Multi-device information assisted precise suppression interference enhanced modeling method and device

Abstract

This application discloses a multi-device information-assisted precise jamming enhancement modeling method and apparatus, relating to the field of signal processing technology. It includes: S1, acquiring prior information about the opponent's radar detection equipment at different times using our interception and reconnaissance equipment and radar detection equipment; S2, dynamically adjusting the frequency domain and spatial domain constraints of the jamming signals from our multiple jamming devices based on the prior information of the opponent's radar detection signals at different times; S3, using the jamming signals from our multiple jamming devices as decision variables, and taking maximizing the relative entropy between the pulse compression results of the first radar echo signal and the pulse compression results of the second radar echo signal received by the opponent's radar as the optimization criterion, combined with the frequency domain and spatial domain constraints of the jamming signals from our multiple jamming devices at different times, to construct a precise jamming enhancement model. This solves the problems of traditional single-domain jamming methods being difficult to effectively counter in complex electromagnetic environments with high density and multiple radiation sources, as well as the unreasonable allocation of resources.

Description

Technical Field

[0001] This application relates to the field of signal processing technology, and in particular to a multi-device information-assisted precise interference suppression enhancement modeling method and apparatus. Background Technology

[0002] In modern electronic warfare environments, radar systems face increasingly complex electromagnetic threats and countermeasures. With the continuous advancement of radar technology, the detection capabilities of intercept receivers have also significantly improved, enabling high-precision analysis and identification of radar signals across multiple dimensions, including the time, frequency, spatial, and polarization domains. This multi-domain interception capability makes traditional single-domain jamming methods (such as active or passive jamming) ineffective against modern detection systems, especially in complex electromagnetic environments with high density and multiple radiation sources.

[0003] Traditional signal jamming techniques mainly rely on single-domain jamming methods. Zhang Xufeng et al. proposed a deceptive jamming generation algorithm in the paper "ISAR Radar Deception Jamming Signal Generation Algorithm [J]. Journal of National University of Defense Technology, 2014". Ji Penghui et al. proposed a dense false target generation method in the paper "Dense False Moving Target Generation Method [J]. Systems Engineering and Electronics, 2022". However, the above methods show certain shortcomings when facing multi-domain cooperative detection systems. Frequency domain jamming: Single-frequency band jamming is easily evaded by the opponent system through frequency hopping, spread spectrum or adaptive filtering techniques; Time domain jamming: Random noise jamming lacks specificity, making it difficult to accurately control the timing of jamming, and easily causing a waste of jamming resources; Spatial domain jamming: Traditional directional jamming techniques have limited jamming effects when facing multi-antenna systems, beamforming and smart antenna technologies. In addition, traditional jamming techniques lack dynamic optimization allocation of jamming resources, making it difficult to dynamically adjust the jamming strategy according to the electromagnetic situation and the characteristics of the opponent's signal, resulting in unstable jamming effects. Summary of the Invention

[0004] The purpose of this application is to provide a multi-device information-assisted precise suppression interference enhancement modeling method and apparatus to solve the problems of traditional single-domain interference methods being difficult to effectively counter in complex electromagnetic environments with high density and multiple radiation sources, as well as unreasonable resource allocation.

[0005] To achieve the above objectives, this application adopts the following technical solution:

[0006] On the one hand, this application provides a multi-device information-assisted precise suppression interference enhancement modeling method, including:

[0007] S1. Utilize our intercepted reconnaissance equipment and radar detection equipment to obtain prior information about the enemy's radar detection equipment at different times;

[0008] S2. Based on the prior information of the enemy's radar detection signals at different times, dynamically adjust the frequency domain constraints and spatial domain constraints of the jamming signals of our multiple jamming devices.

[0009] S3. Using the interference signals from multiple jamming devices on our side as decision variables, and taking maximizing the relative entropy between the pulse compression results of the first radar echo signal and the pulse compression results of the second radar echo signal received by the enemy radar as the optimization criterion, and combining the frequency domain constraints and spatial domain constraints of the interference signals from multiple jamming devices on our side at different times, a precise jamming suppression enhancement model is constructed; the first radar echo signal is the radar echo signal received by the enemy radar without interference signals from multiple jamming devices on our side, and the second radar echo signal is the radar echo signal received by the enemy radar with interference signals from multiple jamming devices on our side.

