposing reconstructed signals. The construction of electromagnetic spectrum map can provide a basis for electromagnetic compatibility fault diagnosis.

[0006] At present, the relevant patents for electromagnetic spectrum map construction for underdetermined blind source separation of multiple radiation sources in narrow-band electric field of electromagnetic compatibility EMI mainly include the following:

[0007] Patent CN114895242B discloses "a method for locating radiation sources in a complex electromagnetic environment". The invention uses a number of sensors and a number of anchor nodes evenly distributed in the target area to obtain the two-dimensional position fingerprint of the anchor node; calculates the matching degree between the instantaneous channel characteristics and the two-dimensional position fingerprint of the screened anchor node, thereby determining the location of the radiation source.

[0008] Patent CN116136582A discloses "radiation source positioning method, device, electronic device and storage medium". This method obtains the position and speed of the observation platform at each moment in a preset time period and the reference point position of the radiation source, calculates the time-varying delay of the signal emitted by the radiation source received by the platform at each moment, and determines the position of the radiation source.

[0009] Patent CN115061124A discloses "radiation source positioning method, device, computer equipment and storage medium". This method obtains the target radiation source signal information in the target area and the position information of each sensor, and determines the target radiation source position information according to the position probability distribution matrix.

[0010] Patent CN109358318B discloses "a method for blind source separation of external radiation source radar to extract target echo and direct wave". This method uses SOBI blind source separation technology to extract target echo, and uses phase cancellation technology to reduce the impact of target echo on the remaining signal, thereby extracting a purer direct wave.

[0011] Patent application number CN115356562A discloses "a near-field positioning system and method for EMU radiation interference sources". The system collects electromagnetic field information of the target area in real time through electric field probes and magnetic field probes. Without sacrificing the spatial resolution of the probe, it can expand the low-frequency bandwidth of the electromagnetic field probe through the corresponding preamplifier to meet the detection requirements of 1Mhz to 30MHz of low-frequency radiation interference sources of EMUs. Through the positioning method, the near-field tracking of the EMU radiation interference source is gradually carried out to achieve near-field positioning of the interference source.

[0012] The above patents achieve radiation source positioning and quantitative analysis by calculating beam arrival direction estimation, based on phase difference estimation, using electric field probes, arranging multiple sensors, etc. Although they all involve electric field radiation source positioning or electromagnetic compatibility, relatively speaking, the above methods all use electric field radiation source positioning technology, but none of them mention the use of underdetermined blind source separation methods in electromagnetic compatibility darkrooms to separate and locate multiple narrowband electric field radiation sources and construct electromagnetic spectrum maps. There are currently no reports in China on electromagnetic compatibility EMI narrowband electric field multiple radiation source underdetermined blind source separation electromagnetic spectrum map construction methods, devices and systems.

[0013] Based on the above background, the present invention proposes an electromagnetic spectrum map construction method, device and system for realizing EMI blind source separation, and realizes the use of underdetermined blind source separation method to separate and locate multiple radiation sources in the VHF frequency band of the EMC experimental electric field radiation emission project and generate an electromagnetic spectrum map. Summary of the invention

[0014] The purpose of the present invention is to provide an electromagnetic spectrum map construction method, device and system for realizing EMI blind source separation, and use the underdetermined blind source separation method to separate and locate multiple radiation sources in the VHF frequency band of the aerospace product EMC experimental electric field radiation emission project and generate an electromagnetic spectrum map.

[0015] The technical solution of the present invention is to provide a method for constructing an electromagnetic spectrum map for realizing EMI blind source separation, comprising the following steps:

[0016] S1. Calibrate the electromagnetic compatibility darkroom site environment and calculate the attenuation coefficient η of the electromagnetic compatibility darkroom site attenuation model; the site environment calibration process includes four steps: signal acquisition, signal filtering, signal fitting, and attenuation model calibration;

[0017] S2. Set the device under test and collect test data of array points respectively, wherein the test data includes coordinate information and EMI frequency domain data;

