Coherent interference method and device for inverse synthetic aperture radar image destruction

Abstract

The invention provides a coherent interference method and device for inverse synthetic aperture radar image destruction, and relates to the technical field of radar signal interference. The invention releases simulated baits through a data interception module to intercept and store enemy radar electromagnetic wave characteristics; the data modulation interference module changes the echo signal frequency and phase through phase modulation PM and auxiliary modulation; the simulated bait released by the warhead has two working modes, wherein the noise working mode destroys the image by generating noise to reduce the signal-to-noise ratio; the other mode receives and analyzes enemy radar wave characteristics through simulated baits, stores signals by using optical fiber radio frequency signal storage technology, modulates and amplifies the signals and then forwards them, and performs fuzzy processing on the warhead imaging; through electromagnetic wave interference and misleading, the enemy is prevented from accurately identifying and tracking missile warheads, and the missile strike success rate and survivability are significantly improved.

Description

Technical Field

[0001] The present invention relates to the field of radar signal jamming technology, in particular to a coherent jamming method and device for inverse synthetic aperture radar image destruction. Background Art

[0002] Inverse synthetic aperture radar (ISAR) technology, as a high-resolution imaging radar technology, has been widely used in military and civilian fields. ISAR analyzes the radar echo signals of the target at different time points and uses the rotation or motion characteristics of the target to achieve high-precision two-dimensional or three-dimensional imaging of the target. However, with the continuous development of ISAR technology, its countermeasure technology has also received increasing attention. Coherent interference technology is one of the effective means to counter ISAR imaging. Its core lies in simulating the radar echo signals of the target to destroy the enemy's ISAR imaging process, thereby achieving the purpose of stealth or deception.

[0003] Although the existing coherent interference technology can interfere with ISAR imaging to a certain extent, it still has the following shortcomings:

[0004] First, the traditional coherent jamming method relies on the precise interception and analysis of enemy radar signals, which is technically difficult and uncertain in actual operation. Second, the existing technology lacks flexibility and adaptability in signal modulation and jamming strategies, making it difficult to cope with complex and changing battlefield environments and dynamic adjustments of enemy radar systems.

[0005] In addition, traditional jamming methods often neglect the fine control of jamming signal characteristics during the generation and transmission of jamming signals, resulting in poor jamming effects;

[0006] How to develop a new type of decoy that can implement a coherent interference method to destroy the inverse synthetic aperture radar image, specifically by receiving and analyzing the enemy radar wave, through radio frequency storage, delayed forwarding and modulation technology, effectively interfere with and destroy the enemy radar imaging capability, and through electromagnetic wave interference and misleading, prevent the enemy from accurately identifying and tracking the missile warhead, thereby significantly improving the missile's strike success rate and survivability, and by reducing the signal-to-noise ratio and blurring the enemy's imaging, is the direction that needs to be improved at present;

[0007] The above information disclosed in this Background section is only for enhancement of understanding of the background of the present disclosure and therefore it may contain information that does not constitute the prior art that is already known to one of ordinary skill in the art. Summary of the invention

[0008] The object of the present invention is to provide a coherent interference method and device for inverse synthetic aperture radar image destruction to solve the problems raised in the above background technology.

[0009] To achieve the above object, the present invention provides the following technical solutions:

[0010] The coherent interference method for inverse synthetic aperture radar image destruction includes the following specific steps:

[0011] Step S1, releasing a plurality of groups of simulated decoys in the electromagnetic wave coverage area of ​​the radar to be interfered, and performing signal analysis after the simulated decoys intercept the electromagnetic wave signal emitted by the radar to be interfered to obtain the electromagnetic wave characteristic data of the radar to be interfered, and storing the data, wherein the electromagnetic wave characteristic data includes the operating frequency and pulse width of the electromagnetic wave signal;

[0012] Step S2, acquiring and storing the intercepted electromagnetic wave characteristic data and performing phase modulation and auxiliary modulation in sequence, then selecting an antenna array of the simulated bait as a reference array, collecting relative indexes of the antenna arrays of all simulated baits relative to the reference array, wherein the relative indexes include relative position, relative phase and relative amplitude data;

[0013] Step S3, using an adaptive beamforming algorithm to analyze and process the relative indexes of all simulated decoys to generate a first adjustment strategy for adjusting the simulated decoy antenna array transmission parameters, and at the same time, analyzing and processing the electromagnetic wave characteristic data to generate an interference noise signal;

[0014] Step S4, collecting the self-characteristic parameters of the simulated bait and analyzing and processing them to generate a dynamic evaluation index for dynamically adjusting the first adjustment strategy, the dynamic evaluation index can generate the final emission parameters of each simulated bait in a dynamic adjustment manner, the self-characteristic parameters include the physical position, relative distance, reflection coefficient, emission power, frequency characteristics and modulation parameters of the simulated bait;

[0015] Step S5, the simulated decoy generates a modulation signal according to the final transmission parameters, and after a delay of a specific time length, the simulated decoy synchronously transmits electromagnetic waves generated based on the interference noise signal and the modulation signal to the radar to be interfered.