[0010] On the other hand, this application also provides a multi-device information-assisted precise suppression interference enhancement modeling device, comprising:

[0011] The information acquisition module is used to obtain prior information about the enemy's radar detection equipment at different times by utilizing our intercepted reconnaissance equipment and radar detection equipment;

[0012] The constraint establishment module is used to dynamically adjust the frequency domain constraints and spatial domain constraints of the jamming signals of multiple jamming devices of our side based on the prior information of the enemy's radar detection signals at different times.

[0013] The model building module is used to construct a precise jamming enhancement model by taking the jamming signals from multiple jamming devices on our side as decision variables, maximizing the relative entropy between the pulse compression results of the first radar echo signal and the pulse compression results of the second radar echo signal received by the enemy radar as the optimization criterion, and combining the frequency domain constraints and spatial domain constraints of the jamming signals from multiple jamming devices on our side at different times. The first radar echo signal is the radar echo signal received by the enemy radar without the jamming signals from multiple jamming devices on our side, and the second radar echo signal is the radar echo signal received by the enemy radar with the jamming signals from multiple jamming devices on our side.

[0014] On the other hand, this application also provides an electronic device:

[0015] A processor; and a memory for storing computer-executable instructions, which, when executed, cause the processor to perform the steps of the method as described in any one of the preceding claims.

[0016] On the other hand, this application also provides a storage medium:

[0017] The storage medium stores a processing program for multi-device information-assisted precise suppression interference enhancement modeling, and the processing program for multi-device information-assisted precise suppression interference enhancement modeling is executed by a processor using the steps of the method as described in any one of the preceding claims.

[0018] Based on the above technical solution, this application can achieve the following technical effects:

[0019] By employing multiple jammers in a frequency-domain coordinated operation, multiple suppressive jamming signals are combined into a wide-bandwidth frequency-sweeping jamming signal. Simultaneously, this wide-bandwidth jamming signal is dynamically adjusted at different times based on information such as the position, angle, and frequency of the target radar obtained from intercepted data and active radar. This achieves complete suppression of the target radar's detection signal in both the air and frequency domains, optimizing the allocation of air and frequency resources. By maximizing the relative entropy of the target radar's received echo, which is related to pulse compression, under both jamming and non-jamming conditions, the interference-to-signal ratio after processing the target radar's detection signal is increased, achieving a coordinated air-frequency suppression effect on the detection signal. Attached Figure Description

[0020] Figure 1 This is a flowchart illustrating a multi-device information-assisted precise interference suppression and enhancement modeling method provided in an embodiment of this application;

[0021] Figure 2 This is a schematic diagram of a multi-device information-assisted precision suppression interference enhancement model provided in an embodiment of this application;

[0022] Figure 3 This is a radar detection result diagram provided in an embodiment of this application, showing that the radar is not subject to interference.

[0023] Figure 4 This is a detection result of radar being subjected to uncooperative suppression interference provided in one embodiment of this application;

[0024] Figure 5 This is a detection result of radar being subjected to cooperative suppression jamming provided in an embodiment of this application;

[0025] Figure 6 This is a curve showing the change of radar pulse compression entropy with signal-to-interference ratio provided in an embodiment of this application. Detailed Implementation

[0026] The present application will be further described in detail below with reference to the accompanying drawings and specific embodiments. The advantages and features of the present application will become clearer from the following description. It should be noted that the drawings are all in a very simplified form and are not to scale, and are only used to facilitate and clarify the illustration of the embodiments of the present application.

[0027] It should be noted that, in order to clearly illustrate the content of this application, several embodiments are provided to further explain the different implementations of this application. These embodiments are enumerated rather than exhaustive. Furthermore, for the sake of brevity, content mentioned in the preceding embodiments is often omitted in the following embodiments. Therefore, content not mentioned in the following embodiments can be referred to in the preceding embodiments.

[0028] Example 1

[0029] Please refer to Figure 1 , Figure 1 The diagram shown is a flowchart of a multi-device information-assisted precise interference suppression enhancement modeling method provided in this embodiment. The method specifically includes the following steps:

[0030] S1. Use our intercepted reconnaissance equipment and radar detection equipment to obtain prior information about the enemy's radar detection equipment;

[0031] It should be noted that one implementation of S1 can be:

[0032] We can utilize our intercepted reconnaissance and radar detection equipment to obtain prior information such as the frequency, bandwidth, and beam direction of the enemy's radar detection signals. Secondly, the update cycle of this prior information can be determined based on the signal processing time of our intercepted reconnaissance and radar detection equipment.