[0018] S3. Filter and normalize the EMI frequency domain data in step S2 to obtain normalized EMI data after normalization; perform ICA analysis on the EMI data to extract the frequency and RSSI information of each narrowband signal to obtain a separated RSSI signal; the separated RSSI signal is stored in an RSSI matrix;

[0019] S4. Calculate the RSSI matrix and use the RSSD positioning algorithm to calculate the positioning results of the three points in the RSSI matrix in turn. (x,y) , until all combinations in the RSSI matrix are calculated;

[0020] S5. Use K clustering to cluster the positioning results O(x,y) Perform clustering calculation to obtain K cluster centers; perform blind source separation according to the separated RSSI signals corresponding to the cluster centers to obtain multiple separated signals after blind source separation;

[0021] S6. constructing an electromagnetic spectrum map using an inverse distance weighted method according to the cluster centers;

[0022] S7. Overlay the electromagnetic spectrum map with the test desktop image to obtain a fused image electromagnetic spectrum map.

[0023] Furthermore, in the step S1, the signal collection method is: collecting the received signal strength RSSI at a distance of λ in front of the simulated radiation source placed on the metal test bench; the signal filtering method uses sliding filtering;

[0024] In step S1, the site attenuation model is The attenuation coefficient η is calculated using the site attenuation model.

[0025] Furthermore, in step S2, the array points are arranged in n×m.

[0026] In step S3, the RSSI matrix is ​​expressed as follows:

[0027]

[0028] Wherein, x is the horizontal coordinate of the acquisition point, y is the vertical coordinate of the acquisition point, P i is the RSSI signal, and N is the number of data points collected in total at n×m locations.

[0029] Furthermore, in step S4, the RSSD positioning algorithm:

[0030]

[0031] In the formula, x i 、x j 、x k is the horizontal coordinate of the acquisition point, y i ,y j ,y k is the ordinate of the acquisition point, and x and y are the positioning results. (x,y) Coordinate value, Ω ij ,Ω ik ,Ω jk is the distance factor Ω;

[0032] The distance factor Ω is calculated as:

[0033]

[0034] Where, η is the attenuation coefficient in step S1, and d is the distance from the emission source O to the acquisition point M. i 、M j 、M k The propagation distance d;

[0035] The propagation distance d:

[0036]

[0037] Furthermore, in step S5, the blind source separation process:

[0038]

[0039] Where, X(t) = [x1(t)x2(t)…x m (t)] is the EMI signal received by the receiver, S(t)=[S1(t)S2(t)…S m (t)] is the actual source signal, and the separated source signal Y(t) = [y1(t)y2(t)…y m (t)].

[0040] Furthermore, in step S6, the inverse distance weighted method calculation formula is:

[0041]

[0042] Where N is the estimated number of cluster centers, x i ,y i is the coordinate value of the ith cluster center; the electromagnetic distribution of each point in the plane is calculated according to the inverse distance weighted method formula to obtain the electromagnetic spectrum map.

[0043] Further, in the array point, m is 3 and n is 5;

[0044] The n×m points are spaced 0.5 m apart from each other and are evenly distributed in a matrix.

[0045] Further, the step S2 is repeated multiple times, and the EMI frequency domain data collected multiple times are averaged;

[0046] The EMI test data includes EMI radiation frequency and received signal strength RSSI information. The EMI radiation frequency is within the VHF frequency band, and the RSSI information is the amplitude corresponding to each frequency point of the EMI radiation frequency.

[0047] Another technical solution of the present invention provides an electromagnetic spectrum map construction device for realizing EMI blind source separation, comprising:

[0048] An electromagnetic compatibility darkroom, a test table arranged in the electromagnetic compatibility darkroom, the test table using a metal test tabletop;

[0049] A receiving antenna arranged in front of the test table, for receiving the radiation signal;

[0050] A receiver, configured to receive the RSSI value of the receiving antenna;

[0051] Sampling point set;

[0052] Test the computer.