[0016] Furthermore, the dynamic evaluation index is defined as E dynamic , the calculation formula is as follows:

[0017]

[0018] The parameters are explained as follows: dynamic is the dynamic evaluation index; α i′ is the weight of the i′th parameter, there are N′ parameters in total;

[0019] f i′ (r decoy ,Δr,Γ,P decoy ,f decoy ,M decoy ) is the complex summation function of the i′th parameter; β is the parameter that adjusts the steepness of the exponential function,

[0020] P decoy is the emission power of the simulated decoy; P0 is the reference value of the emission power, e is a natural constant; γ is the adjustment parameter of the normalization function;

[0021] g j (r decoy ,Δr,Γ,P decoy ,f decoy ,M decoy ) is the complex information filtering function of the jth parameter, with a total of M parameters;

[0022] For the complex sum function f i′ :

[0023]

[0024] For complex information filtering function g j :

[0025]

[0026] The parameter is interpreted as, r decoy [k] represents the position vector r of the simulated bait decoy The kth element of represents the position coordinates of the bait in space;

[0027] Δr[k] represents the kth element of the position change vector Δr, which represents the relative change of position; Indicates the simulated bait transmission power P decoy The square root of

[0028] log(f decoy ·M decoy [k]) indicates the decoy and M decoy The logarithm of the product of [k]; M decoy [k] represents the kth element of the simulated decoy modulation parameters;

[0029] α i′k represents the weight of the kth sub-parameter of the i-th parameter; Δr[l] represents the lth element of the position change vector Δr;

[0030] represents f decoy and M decoyThe negative power of the square of the product of [l], i.e., the exponential decay function;

[0031] α jl represents the weight of the lth sub-parameter of the jth parameter;

[0032] Get dynamic evaluation index E dynamic , to adjust the weight vector w of the antenna array and obtain the following optimal weight vector w opt :

[0033]

[0034] And set the dynamic evaluation index value range to E dynamic ∈[0,10];

[0035] When E dynamic The closer it is to 0, the smaller the influence of the simulated decoy parameters on beamforming is, and the smaller the adjustment of the optimal weight vector is;

[0036] When E dynamic The closer it is to 10, the greater the influence of the simulated decoy parameters on beamforming, and the greater the adjustment of the optimal weight vector.

[0037] Furthermore, E dynamic ∈[0,10] is divided into the following intervals, and the judgment criteria and rules, as well as the interaction rules are described for each interval;

[0038] Interval 1, E dynamic ∈[0,2); In this interval, the influence of simulated decoy parameters on beamforming is minimal; the transmission power P decoy Below 5dBm, the relative distance Δr exceeds 50 meters, resulting in weak interference signals;

[0039] In terms of technical effect, the antenna array has a low adjustment requirement and the existing configuration is maintained; the E dynamic The threshold is 1, and judgment is made. When E dynamic When it is less than 1, no adjustment is required; when E dynamic When it is between 1 and 2, fine-tune; parameter changes have an impact on E dynamic The impact is small; the dynamic index adjustment rules are as follows:

[0040] ΔE dynamic =0.1·ΔP decoy +0.05·Δf decoy +0.02·ΔΓ

[0041] Parameter explanation, ΔE dynamic is the change of dynamic evaluation index; ΔP decoy is the change in transmit power; Δf decoyis the change of frequency characteristics; ΔΓ is the change of reflection coefficient;

[0042] Interval 2, E dynamic ∈[2,5), in this interval, the simulated decoy parameters have a 10% to 25% effect on beamforming; the transmit power P decoy Between 5 and 10 dBm, the relative distance Δr is between 20 and 50 meters; set E dynamic The threshold is 3.5, and the interference intensity is dynamically judged and adjusted; when E dynamic When it is less than 3.5, adjust the parameters within 15%; when E dynamic When the value is between 3.5 and 5, a significant adjustment of less than 35% is made; the change of this parameter has a significant impact on E dynamic The impact is more obvious;

[0043] The dynamic index adjustment rule expression is as follows:

[0044] ΔE dynamic =0.15·ΔP decoy +0.10·Δf decoy +0.05·ΔΓ

[0045] Parameter explanation, ΔE dynamic is the change of dynamic evaluation index; ΔP decoy is the change in transmit power; Δf decoy is the change of frequency characteristics; ΔΓ is the change of reflection coefficient;

[0046] Interval 3, E dynamic ∈[5,7), this interval indicates that the simulated decoy parameters have a greater impact on beamforming, accounting for more than 25%; the transmission power P decoy Between 10 and 15 dBm, the relative distance Δr is between 10 and 20 meters; set E dynamic The threshold is 6, and the interference intensity is dynamically judged and adjusted; when E dynamic When it is less than 6, make adjustments within 30%; when E dynamic When the value is between 6 and 7, make an adjustment of more than 30%; the change of each parameter has an impact on E dynamic The impact is significant;

[0047] The dynamic index adjustment rule expression is as follows:

[0048] ΔE dynamic =0.2·ΔP decoy +0.15·Δf decoy +0.1·ΔΓ

[0049] Parameter explanation: ΔE dynamic is the change of dynamic evaluation index; ΔP decoyis the change in transmit power; Δf decoy is the change of frequency characteristics; ΔΓ is the change of reflection coefficient;

[0050] Interval 4, E dynamic ∈[7,10], this interval indicates that the simulated decoy parameters have a great influence on beamforming; the influence accounts for more than 65%; the transmission power P decoy More than 15dBm, relative distance Δr is between 0 and 10 meters; set E dynamic The threshold is 8.5, and the interference intensity is dynamically judged and adjusted to the maximum; when E dynamic When it is less than 8.5, make a comprehensive adjustment; when E dynamic When it is greater than or equal to 8.5, the maximum adjustment is made; the parameter change has an impact on E dynamic The impact is huge;

[0051] The dynamic index adjustment rule expression is as follows:

[0052] ΔE dynamic =0.25·ΔP decoy +0.20·Δf decoy +0.15·ΔΓ

[0053] Parameter explanation, ΔE dynamic is the change of dynamic evaluation index; ΔP decoy is the change in transmit power; Δf decoy is the change in frequency characteristics; ΔΓ is the change in reflection coefficient.