[0033] S2. Based on the prior information of the enemy's radar detection signals at different times, dynamically adjust the frequency domain constraints and spatial domain constraints of the jamming signals of our multiple jamming devices.

[0034] It should be noted that one implementation of S2 can be:

[0035] S21. Assume the number of our jamming devices is... Then the bandwidth of the opponent's radar detection signal is divided equally. The bandwidth is divided into portions and allocated sequentially to each jamming device to obtain the allocated bandwidth range for each jamming device;

[0036] S22. Based on our bandwidth measurement error and the bandwidth range allocated to each interference device, a bandwidth constraint is formed on the interference signal of each interference device.

[0037] S23. Based on the carrier frequency of the enemy radar detection signal and the bandwidth constraints of the interference signals of each interference device, a carrier frequency constraint is formed for each interference device.

[0038] Furthermore, S2 also includes:

[0039] S24, Order No. The and the first The carrier frequency constraint of the interference signal from each interfering device must simultaneously satisfy the following constraints:

[0040]

[0041] in, Indicates the launch time. Indicates the carrier frequency. Indicates bandwidth.

[0042] Based on this, by constraining the carrier frequency of the interference signal of adjacent interference devices through S24, it is ensured that the carrier frequencies of the two interference devices overlap.

[0043] Furthermore, S2 also includes:

[0044] S25, Order The total bandwidth of the interference signal from the interfering device The following constraints must be met:

[0045]

[0046]

[0047] in, This indicates the bandwidth of the opponent's radar detection signal. Indicates intersection, constant This indicates the frequency band overlap between the jamming signal and the opponent's radar detection signal. express The bandwidth corresponding to the frequency of the highest interference signal at the transmission time. express The bandwidth corresponding to the frequency of the interference signal with the lowest transmission time.

[0048] Based on this, by constraining the total bandwidth of multiple jamming devices through S25, it is ensured that the frequency band of the opponent's radar signal is completely suppressed.

[0049] Therefore, by utilizing prior information obtained from intercepted reconnaissance and radar detection equipment, multiple jamming devices can coordinate in the frequency domain to splice multiple suppression jamming signals into a large-bandwidth frequency sweep jamming signal, thereby completely suppressing the opponent's radar detection signal in the frequency domain. Secondly, by acquiring prior information about the opponent's radar detection equipment at different times, the jamming carrier frequency and bandwidth can be precisely adjusted in real time to achieve precise frequency domain suppression jamming of the opponent's radar.

[0050] Another way to implement S2 is:

[0051] Based on the beam pointing of the enemy's radar detection signal and the measurement error of our own beam pointing, spatial constraints are formed for the interference signals of each jamming device, with the spatial constraints being the same for the interference signals of each jamming device.

[0052] Based on this, by acquiring prior information about the opponent's radar detection equipment at different times, the direction of the interference beam can be precisely adjusted in real time to achieve accurate matching of the direction of the opponent's radar beam.

[0053] S3. Using the interference signals from multiple jamming devices on our side as decision variables, and taking maximizing the relative entropy between the pulse compression results of the first radar echo signal and the pulse compression results of the second radar echo signal received by the enemy radar as the optimization criterion, and combining the frequency domain constraints and spatial domain constraints of the interference signals from multiple jamming devices on our side at different times, a precise jamming suppression enhancement model is constructed; the first radar echo signal is the radar echo signal received by the enemy radar without interference signals from multiple jamming devices on our side, and the second radar echo signal is the radar echo signal received by the enemy radar with interference signals from multiple jamming devices on our side.

[0054] It should be noted that one implementation of S3 can be:

[0055] S31. Construct the relative entropy function between the pulse compression results of the first radar echo signal received by the enemy radar and the pulse compression results of the second radar echo signal.

[0056] S32. Using the interference signals of multiple jamming devices of our side in the second radar echo signal as decision variables, taking the maximization of the relative entropy function as the objective function, and ensuring that the interference signals of multiple jamming devices of our side satisfy the frequency domain constraints and spatial domain constraints at different times, a precise jamming suppression enhancement model is obtained.

[0057] Furthermore, S31 includes:

[0058] S31-1. Perform pulse compression processing on the first radar echo signal and the second radar echo signal received by the opponent's radar respectively to obtain the pulse compression result of the first radar echo signal and the pulse compression result of the second radar echo signal received by the opponent's radar.