[0053] Furthermore, the metal test tabletop is grounded via a conductive cable;

[0054] The receiving antenna is a biconical antenna, and the vertical polarization pattern of the biconical antenna is a uniform circle;

[0055] The receiving antenna is connected to the receiver via a wire, and the receiving frequency of the receiver includes a VHF frequency band;

[0056] The electromagnetic compatibility darkroom is a three-meter semi-anechoic chamber;

[0057] The sampling point set is arranged 0.5 meters in front of the test table top, and the insulating plate on the metal test table top has a thickness greater than 3 cm.

[0058] Another technical solution of the present invention provides an electromagnetic spectrum map construction system for realizing EMI blind source separation, including the above-mentioned electromagnetic spectrum map construction device for realizing EMI blind source separation.

[0059] The beneficial effects achieved by the electromagnetic spectrum map construction method, device and system for realizing EMI blind source separation provided by the present invention are:

[0060] The present invention proposes an electromagnetic spectrum map construction method, device and system for realizing EMI blind source separation. Through site environment calibration, signal acquisition, signal processing, blind source separation and electromagnetic spectrum map imaging, the underdetermined blind source separation method is used to separate and locate multiple radiation sources in the VHF frequency band of the EMC experimental electric field radiation emission project and generate an electromagnetic spectrum map. It has high positioning accuracy, can realize the separation of multiple radiation sources, and makes the electromagnetic compatibility test results more intuitive. BRIEF DESCRIPTION OF THE DRAWINGS

[0061] The invention will be further described below in conjunction with the accompanying drawings:

[0062] Figure 1 The figure is a flow chart of the system of the present invention.

[0063] Figure 2A flow chart for constructing an electromagnetic spectrum map of the present invention.

[0064] Figure 3 It is a principle block diagram of the blind source separation method of the present invention.

[0065] Figure 4 This is the RSSD positioning principle diagram of the present invention. i 、M j 、M k There are three receiving points, with the three receiving points as the center and the propagation distance as the radius, intersecting at the radiation source S.

[0066] Figure 5 This is a diagram showing the arrangement of sampling points in the array of the present invention.

[0067] Figure 6 This is the clustering result diagram of the present invention.

[0068] Figure 7 This is a diagram of the signal separation results of the present invention.

[0069] Figure 8 Map of the electromagnetic spectrum before clustering constructed for the present invention.

[0070] Fig. 9 This is the spatial electric field intensity distribution diagram of the present invention.

[0071] Fig.10 This is the electromagnetic spectrum map after the present invention is superimposed with the test desktop. DETAILED DESCRIPTION

[0072] The electromagnetic spectrum map construction method, device and system for realizing EMI blind source separation proposed by the present invention are further described in detail below in conjunction with the accompanying drawings and specific embodiments. The advantages and features of the present invention will become clearer according to the following description and claims. It should be noted that the accompanying drawings are all in a very simplified form and use inaccurate ratios, which are only used to conveniently and clearly assist in explaining the purpose of the embodiments of the present invention.

[0073] Example 1

[0074] This embodiment provides a method for constructing an electromagnetic spectrum map to achieve EMI blind source separation, such as Figure 1 As shown, the following steps are included in sequence:

[0075] S1. Calibrate the electromagnetic compatibility darkroom site environment and calculate the attenuation coefficient η of the electromagnetic compatibility darkroom site attenuation model. The site environment calibration process includes four steps: signal acquisition, signal filtering, signal fitting, and attenuation model calibration. Among them, the signal acquisition measures the RSSI strength information at 0.3m to 2.5m from the radiation source in sequence through a biconical antenna, and the RSSI strength information sampling interval is 0.1m. The signal received by the antenna is stored as an array:

[0076] S=[s1s2…s n ]

[0077] Among them, s n is the RSSI strength information collected by the biconical antenna.

[0078] Enter array S into the formula

[0079]

[0080] Fitting is performed to obtain the attenuation coefficient η. In the formula, P r (d0) is the RSSI strength information at a distance of 1m, P r (d) is the RSSI strength information after the distance changes, d0 is 1m, and d is the interval distance.

[0081] Preferably, the signal filtering uses sliding filtering, and the sliding filtering window size is set to 3.

[0082] S2. Set the device under test and collect test data of array points respectively, wherein the test data includes coordinate information and EMI frequency domain data.