[0054] A coherent interference device for inverse synthetic aperture radar image destruction, the device is used to execute the coherent interference method for inverse synthetic aperture radar image destruction, comprising:

[0055] Data interception module: used to release several groups of simulated baits in the electromagnetic wave coverage area of ​​the radar to be interfered. After the simulated baits intercept the electromagnetic wave signals emitted by the radar to be interfered, they perform signal analysis to obtain the electromagnetic wave characteristic data of the radar to be interfered, and store the data. The electromagnetic wave characteristic data includes the operating frequency and pulse width of the electromagnetic wave signal;

[0056] Data modulation interference module: used to obtain and store intercepted electromagnetic wave characteristic data and perform phase modulation and auxiliary modulation in sequence, then select an antenna array of simulated bait as a reference array, and collect the relative index of all antenna arrays of simulated bait relative to the reference array, the relative index includes relative position, relative phase and relative amplitude data;

[0057] Adaptive adjustment module: used to analyze and process the relative indexes of all simulated decoys using an adaptive beamforming algorithm to generate a first adjustment strategy for adjusting the transmission parameters of the simulated decoy antenna array, and at the same time, analyze and process the electromagnetic wave characteristic data to generate an interference noise signal;

[0058] Index evaluation module: used to collect, analyze and process the self-characteristic parameters of the simulated bait, generate a dynamic evaluation index for dynamically adjusting the first adjustment strategy, and the dynamic evaluation index can generate the final emission parameters of each simulated bait in a dynamic adjustment manner. The self-characteristic parameters include the physical position, relative distance, reflection coefficient, emission power, frequency characteristics and modulation parameters of the simulated bait;

[0059] Transmitting module: used to simulate the decoy to generate a modulated signal based on the final transmission parameters, and after a delay of a specific length of time, simulate the decoy to synchronously transmit electromagnetic waves generated based on the interference noise signal and the modulated signal to the radar to be interfered.

[0060] Compared with the prior art, the present invention has the following beneficial effects:

[0061] 1. Through radio frequency storage, delayed forwarding and modulation technology, the enemy radar imaging capability can be effectively interfered with and destroyed. The data interception module releases simulated bait to intercept and store the enemy radar electromagnetic wave characteristics, including frequency, operating frequency, and pulse width; delayed forwarding changes the signal timing characteristics, and the data modulation interference module changes the echo signal frequency and phase through phase modulation PM and auxiliary modulation; the adaptive adjustment module optimizes the transmission direction and characteristics of the interference signal, and the index evaluation module dynamically adjusts the strategy, the interference noise signal reduces the signal-to-noise ratio, and blurs the enemy imaging;

[0062] 2. The simulated decoy released by the warhead has two working modes. The first is the noise working mode, which destroys the image by generating noise and reduces the signal-to-noise ratio. The second is the modulation mode, which receives and analyzes the characteristics of enemy radar waves through simulated decoys, stores signals using optical fiber RF signal storage technology, modulates and amplifies them and forwards them, further optimizes the emission direction and characteristics of the interference signal through the adaptive adjustment module, and uses the index evaluation module to dynamically adjust the strategy to improve the effect of blurring the warhead imaging. This strategy prevents the enemy from accurately identifying and tracking missile warheads through electromagnetic wave interference and misleading, significantly improving the missile's strike success rate and survivability. BRIEF DESCRIPTION OF THE DRAWINGS

[0063] Figure 1 It is a schematic diagram of the overall method flow of the present invention;

[0064] Figure 2 This is a block diagram of the system modules of the present invention. DETAILED DESCRIPTION

[0065] In order to make the objectives, technical solutions and advantages of the present invention more clearly understood, the present invention is further described in detail below in conjunction with specific embodiments.

[0066] It should be noted that, unless otherwise defined, the technical terms or scientific terms used in the present invention should be understood by people with ordinary skills in the field to which the present invention belongs. The words "first", "second" and similar words used in the present invention do not indicate any order, quantity or importance, but are only used to distinguish different components. "Include" or "comprise" and similar words mean that the elements or objects appearing before the word include the elements or objects listed after the word and their equivalents, without excluding other elements or objects. "Connect" or "connected" and similar words are not limited to physical or mechanical connections, but may include electrical connections, whether direct or indirect. "Up", "down", "left", "right" and the like are only used to indicate relative positional relationships. When the absolute position of the described object changes, the relative positional relationship may also change accordingly.

[0067] Embodiment 1:

[0068] See also Figure 1 , the present invention provides a technical solution:

[0069] A coherent interference method for inverse synthetic aperture radar image destruction, the specific steps comprising:

[0070] Step S1, releasing a plurality of groups of simulated decoys in the electromagnetic wave coverage area of ​​the radar to be interfered, and performing signal analysis after the simulated decoys intercept the electromagnetic wave signal emitted by the radar to be interfered to obtain the electromagnetic wave characteristic data of the radar to be interfered, and storing the data, wherein the electromagnetic wave characteristic data includes the operating frequency and pulse width of the electromagnetic wave signal;

[0071] Step S2, acquiring and storing the intercepted electromagnetic wave characteristic data and performing phase modulation and auxiliary modulation in sequence, then selecting an antenna array of the simulated bait as a reference array, collecting relative indexes of the antenna arrays of all simulated baits relative to the reference array, wherein the relative indexes include relative position, relative phase and relative amplitude data;

[0072] Step S3, using an adaptive beamforming algorithm to analyze and process the relative indexes of all simulated decoys to generate a first adjustment strategy for adjusting the simulated decoy antenna array transmission parameters, and at the same time, analyzing and processing the electromagnetic wave characteristic data to generate an interference noise signal;

[0073] Step S4, collecting the self-characteristic parameters of the simulated bait and analyzing and processing them to generate a dynamic evaluation index for dynamically adjusting the first adjustment strategy, the dynamic evaluation index can generate the final emission parameters of each simulated bait in a dynamic adjustment manner, the self-characteristic parameters include the physical position, relative distance, reflection coefficient, emission power, frequency characteristics and modulation parameters of the simulated bait;

[0074] Step S5, the simulated decoy generates a modulation signal according to the final transmission parameters, and after a delay of a specific time length, the simulated decoy synchronously transmits electromagnetic waves generated based on the interference noise signal and the modulation signal to the radar to be interfered.