[0059] S31-2. After normalizing the pulse compression results of the first radar echo signal and the second radar echo signal received by the other party's radar, the discrete probability density distribution of the pulse compression results of the first radar echo signal and the discrete probability density distribution of the pulse compression results of the second radar echo signal are obtained.

[0060] S31-3. Based on the discrete probability density distribution of the pulse compression result of the first radar echo signal and the discrete probability density distribution of the pulse compression result of the second radar echo signal, construct the relative entropy function between the first radar echo signal and the second radar echo signal received by the other radar.

[0061] Based on this, by using the relative entropy related to pulse compression to evaluate the precise suppression effect of multi-device information assistance, a more accurate suppression effect can be obtained, thereby improving the accuracy of our interference signal modeling.

[0062] In summary, this method utilizes multiple jammers operating in a frequency-domain coordinated manner. Multiple suppressive jamming signals are combined into a wide-bandwidth sweeping jamming signal in the frequency domain. Simultaneously, this wide-bandwidth jamming is dynamically adjusted at different times based on information such as the position, angle, and frequency of the target radar obtained from our interception and active radar. This achieves complete suppression of the target radar's detection signal in both the air and frequency domains, optimizing the allocation of air and frequency resources. By maximizing the relative entropy related to pulse compression of the target radar's received echo under both with and without jamming conditions, the interference-to-signal ratio after processing the target radar's detection signal is increased, achieving a coordinated air-frequency suppression effect on the detection signal.

[0063] Example 2

[0064] This embodiment provides a detailed implementation process for a multi-device information-assisted precise interference suppression enhancement modeling method, the principle of which is as follows: Figure 2 As shown, the specific steps are as follows:

[0065] Step 1: Construct a precise interference signal suppression model assisted by multi-device information:

[0066] Assuming a radar exists in the electromagnetic space, and the radar echo signal includes target echo, interference signal, and noise, it can be represented as:

[0067]

[0068] in, This is the echo signal of the radar transmitted signal received by the radar. This is a noise signal. This is an interference signal. Indicates time.

[0069] Assuming there are within the space exploration area The jammer, of which the first... The interference signal is represented as follows:

[0070]

[0071]

[0072] in, For the first The amplitude of the interference signal from the jammer. For the first The jamming signal emitted by the jammer reaches the radar receiver. For the first The time delay of the jamming signal emitted by a jammer reaching the radar receiver.

[0073] The jamming signals emitted by jammers vary depending on the type of jamming and the coordination method. The following primarily considers suppression-type multi-main-lobe jamming. It is assumed that each jammer emits noise-type suppression jamming, mainly noise frequency modulation (FM) and noise amplitude modulation (AM) jamming.

[0074] Among them, the frequency modulation noise interference is:

[0075]

[0076] in, For the first The jammer was at the first Carrier frequency and modulation noise at the time of transmission It is a zero-mean generalized stationary random process. , are constants, representing the amplitude and modulation slope of the frequency-modulated noise interference, respectively, and the phase... obey Evenly distributed on top, and with independent. That is, variables Since the maximum points are , Introduction Used for differentiation.

[0077] The noise amplitude modulation interference is:

[0078]

[0079] in, With a mean of 0 and a variance of ( (where is a constant), in the interval A generalized stationary random process with a distributed phase obey Evenly distributed on top, and with independent, It is a constant.

[0080] Step 2: Maximize the relative entropy of the radar echo received under interference-free conditions, and construct an optimization criterion based on maximizing the relative entropy;

[0081] First, define the KL (Kullback-Leibler, KL) distance as a measure of the difference between two probability density functions. Assume the ideal probability density function is... The estimated probability density function is as follows: Then the estimated probability density function is The ideal probability density function is The KL distance is expressed as:

[0082]

[0083] The above concepts are now introduced into the evaluation of anti-interference effect. Assuming an ideal, interference-free condition, the radar echo pulse compression result is expressed as follows: , This represents the number of discrete points, and the normalized result is:

[0084]

[0085] Then its discrete probability density distribution is :

[0086]

[0087] Under interference conditions, the radar echo pulse compression and normalization result is:

[0088]

[0089] Then its discrete probability density distribution is :

[0090]

[0091] The KL distance between the pulse compression results under interference and those under no interference is:

[0092]