[0083] Furthermore, the test data is stored in the matrix S(t)

[0084]

[0085] Among them, x is the horizontal coordinate of the collection point, y is the vertical coordinate of the collection point, S(t) is the EMI frequency domain data, and n×m is the data of the n×m points collected in total.

[0086] S3. Filter and normalize the EMI frequency domain data described in S2 to obtain normalized EMI data after normalization. Perform ICA analysis on the EMI data to extract the frequency and RSSI information of each narrowband signal to obtain a separated RSSI signal. The separated RSSI signal is stored in an RSSI matrix.

[0087] The RSSI matrix is ​​expressed as

[0088]

[0089] Wherein, x is the horizontal coordinate of the acquisition point, y is the vertical coordinate of the acquisition point, P i is the RSSI signal, and N is the number of data collected from a total of n×m points.

[0090] S4. Calculate the RSSI matrix using the formula

[0091]

[0092] Where Ω is calculated using the formula

[0093]

[0094] Calculated. Where x and y are the emission source O (x,y) The horizontal and vertical coordinates, x i 、x j 、x k is the horizontal coordinate of the acquisition point, y i ,y j ,y k is the ordinate of the acquisition point, η is the attenuation coefficient, d is the emission source O (x,y) To the collection point M i 、M j 、M k The propagation distance d.

[0095] Traverse the positioning results of the three points in the RSSI matrix O (x,y) , until all combinations in the RSSI matrix are calculated.

[0096] S5. Use K clustering to cluster the positioning results O (x,y) Perform clustering calculation to obtain K cluster centers and perform blind source separation according to the separated RSSI signals corresponding to the cluster centers to obtain multiple separated signals after blind source separation.

[0097] S6. Construct an electromagnetic spectrum map based on the cluster centers using an inverse distance weighted method.

[0098] S7. Overlay the electromagnetic spectrum map with the test desktop image to obtain a fused image electromagnetic spectrum map.

[0099] The above method can be used to separate and locate multiple radiation sources in the VHF frequency band of the EMC experimental electric field radiation emission project of aerospace products and generate an electromagnetic spectrum map.

[0100] Figure 2 A flow chart for constructing the electromagnetic spectrum map of the present invention is as follows: Figure 2As shown in the figure, electromagnetic spectrum construction includes defining spatial grids, obtaining the location of radiation sources, initializing signal strength, calculating the distance from the emission source to each point, calculating the path loss of each point, accumulating signal strength, and drawing RSSI distribution. Figure 7 Steps.

[0101] Specifically, the inverse distance weighted method is used to calculate the path loss at each point:

[0102]

[0103] Where N is the estimated number of cluster centers, x i ,y i is the coordinate value of the i-th cluster center, x a ,y a is the coordinate value of any point A in the electromagnetic spectrum map. The electromagnetic distribution of each point in the plane is calculated according to the inverse distance weighted method formula to obtain the electromagnetic spectrum map.

[0104] Figure 3 This is a principle block diagram of the blind source separation method of the present invention. EMI receiving signal X(t)

[0105] X(t)=[x1(t)x2(t)…x m (t)]

[0106] Contains the actual useful source signal S(t)

[0107] S(t)=[S1(t)S2(t)…S m (t)]

[0108] and noise signal N(t)

[0109] N(t)=[n1(t)n2(t)…n m (t)]

[0110] , after separation by the signal separation model, the separated source signal is obtained

[0111] Y(t)=[y1(t)y2(t)…y m (t)].

[0112] Blind source separation of EMI signals can be achieved through the blind source separation system.

[0113] Figure 4 This is the RSSD positioning principle diagram of the present invention. i 、M j 、M k There are three receiving points, with the three receiving points as the center of the circle and the propagation distance as the radius, intersecting at the EMI radiation source S.

[0114] Furthermore, the radiation source can be calculated using the formula

[0115]

[0116] The radiation source position (x, y) is calculated.