[0075] Embodiment 2:

[0076] Further illustrating on the basis of the first embodiment, the simulated decoy realizes the function of receiving and sending electromagnetic waves through a preset antenna; and the simulated decoy stores the received enemy radar electromagnetic waves through a preset radio frequency memory, and the radio frequency memory uses optical fiber radio frequency signal storage technology to store the received electromagnetic wave characteristic data;

[0077] The releasing of a plurality of simulated decoys that can be covered by electromagnetic waves of enemy radars includes arranging a plurality of simulated decoys in a target area, activating a signal interception device of the simulated decoys, and monitoring electromagnetic waves emitted by the enemy radar in real time; by arranging a plurality of simulated decoys, the coverage of signal interception is enhanced to ensure that as much electromagnetic wave characteristic data of the enemy radar as possible can be obtained;

[0078] The simulated decoys are specifically: a large number of inflated balloons are released simultaneously as simulated decoys when the missile is launched. The surfaces of these simulated decoys are covered with aluminum powder, simulating real warheads to confuse enemy radars;

[0079] The simulated decoy released by the warhead has two working modes. The first is the noise working mode, which destroys the image by generating noise and reduces the signal-to-noise ratio;

[0080] The second is the modulation mode, which specifically receives and analyzes the enemy's radar wave characteristics by simulating bait, stores the signal using fiber-optic radio frequency signal storage technology, modulates and amplifies it and then forwards it, blurring the warhead image. This strategy prevents the enemy from accurately identifying and tracking the missile warhead through electromagnetic wave interference and misleading, significantly improving the missile's strike success rate and survivability.

[0081] The phase modulation and auxiliary modulation of the second modulation mode specifically include the following contents:

[0082] Phase modulation PM is a modulation method that transmits information by changing the instantaneous phase of the signal. Before the delayed signal is ready to be transmitted again, the stored intercepted electromagnetic wave characteristic data is phase modulated; the calculation formula is:

[0083] S1(t)=Acos(ω c t+k p m(t)+φ0)

[0084] Where S1(t) is the modulated signal, which changes with time t, A is the signal amplitude, ω c is the carrier angular frequency, is the signal angular frequency when not modulated, k p is the phase modulation sensitivity, which indicates the influence of the baseband signal m(t) on the instantaneous phase change. m(t) is the baseband signal, which is an audio signal used to modulate the phase of the carrier and changes with time t. φ0 is the initial phase, which is the phase state at the beginning of modulation.

[0085] Through phase modulation, the instantaneous phase of the signal changes with the baseband signal m(t), so that the phase characteristics of the echo signal are changed, making it more difficult for the enemy radar to identify and process. Phase modulation effectively increases the complexity of the signal and improves the signal's anti-interference ability.

[0086] Auxiliary modulation includes amplitude modulation AM and frequency modulation FM. Amplitude modulation AM is a modulation method that transmits information by changing the amplitude of the signal. Before the delayed signal is ready to be transmitted again, the stored intercepted electromagnetic wave characteristic data is amplitude modulated; the calculation formula is:

[0087] S2(t)=[A c +k a m(t)]cos(ω c t+φ0)

[0088] Where S2(t) is the modulated signal, which changes with time t, A c is the carrier amplitude, is the signal amplitude when not modulated, k a is the amplitude modulation sensitivity, which is the influence of the baseband signal m(t) on the signal amplitude change, where m(t) is the baseband signal and φ0 is the initial phase;

[0089] Through amplitude modulation, the amplitude of the signal changes with the baseband signal m(t), so that the amplitude characteristics of the echo signal are changed, making it more difficult for the enemy radar to identify and process. Amplitude modulation can effectively increase the bandwidth of the signal and improve the signal's anti-interference ability;

[0090] The frequency modulation FM is a modulation method that transmits information by changing the instantaneous frequency of the signal. The calculation formula is:

[0091]

[0092] Where S3(t) is the modulated signal, which varies with time t, A is the signal amplitude, f(τ) is the instantaneous frequency at time τ, and φ0 is the initial phase;

[0093] The instantaneous frequency f(τ) is determined by the baseband signal m(t) and is expressed as: f(τ) = f c +k f m(τ), where f c is the carrier frequency, is the signal frequency when not modulated, k f is the frequency modulation sensitivity, which indicates the influence of the baseband signal m(t) on the instantaneous frequency change, where m(τ) is the baseband signal;

[0094] Through frequency modulation, the instantaneous frequency of the signal changes with the baseband signal m(t), so that the frequency characteristics of the echo signal are changed, making it more difficult for enemy radar to identify and process. Frequency modulation effectively increases the bandwidth of the signal and improves the signal's anti-interference ability.