[0093] The following is a collaborative and precise jamming suppression model based on relative entropy related to pulse compression and aided by multi-device information. It considers multiple jammers operating in a frequency-domain collaborative mode, where multiple jamming signals are combined into a large-bandwidth sweeping jammer. Simultaneously, at different times, this large-bandwidth jammer is adjusted based on information such as the position, angle, and frequency of the target radar obtained by our passive reconnaissance aircraft and active radar. This achieves complete suppression of the target radar's detection signal in both the air and frequency domains, increasing the interference-to-signal ratio after processing by the target radar, i.e., maximizing the relative entropy of the target radar's received echo under jamming conditions. The optimization criterion based on maximizing relative entropy is as follows:

[0094]

[0095] in, The target echo received by the enemy's radar. For radar echo signals, This refers to the jamming signal received by the enemy's radar. These represent the carrier frequency, bandwidth, azimuth angle, and elevation angle of our jamming aircraft, respectively, and have... , , Indicates the first The transmission frequency sequence of a jammer. Indicates the first The jammer was at the first The transmission frequency at the time of launch; , , Indicates the first The transmit bandwidth sequence of a jammer, Indicates the first The jammer was at the first The bandwidth of the transmitted signal at the moment of transmission; , , Indicates the first Azimuth sequence of each jammer Indicates the first The jammer was at the first The azimuth angle at the moment of launch; , , Indicates the first The transmission elevation angle sequence of a jammer, Indicates the first The jammer was at the first The elevation angle at launch. Where the relative entropy is... Represented as:

[0096]

[0097] Step 3: Consider the constraints of precise interference suppression aided by multi-device information;

[0098] 1. Frequency domain resource constraints

[0099] Interference signal frequency domain resource constraints include bandwidth and carrier frequency .

[0100] The interference bandwidth constraint is expressed as follows:

[0101]

[0102] in, and The bandwidth B is jointly determined by the intercepted receiver and the radar detection signal acquired by our active radar.

[0103] Interference carrier frequency constraints can be expressed as:

[0104]

[0105] in, and The carrier frequency is jointly determined by the intercepted receiver and the radar detection signal acquired by our active radar.

[0106] Combining the above two equations, we can obtain the total constraint on frequency domain resources, that is... jammer Total bandwidth at launch time Bandwidth of the opponent's radar detection signal When the overlap is greater than or equal to 1, the frequency band of the opposing radar signal is completely suppressed. The constraint condition is expressed as:

[0107]

[0108] in, , express The bandwidth corresponding to the frequency of the highest interference signal at the transmission time. express The bandwidth corresponding to the frequency of the interference signal with the lowest transmission time. Indicates intersection, constant This indicates the degree of overlap between the interference and the radar frequency band.

[0109] 2. Airspace resource constraints

[0110] When the jammer's transmitted beam is aligned with the radar beam's main lobe, it will reach maximum jamming power at the radar receiver. Therefore, based on the azimuth and elevation information of the enemy's detection radar provided by our intercepted reconnaissance equipment, the jammer's beam direction is constrained, as shown below:

[0111]

[0112] in, The location and elevation information of the enemy's detection radar, obtained by our interception and reconnaissance equipment, are determined.

[0113] Step 4: Construct a precise interference suppression optimization model assisted by multi-device information.

[0114] Taking into account the optimization criteria and constraints mentioned in steps two and three, the following optimization model for precise interference suppression with multi-device information assistance is constructed:

[0115]

[0116] like Figure 3 This is a diagram showing the detection results of the radar without interference. Figure 4 This is the detection result of radar being subjected to uncooperative suppression interference. Figure 5 The detection results of radar being subject to cooperative suppression jamming. Figure 6 This is a curve showing the variation of radar relative entropy with signal-to-interference ratio (SIR) related to pulse compression. Figure 4It can be seen that, because the jammer is in a non-cooperative operating mode and the radar's transmitted waveform is pulse-hopping, the detection radar can still obtain target information from the signal processing results. Figure 5 It is known that under the precise suppression and jamming aided by information from multiple devices, the jammer can use the air frequency and other information of the opponent's detection equipment obtained by the intercepted receiver and radar to precisely adjust the jamming carrier frequency, bandwidth and beam direction in real time, so as to achieve precise suppression and jamming of the opponent's radar.