[0117] Example 2

[0118] This embodiment provides an electromagnetic spectrum map construction device for realizing EMI blind source separation. Figure 5 The array sampling point arrangement diagram of the present invention is shown in the figure. In the figure, the array points are arranged in a 3×5 point layout, and the center of the array point is set 1 meter in front of the test table.

[0119] Furthermore, in this embodiment, the receiving antennas are sequentially placed at the array points. During the test, the EMI radiation source comes from the device under test placed on the test table.

[0120] Preferably, the height of the receiving antenna is 1 m.

[0121] Example 3

[0122] This embodiment provides an electromagnetic spectrum map construction system for implementing EMI blind source separation. During testing, an EMI test system is used to receive EMI frequency domain signals at test points and store signal data.

[0123] The clustering result of the present invention is shown in FIG. Figure 6 , where the triangle is the estimated position of the 100MHz signal radiation source, and the square is the estimated position of the 48MHz signal radiation source. In the embodiment of the present invention, two point radiation sources are used. Two cluster centers are obtained by using K clustering. Figure 7 This is the signal separation result diagram of the present invention, arranged from top to bottom are the original signal frequency domain curve, the separated signal 1 frequency domain curve, and the separated signal 2 frequency domain curve. Separated signal 1 and separated signal 2 are curves obtained by the original signal through an electromagnetic spectrum map construction method for electromagnetic compatibility EMI narrowband electric field multi-radiation source underdetermined blind source separation provided by the present invention. It can be seen in the figure that the original signal is the superposition of separated signal 1 and separated signal 2. Figure 6 According to the first part of the present invention, the electromagnetic spectrum map is constructed, and the obtained Figure 8 Image shown. Fig. 9 The electromagnetic spectrum map is constructed according to the first part of the present invention using the cluster centers of the separated signals 1 and 2, and displayed using a 3D image, wherein the peak points in the image are the estimated positions of the radiation sources.

[0124] Will Figure 8 The image obtained by superimposing it with the image taken from the top of the test table is as follows: Fig.10As shown in the figure, the bright area is the area with high radiation intensity. Through this image, the distribution of radiation sources can be located and quantitatively analyzed, thereby realizing the fault diagnosis of electromagnetic compatibility electric field radiation emission.

[0125] The contents not described in detail in this specification belong to the prior art known to those skilled in the art. It is obvious to those skilled in the art that the present invention is not limited to the details of the exemplary embodiments described above, and that the present invention can be implemented in other specific forms without departing from the spirit or essential features of the present invention. Therefore, no matter from which point of view, the embodiments should be regarded as exemplary and non-restrictive, and the scope of the present invention is defined by the appended claims rather than the above description, and it is intended that all changes falling within the meaning and scope of the equivalent elements of the claims are included in the present invention.

Claims

1. A method for constructing an electromagnetic spectrum map for realizing EMI blind source separation, characterized in that: The steps include: S1. Calibrate the electromagnetic compatibility darkroom site environment and calculate the attenuation coefficient η of the electromagnetic compatibility darkroom site attenuation model; the site environment calibration process includes four steps: signal acquisition, signal filtering, signal fitting, and attenuation model calibration; S2. Set the device under test and collect test data of array points respectively, wherein the test data includes coordinate information and EMI frequency domain data; S3. Filtering and normalizing the EMI frequency domain data in step S2 to obtain normalized EMI data after normalization; performing ICA analysis on the EMI data to extract the frequency and RSSI information of each narrowband signal to obtain the separated RSSI signal; The separated RSSI signals are stored in an RSSI matrix; S4. Calculate the RSSI matrix and use the RSSD positioning algorithm to calculate the positioning results of the three points in the RSSI matrix in turn. (x,y) , until all combinations in the RSSI matrix are calculated; S5. Use K clustering to cluster the positioning results O (x,y) Perform clustering calculation to obtain K cluster centers; perform blind source separation according to the separated RSSI signals corresponding to the cluster centers to obtain multiple separated signals after blind source separation; S6. constructing an electromagnetic spectrum map using an inverse distance weighted method according to the cluster centers; S7. Overlay the electromagnetic spectrum map with the test desktop image to obtain a fused image electromagnetic spectrum map.