[0095] Embodiment three:

[0096] Further illustrating on the basis of the second embodiment, the relative indexes of all simulated decoys are analyzed and processed using an adaptive beamforming algorithm to generate a first adjustment strategy for adjusting the simulated decoy antenna array transmission parameters, which specifically includes the following contents:

[0097] The adaptive beamforming algorithm described in this embodiment adopts the SINR maximization adaptive beamforming algorithm (Max-SINRAdaptiveBeamformingAlgorithm). The adaptive antenna array can dynamically optimize the transmission direction and signal characteristics, making the interference signal more difficult to be detected and identified by the enemy radar, thereby enhancing the interference effect;

[0098] The relative position of the antenna array is marked as r, and the position vector of the antenna element is represented by r i =[x i ,y i ,z i ], where i represents the i-th antenna element;

[0099] The relative phase of the antenna array is denoted as φ, and the relative phase of each antenna element is denoted as φ i , where i represents the i-th antenna element;

[0100] The relative amplitude of the antenna array is marked as A, and the relative amplitude of each antenna element is represented by A i , where i represents the i-th antenna element;

[0101] Set the adaptive beamforming weight vector to w:

[0102] The weight vector of the antenna array is expressed as w = [w1, w2, ..., w N ], where N is the number of antenna elements, w i is the weight of the ith antenna element;

[0103] Set the signal covariance matrix to R, which represents the covariance matrix of the received signal, calculated using the received signal data;

[0104] Use the following optimization formula to optimize the transmission direction and signal characteristics of the interference signal:

[0105]

[0106] Among them, w opt is the optimal weight vector; R is the signal covariance matrix; D is the interference covariance matrix; w is the weight vector; w H R -1 w and w H Dw are all inner product forms, where w H R -1 w represents the inner product of the weight vector w and the inverse matrix of the signal covariance matrix R, and w H Dw represents the inner product of the weight vector w and the interference covariance matrix D. The ratio of these two inner products is maximized to find the optimal weight vector w opt , thereby optimizing the emission direction and signal characteristics of the interference signal;

[0107] The specific optimization steps are as follows:

[0108] 1. Collect signal data and calculate the signal covariance matrix R;

[0109] 1.1 Collect signal data:

[0110] At each antenna element of the antenna array, the received signal sample data is collected. Assume that the signal received by each antenna element is s i (t), where i represents the i-th antenna element and t represents time;

[0111] 1.2 Construct signal sample matrix:

[0112] The signal sample data received by all antenna elements are constructed into a matrix S, where N is the number of antenna elements and T is the number of sampling points in the sampling time window.

[0113]

[0114] 1.3 Calculate the signal covariance matrix R:

[0115] According to the signal sample matrix S, calculate the signal covariance matrix R:

[0116]

[0117] Among them, S H is the conjugate transpose of S;

[0118] 2. Collect interference signal data and calculate the interference covariance matrix D;

[0119] 2.1 Collect interference signal data:

[0120] At each antenna element of the antenna array, sample data of the received interference signal is collected. Assume that the interference signal received by each antenna element is d i(t) ;

[0121] 2.2 Construct interference signal sample matrix:

[0122] The interference signal sample data received by all antenna elements is constructed into a matrix D, where

[0123]

[0124] 2.3 Calculate the interference covariance matrix D:

[0125] According to the interference signal sample matrix D, calculate the interference covariance matrix D:

[0126]

[0127] 3. Use the above formula to calculate the optimal weight vector w opt ;

[0128] 3.1 Define optimization goals:

[0129] The optimization goal of the optimal weight vector is to maximize the ratio of signal covariance to interference covariance:

[0130]

[0131] 3.2 Construct Lagrangian function:

[0132] In order to solve the optimal weight vector, construct the Lagrangian function:

[0133] L(w,λ)=w H R -1 wλ(w H Dw1)

[0134] Where λ is the Lagrange multiplier;

[0135] 3.3 Obtain the optimal weight vector:

[0136] Taking the partial derivative of the Lagrangian function and setting it equal to zero, we get the solution to the optimization problem:

[0137]

[0138] The solution is:

[0139] R -1 w=λDw

[0140] Multiply both sides by R:

[0141] w=λRDw

[0142] This problem is transformed into an eigenvalue problem:

[0143]

[0144] The optimal weight vector w opt is the eigenvector corresponding to the maximum eigenvalue of the generalized eigenvalue problem RDw=μw;

[0145] 4. Adjust the relative phase φ and amplitude A of the antenna array to meet the optimal weight vector w opt Result;

[0146] 4.1 Initialize phase and amplitude:

[0147] According to the calculated optimal weight vector w opt , initialize the phase φ and amplitude A;

[0148] 4.2 Adjust the phase:

[0149] For the i-th antenna element, adjust its phase φ i Let it be the optimal weight vector w opt The phase coincidence is:

[0150] φ i = arg(w opt,i )

[0151] 4.3 Adjustment range:

[0152] For the i-th antenna element, adjust its amplitude A i Let it be the optimal weight vector w opt The amplitude is consistent:

[0153] A i =|w opt,i |

[0154] 4.4 Implementation adjustments:

[0155] Adjust the phase and amplitude of the antenna array to meet the optimal weight vector w optThe result ensures that the antenna array achieves the best signal reception performance and interference suppression effect.