[0117] The effectiveness of precise jamming aided by multi-device information assistance is evaluated using relative entropy related to pulse compression. With signal-to-interference ratio (SIR) as the variable, the relative entropy results of the detection radar with and without interference are as follows: Figure 6 Under both cooperative and non-cooperative jamming conditions, the relative entropy related to pulse compression increases with the increase of the signal-to-interference ratio (SIR) at the radar receiver, which is consistent with theoretical conditions. Furthermore, the relative entropy curve related to pulse compression under cooperative jamming is consistently higher than that under non-cooperative jamming, indicating that cooperative jamming is more effective.

[0118] In summary, with the assistance of multiple devices for precise suppression and jamming, the jammer can use the air frequency and other information of the opponent's detection equipment obtained by the interceptor and radar to adjust the jamming carrier frequency, bandwidth and beam direction in real time, so as to achieve precise suppression and jamming of the opponent's radar.

[0119] Example 3

[0120] This embodiment provides a multi-device information-assisted precise interference suppression enhancement modeling device. The device specifically includes:

[0121] The information acquisition module is used to obtain prior information about the enemy's radar detection equipment at different times by utilizing our intercepted reconnaissance equipment and radar detection equipment;

[0122] The constraint establishment module is used to dynamically adjust the frequency domain constraints and spatial domain constraints of the jamming signals of multiple jamming devices of our side based on the prior information of the enemy's radar detection signals at different times.

[0123] The model building module is used to construct a precise jamming enhancement model by taking the jamming signals from multiple jamming devices on our side as decision variables, maximizing the relative entropy between the pulse compression results of the first radar echo signal and the pulse compression results of the second radar echo signal received by the enemy radar as the optimization criterion, and combining the frequency domain constraints and spatial domain constraints of the jamming signals from multiple jamming devices on our side at different times. The first radar echo signal is the radar echo signal received by the enemy radar without the jamming signals from multiple jamming devices on our side, and the second radar echo signal is the radar echo signal received by the enemy radar with the jamming signals from multiple jamming devices on our side.

[0124] Example 4

[0125] In another feasible embodiment, this embodiment provides a device for multi-device information-assisted precise suppression of interference enhancement modeling, the device specifically including:

[0126] A processor; and a memory for storing computer-executable instructions, which, when executed, cause the processor to perform the steps as described in any of the above method embodiments.

[0127] Example 5

[0128] In another feasible embodiment, this embodiment provides a storage medium for multi-device information-assisted precise suppression of interference enhancement modeling, the storage medium specifically including:

[0129] The storage medium stores a processing program for multi-device information-assisted precise suppression of interference enhancement modeling. When the multi-device information-assisted precise suppression of interference enhancement modeling processing program is executed by the processor, it implements the steps as described in any of the above method embodiments.

[0130] The above description is merely an embodiment of this application and is not intended to limit this application. Various modifications and variations can be made to this application by those skilled in the art. Any modifications, equivalent substitutions, improvements, etc., made within the spirit and principle of this application should be included within the scope of the claims of this application.

Claims

1. A multi-device information-assisted precise interference suppression and enhancement modeling method, characterized in that, include: S1. Utilize our intercepted reconnaissance equipment and radar detection equipment to obtain prior information about the enemy's radar detection equipment at different times; S2. Based on the prior information of the enemy's radar detection equipment at different times, dynamically adjust the frequency domain constraints and spatial domain constraints of the interference signals of our multiple jamming devices; S3. Using the interference signals from multiple jamming devices on our side as decision variables, and taking maximizing the relative entropy between the pulse compression results of the first radar echo signal and the pulse compression results of the second radar echo signal received by the enemy radar as the optimization criterion, and combining the frequency domain constraints and spatial domain constraints of the interference signals from multiple jamming devices on our side at different times, a precise jamming suppression enhancement model is constructed; the first radar echo signal is the radar echo signal received by the enemy radar without interference signals from multiple jamming devices on our side, and the second radar echo signal is the radar echo signal received by the enemy radar with interference signals from multiple jamming devices on our side.

2. The method according to claim 1, characterized in that, The prior information includes the bandwidth and carrier frequency of the opponent's radar detection signal at different times, and S2 includes: S21. Assuming the number of our jamming devices is M, the bandwidth of the enemy's radar detection signal is divided into M equal parts and distributed to each jamming device in sequence to obtain the bandwidth range allocated to each jamming device. S22. Based on our bandwidth measurement error and the bandwidth range allocated to each interference device, a bandwidth constraint is formed on the interference signal of each interference device. S23. Based on the carrier frequency of the enemy radar detection signal and the bandwidth constraints of the interference signals of each interference device, a carrier frequency constraint is formed for each interference device.