2. The method for constructing an electromagnetic spectrum map for realizing EMI blind source separation according to claim 1, characterized in that: In the step S1, the signal collection method is: collecting the received signal strength RSSI at a distance of λ in front of the simulated radiation source placed on the metal test bench; the signal filtering method uses sliding filtering; In step S1, the site attenuation model is The attenuation coefficient η is calculated using the site attenuation model.

3. The method for constructing an electromagnetic spectrum map for realizing EMI blind source separation according to claim 1, characterized in that: In the step S2, the array points are arranged in n×m. In step S3, the RSSI matrix is ​​expressed as follows: Wherein, x is the horizontal coordinate of the acquisition point, y is the vertical coordinate of the acquisition point, P i is the RSSI signal, and N is the number of data collected from a total of n×m points.

4. The method for constructing an electromagnetic spectrum map for realizing EMI blind source separation according to claim 1, characterized in that: In step S4, the RSSD positioning algorithm: In the formula, x i 、x j 、x k is the horizontal coordinate of the acquisition point, y i ,y j ,y k is the ordinate of the acquisition point, and x and y are the positioning results. (x,y) Coordinate value, Ω ij ,Ω ik ,Ω jk is the distance factor Ω; The distance factor Ω is calculated as: Where, η is the attenuation coefficient in step S1, and d is the distance from the emission source O to the acquisition point M. i 、M j 、M k The propagation distance d; The propagation distance d:

5. The method for constructing an electromagnetic spectrum map for realizing EMI blind source separation according to claim 1, characterized in that: In step S5, the blind source separation process: Where, X(t) = [x1(t)x2(t)…x m (t)] is the EMI signal received by the receiver, S(t)=[S1(t)S2(t)…S m (t)] is the actual source signal, and the separated source signal Y(t) = [y1(t)y2(t)…y m (t)].

6. The method for constructing an electromagnetic spectrum map for realizing EMI blind source separation according to claim 1, characterized in that: In step S6, the inverse distance weighted method calculation formula is: Where N is the estimated number of cluster centers, x i ,y i is the coordinate value of the ith cluster center; the electromagnetic distribution of each point in the plane is calculated according to the inverse distance weighted method formula to obtain the electromagnetic spectrum map.

7. The method for constructing an electromagnetic spectrum map for realizing EMI blind source separation according to claim 3, characterized in that: In the array point, m is 3 and n is 5; The n×m points are spaced 0.5 m apart from each other, and are evenly distributed in a matrix. Repeating step S2 multiple times, and averaging the EMI frequency domain data collected multiple times; The EMI test data includes EMI radiation frequency and received signal strength RSSI information. The EMI radiation frequency is within the VHF frequency band, and the RSSI information is the amplitude corresponding to each frequency point of the EMI radiation frequency.

8. An electromagnetic spectrum map construction device for realizing EMI blind source separation, used to realize the electromagnetic spectrum map construction method for realizing EMI blind source separation as described in any one of claims 1 to 7, characterized in that: include: An electromagnetic compatibility darkroom, a test table arranged in the electromagnetic compatibility darkroom, the test table using a metal test tabletop; A receiving antenna arranged in front of the test table, for receiving the radiation signal; A receiver, configured to receive the RSSI value of the receiving antenna; Sampling point set; Test the computer.

9. The electromagnetic spectrum map construction device for realizing EMI blind source separation according to claim 8, characterized in that: The metal test tabletop is grounded via a conductive cable; The receiving antenna is a biconical antenna, and the vertical polarization pattern of the biconical antenna is a uniform circle; The receiving antenna is connected to the receiver via a wire, and the receiving frequency of the receiver includes a VHF frequency band; The electromagnetic compatibility darkroom is a three-meter semi-anechoic chamber; The sampling point set is arranged 0.5 meters in front of the test table top, and the insulating plate on the metal test table top has a thickness greater than 3 cm.

10. An electromagnetic spectrum map construction system for realizing EMI blind source separation, characterized in that: It comprises an electromagnetic spectrum map construction device for realizing EMI blind source separation as described in any one of claims 8 or 9.

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