[0156] Embodiment 4:

[0157] Further explanation is given on the basis of Example 3, the characteristic parameters of the simulated bait are collected and analyzed and processed to generate a dynamic evaluation index for dynamically adjusting the first adjustment strategy. The dynamic evaluation index can generate the final emission parameters of each simulated bait in a dynamic adjustment manner. The characteristic parameters include the physical position, relative distance, reflection coefficient, emission power, frequency characteristics and modulation parameters of the simulated bait, specifically including the following contents:

[0158] The physical location of the simulated bait is marked as r decoy :

[0159] The position vector of the bait is denoted as r decoy =[x decoy ,y decoy ,z decoy ];

[0160] The relative distance to the simulated bait is marked as Δr:

[0161] The distance vector between the decoy and the antenna array is denoted as Δr = r decoy r array , where r array is the center position vector of the antenna array;

[0162] The reflection coefficient of the simulated bait is marked as Γ. The reflection ability of the bait is determined by its material and surface area;

[0163] The transmission power of the simulated bait is marked as P decoy , which is the power of the simulated decoy emission signal;

[0164] The frequency characteristic of the simulated bait is marked as f decoy , which represents the frequency distribution of the simulated decoy signal, used to match the receiving frequency of the antenna array;

[0165] The modulation parameter of the simulated bait is marked as M decoy , which represents the modulation parameter of the simulated bait signal, specifically the modulation frequency;

[0166] Define the dynamic evaluation index as E dynamic , the calculation formula is as follows:

[0167]

[0168] The parameters are explained as follows:

[0169] E dynamicis the dynamic evaluation index; α i′ is the weight of the i′th parameter, there are N′ parameters in total;

[0170] f i′ (r decoy ,Δr,Γ,P decoy ,f decoy ,M decoy ) is the complex summation function of the i′th parameter; β is a parameter for adjusting the steepness of the exponential function, 0.12≤β≤0.68, β is determined by the expert group based on experimental data; controls the rate of change of the exponential function; P decoy is the emission power of the simulated decoy; P0 is the baseline value of the emission power, which is used to normalize the emission power; e is a natural constant; γ is the adjustment parameter of the normalization function, which is used to adjust the degree of normalization;

[0171] g j (r decoy ,Δr,Γ,P decoy ,f decoy ,M decoy ) is the complex information filtering function of the jth parameter, with a total of M parameters;

[0172] For the complex sum function f i′ :

[0173]

[0174] For complex information filtering function g j :

[0175]

[0176] Δr[l] represents the lth element of the position change vector Δr;

[0177] represents f decoy and M decoy The negative power of the square of the product of [l], i.e., the exponential decay function;

[0178] α jl represents the weight of the lth sub-parameter of the jth parameter;

[0179] In order to transform the frequency characteristic f decoy and modulation parameter M decoy Integrated into the dynamic evaluation index E dynamic In the calculation formula, it is necessary to make detailed quantitative definitions of these two parameters and embed their mathematical expressions into the formula; the following is the quantitative definition of these two parameters and their application in the formula:

[0180] 1. Frequency characteristics f decoy :

[0181] Assume f decoy is a scalar, indicating the center frequency of the simulated decoy signal, defined as f decoy for:

[0182] f decoy =f c

[0183] The center frequency fc is determined by analyzing the spectrum of the signal emitted by the simulated bait. In practical applications, Fourier Transform is used to analyze the spectrum of the signal to determine the center frequency of the signal. The mathematical expression is as follows:

[0184] f c = argmax f |F{s(t)}(f)|

[0185] Where s(t) is the time domain signal of the simulated bait emission, F{s(t)}(f) represents the frequency domain representation obtained after Fourier transform of s(t), which means finding the frequency with the largest spectrum amplitude among all existing frequencies f, and f is the frequency variable. By finding the maximum amplitude point in the spectrum, the center frequency fc is determined;

[0186] Among them, f c is the center frequency of the signal, at E dynamic In the formula, f decoy Affects the matching degree and spectral characteristics of the signal; in the complex summation function f i′ In, f decoy With the modulation parameter M decoy Together they are used to compute the following logarithmic functions:

[0187] log(f decoy ·M decoy [k])

[0188] This represents the logarithm of the product of the frequency characteristic and the modulation parameter and is used to evaluate the frequency and modulation characteristics of the signal;

[0189] 2. Modulation parameter M decoy :

[0190] Assume M decoy is a vector representing the modulation parameters of the simulated decoy signal, including the modulation type and modulation index. For frequency modulation (FM), define M decoy for:

[0191] M decoy =[mf]

[0192] Among them, m f is the frequency modulation index, in Edynamic In the formula, M decoy In the complex summation function f i′ and complex information filtering function g j There are applications in f i′ In the decoy are used together to calculate the logarithmic function; in g j In , it is used to calculate the following exponential function:

[0193]

[0194] This represents the negative exponent of the square of the product of the frequency characteristic and the modulation parameter, and is used to evaluate the influence of the modulation parameter on the signal characteristics;

[0195] Frequency modulation index m f It is an important parameter of frequency modulation (FM) signal, which describes the rate at which the signal frequency changes over time. f It is calculated by analyzing the frequency offset of the modulated signal and the amplitude of the modulated signal. The mathematical expression is as follows:

[0196]

[0197] Where Δf is the maximum frequency deviation, that is, the maximum value of the frequency change caused by the modulation signal, f m is the frequency of the modulating signal. In practical applications, m is calculated by measuring the frequency of the modulating signal and the corresponding frequency offset. f ;

[0198] According to the calculated dynamic evaluation index E dynamic , adjust the weight vector w of the antenna array:

[0199]

[0200] The specific steps are as follows:

[0201] 1. Initialize the weight vector w and set the initial value of the weight vector according to the initial conditions or empirical values;

[0202] 2. Calculate the signal covariance matrix R based on the received signal data;

[0203] 3. Calculate the interference covariance matrix D based on the received interference signal data;

[0204] 4. Optimize the weight vector:

[0205] The objective function is

[0206] The objective function and the dynamic evaluation index E dynamicCombined, the following new optimization objectives are formed:

[0207]

[0208] 5. Iterative adjustment:

[0209] Use the gradient descent optimization algorithm to iteratively adjust the weight vector w until the objective function converges;

[0210] 6. Apply the optimal weight vector:

[0211] The optimal weight vector w is calculated opt Applied to antenna arrays to adjust the relative phase and amplitude of antennas;