3. The method according to claim 2, characterized in that, S2 further includes: S24. Let the carrier frequency constraints of the interference signals of the m-th and (m+1)-th interfering devices simultaneously satisfy the following constraints: f mk +b mk / 2≤f (m+1)k ≤f mk +b mk / 2+b (m+1)k / 2 Where k represents the transmission time, f represents the carrier frequency, and b represents the bandwidth.

4. The method according to claim 2, characterized in that, S2 further includes: S25. Let B be the total bandwidth of the interference signals from M interfering devices. J The following constraints must be met: B J (k)=(max(f mk )+b max / 2)-(min(f mk )-b min / 2) Where B represents the bandwidth of the opponent's radar detection signal, ∩ represents the intersection, δ is a constant δ∈[0,1], and represents the frequency band overlap between the jamming signal and the opponent's radar detection signal. max b represents the bandwidth corresponding to the frequency point of the highest interference signal at transmission time k. min f represents the bandwidth corresponding to the lowest interference signal frequency at transmission time k. mk Let represent the transmission frequency of the m-th jammer at the k-th transmission time.

5. The method according to claim 1, characterized in that, The prior information also includes the beam pointing of the opponent's radar detection signal at different times, and S2 includes: Based on the beam pointing of the enemy radar detection signal and the measurement error of our beam pointing, spatial constraints are formed for the interference signals of each jamming device, wherein the spatial constraints are the same for the interference signals of each jamming device.

6. The method according to claim 1, characterized in that, S3 includes: S31. Construct the relative entropy function between the pulse compression results of the first radar echo signal received by the enemy radar and the pulse compression results of the second radar echo signal. S32. Using the interference signals of multiple jamming devices of our side in the second radar echo signal as decision variables, taking the maximization of the relative entropy function as the objective function, and ensuring that the interference signals of multiple jamming devices of our side satisfy the frequency domain constraints and spatial domain constraints at different times, a precise jamming suppression enhancement model is obtained.

7. The method according to claim 6, characterized in that, S31 includes: S31-1. Perform pulse compression processing on the first radar echo signal and the second radar echo signal received by the opponent's radar respectively to obtain the pulse compression result of the first radar echo signal and the pulse compression result of the second radar echo signal received by the opponent's radar. S31-2. After normalizing the pulse compression results of the first radar echo signal and the second radar echo signal received by the other party's radar, the discrete probability density distribution of the pulse compression results of the first radar echo signal and the discrete probability density distribution of the pulse compression results of the second radar echo signal are obtained. S31-3. Based on the discrete probability density distribution of the pulse compression result of the first radar echo signal and the discrete probability density distribution of the pulse compression result of the second radar echo signal, construct the relative entropy function between the first radar echo signal and the second radar echo signal received by the other radar.

8. A multi-device information-assisted precise interference suppression and enhancement modeling device, characterized in that, include: The information acquisition module is used to obtain prior information about the enemy's radar detection equipment at different times by utilizing our intercepted reconnaissance equipment and radar detection equipment; The constraint establishment module is used to dynamically adjust the frequency domain constraints and spatial domain constraints of the interference signals of multiple jamming devices of our side based on the prior information of the enemy's radar detection equipment at different times. The model building module is used to construct a precise jamming enhancement model by taking the jamming signals from multiple jamming devices on our side as decision variables, maximizing the relative entropy between the pulse compression results of the first radar echo signal and the pulse compression results of the second radar echo signal received by the enemy radar as the optimization criterion, and combining the frequency domain constraints and spatial domain constraints of the jamming signals from multiple jamming devices on our side at different times. The first radar echo signal is the radar echo signal received by the enemy radar without the jamming signals from multiple jamming devices on our side, and the second radar echo signal is the radar echo signal received by the enemy radar with the jamming signals from multiple jamming devices on our side.

9. An electronic device, characterized in that, include: processor; And a memory arranged to store computer-executable instructions, which, when executed, cause the processor to perform the steps of the method as claimed in any one of claims 1 to 7.

10. A storage medium, characterized in that, include: The storage medium stores a processing program for multi-device information-assisted precise suppression of interference enhancement modeling, and the processing program for multi-device information-assisted precise suppression of interference enhancement modeling is executed by a processor using the steps of the method as described in any one of claims 1 to 7.

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