[0212] Set the dynamic evaluation index value range to E dynamic ∈[0,10]; the technical effects of different range values ​​are as follows:

[0213] When E dynamic The closer it is to 0, the smaller the influence of the simulated decoy parameters on beamforming is, and the smaller the adjustment of the optimal weight vector is;

[0214] When E dynamic The closer it is to 10, the greater the influence of the simulated decoy parameters on beamforming, and the greater the adjustment of the optimal weight vector;

[0215] The formula design dynamically adjusts the weight vector of the antenna array through a composite summation and normalization function combined with an exponential function to ensure the optimization of signal reception performance under different decoy conditions; the complex summation function and the complex information filtering function process the decoy parameters through weighted and nonlinear normalization respectively to ensure that the effect of parameter changes on the dynamic evaluation index has interactive and nonlinear characteristics;

[0216] Through this design, the formula not only avoids the limitations of simple linear weight combinations, but also ensures that under various decoy parameter changes, the dynamic evaluation index can accurately reflect their impact on beamforming, thereby achieving adaptive optimal weight vector adjustment.

[0217] Embodiment five:

[0218] Further explanation is given on the basis of Example 4. dynamic ∈[0,10] is divided into the following intervals, and the judgment criteria and rules, as well as the interaction rules are described for each interval;

[0219] Interval 1, E dynamic ∈[0,2); In this interval, the influence of simulated decoy parameters on beamforming is minimal; the transmission power P decoy Below 5dBm, the relative distance Δr exceeds 50 meters, resulting in weak interference signals;

[0220] In terms of technical effect, the antenna array has low adjustment requirements and the existing configuration can be maintained. The system makes judgments based on the set thresholds. dynamic When it is less than 1, no adjustment is required; when E dynamic When it is between 1 and 2, fine-tune; parameter changes have an impact on E dynamic The impact is small, ensuring the stable operation of the system; this reflects the stability and efficiency of the system under low interference conditions; the specific description is as follows:

[0221] In E dynamic When the value is between 0 and 2, it means that the simulated decoy parameters have little effect on beamforming; within this range, the simulated decoy parameters detected by the system, such as the physical position r decoy , relative distance Δr, reflection coefficient Γ, transmission power P decoy , frequency characteristics f decoy and modulation parameter M decoy are all at a low or steady-state level; for example, the emission power P of the decoy decoy When the signal level is lower than 5 dBm and the relative distance Δr exceeds 50 meters, the interference signal to the antenna array is very weak. In terms of technical effect, the antenna array has low adjustment requirements and the original configuration can basically meet the signal reception requirements. The weight vector w does not need to be adjusted significantly.

[0222] The judgment criteria and rules are as follows:

[0223] In this interval, set the threshold E threshold =1; when E dynamic When it is less than 1, it means that the influence of the simulated bait is extremely weak, and the change rate of the relative phase φ and amplitude A of the antenna array is within 3%, which is basically unchanged; when E dynamic When the value is greater than or equal to 1 but less than 2, it indicates that the simulated decoy has a slight impact on the beamforming and the antenna array needs to be slightly adjusted. For example, if the relative phase deviation exceeds 5 degrees or the transmit power changes by more than 10%, fine-tuning is required. The fine-tuning measure is to adjust the corresponding parameters within 8%. Setting such a threshold can effectively manage system resources and avoid unnecessary frequent adjustments.

[0224] The interaction rules are described as follows:

[0225] In this range, the changes in various parameters have little impact on the dynamic evaluation index; specifically, when the physical position r decoy When the transmission power P changes by 10%, the change of Δr does not exceed 5%, and the change of reflection coefficient Γ is less than 2%. decoy Increase by 20%, E dynamic will increase by 0.5; the frequency characteristic f decoy and modulation parameter M decoyThe change of the index is also limited; when any parameter changes by more than 10%, the change of other parameters does not exceed 5%, ensuring the stability of the overall technical effect, avoiding system overreaction, and ensuring effective interference suppression and signal reception in actual operation; the dynamic index adjustment rules are as follows:

[0226] ΔE dynamic =0.1·ΔP decoy +0.05·Δf decoy +0.02·ΔΓ

[0227] Parameter explanation, ΔE dynamic is the change of dynamic evaluation index; ΔP decoy is the change in transmit power; Δf decoy is the change of frequency characteristics; ΔΓ is the change of reflection coefficient;

[0228] Interactive content description:

[0229] In this range, the change of parameters has an impact on E dynamic The influence of the transmission power P is small. decoy Increase by 20%, E dynamic It will increase by 0.5, and changes in other parameters will also have corresponding effects, but the overall impact is limited;

[0230] Interval 2, E dynamic ∈[2,5), in this interval, the simulated decoy parameters have a 10% to 25% effect on beamforming; the transmit power P decoy Between 5 and 10 dBm, the relative distance Δr is between 20 and 50 meters; by setting E dynamic The threshold is 3.5, and the interference intensity is dynamically judged and adjusted; when E dynamic When it is less than 3.5, adjust the parameters within 15%; when E dynamic When the value is between 3.5 and 5, the significant adjustment is within 35%; the parameter change has an impact on E dynamic The impact is more obvious, ensuring that the system effectively adjusts the antenna array under medium interference conditions, improves signal reception quality, and achieves flexible interference suppression; the specific description is as follows:

[0231] In E dynamic When the value is between 2 and 5, it means that the simulated decoy parameters have a certain influence on the beamforming; at this time, the physical position of the decoy r decoy There is frequent activity within the coverage area of ​​the antenna array, the relative distance Δr is between 20 and 50 meters, the reflection coefficient Γ is high, and the transmission power P decoy Between 5 and 10dBm, the frequency characteristic f decoy and modulation parameter M decoyThe changes are obvious; in terms of technical effects, the relative phase and amplitude of the antenna array need to be adjusted appropriately to optimize signal reception and interference suppression effects; the adjustment strategy needs to dynamically respond to changes in the decoy to ensure signal quality;

[0232] Judging criteria and rules:

[0233] In this interval, set the threshold E threshold =3.5; when E dynamic When it is less than 3.5, it means that the influence of the simulated bait is moderate, and the antenna array needs to be adjusted appropriately; the change range of the relative phase φ of the antenna array does not exceed 15 degrees, and the adjustment range of the transmission power does not exceed 20%; when E dynamic When it is greater than or equal to 3.5 but less than 5, it means that the simulated decoy has a greater impact and requires a greater adjustment. When the relative phase adjustment exceeds 20 degrees, the transmission power adjustment does not exceed 30%. By setting such a threshold, it is ensured that when the decoy has a greater impact, the system can respond and adjust in time to ensure the realization of the technical effect.

[0234] The interaction rules are described as follows:

[0235] In this range, the changes in various parameters have a significant impact on the dynamic evaluation index; specifically, when the physical position r decoy When a 15% change occurs, Δr changes by 10%, and the reflection coefficient Γ changes by no more than 5%; if the transmission power P decoy Increase by 30%, E dynamic will increase by 1.5; the frequency characteristic f decoy and modulation parameter M decoy The change of has a greater impact on the index. When the frequency characteristic changes by 20% and the modulation parameter changes by 15%, the dynamic index will increase by 2; when each parameter changes by more than 15%, the change of other parameters does not exceed 10%, ensuring the balance of the overall technical effect and ensuring the rapid response and timely adjustment of the system; the dynamic index adjustment rule expression is as follows:

[0236] ΔE dynamic =0.15·ΔP decoy +0.10·Δf decoy +0.05·ΔΓ

[0237] Parameter explanation, ΔE dynamic is the change of dynamic evaluation index; ΔP decoy is the change in transmit power; Δf decoy is the change of frequency characteristics; ΔΓ is the change of reflection coefficient;

[0238] In this range, the change of parameters has an impact on E dynamic The influence of the transmission power P decoy Increase by 30%, Edynamic Will increase by 1.5, other parameter changes will also significantly affect E dynamic ;

[0239] Interval 3, E dynamic ∈[5,7), this interval indicates that the simulated decoy parameters have a greater impact on beamforming, accounting for more than 25%; the transmission power P decoy Between 10 and 15 dBm, the relative distance Δr is between 10 and 20 meters; set E dynamic The threshold is 6, and the interference intensity is dynamically judged and adjusted; when E dynamic When it is less than 6, make adjustments within 30%; when E dynamic When the value is between 6 and 7, make an adjustment of more than 30%; the change of each parameter has an impact on E dynamic The influence is significant, ensuring that the system can adjust the antenna array to a large extent, maintain the best signal reception performance under high interference conditions, and achieve efficient interference suppression; the specific description is as follows:

[0240] In E dynamic When the value is between 5 and 7, it means that the simulated decoy parameters have a greater impact on beamforming; within this range, the physical position r of the simulated decoy decoy In the close range of the antenna array, the relative distance Δr is between 10 and 20 meters, the reflection coefficient Γ is high, and the transmission power P decoy Between 10 and 15 dBm, the frequency characteristic f decoy and modulation parameter M decoy The changes are significant; in terms of technical effects, the relative phase and amplitude of the antenna array need to be adjusted significantly, with an adjustment range of more than 45% to ensure optimal signal reception and interference suppression effects; the system needs to respond in real time and dynamically adjust strategies to deal with high interference situations;

[0241] Judging criteria and rules:

[0242] In this range, set E dynamic The threshold is 6; when E dynamic When it is less than 6, it means that the simulated bait has a large impact and the antenna array needs to be significantly adjusted; for example, the change range of the relative phase φ of the antenna array is between 20 and 30 degrees, and the adjustment range of the transmission power is between 30% and 50%; when E dynamic When it is greater than or equal to 6 but less than 7, it means that the simulated decoy impact is very significant and requires the maximum adjustment; for example, the relative phase adjustment amplitude exceeds 30 degrees, and the transmission power adjustment amplitude is between 50% and 70%. By setting such a threshold, it is ensured that in the case of high interference, the system can make the maximum response adjustment in time to ensure the realization of the technical effect;

[0243] Interaction rules description:

[0244] In this range, the changes in various parameters have a significant impact on the dynamic evaluation index; specifically, when the physical position r decoy When the transmission power P changes by 20%, Δr changes by 15%, and the reflection coefficient Γ changes by no more than 10%. decoy Increase E by 50% dynamic Will increase by 2; frequency characteristic f decoy and modulation parameter M decoy The change of has a great impact on the index. When the frequency characteristic changes by 30% and the modulation parameter changes by 20%, the dynamic index will increase by 3; when each parameter changes by more than 20%, the change of other parameters does not exceed 15%, ensuring the balance of the overall technical effect, ensuring that the system can stably cope with high interference environments, and provide effective signal reception and interference suppression; the dynamic index adjustment rule expression is as follows:

[0245] ΔE dynamic =0.2·ΔP decoy +0.15·Δf decoy +0.1·ΔΓ

[0246] Parameter explanation: ΔE dynamic is the change of dynamic evaluation index; ΔP decoy is the change in transmit power; Δf decoy is the change of frequency characteristics; ΔΓ is the change of reflection coefficient;

[0247] In this range, the change of each parameter has an impact on E dynamic The influence of the transmission power P is significant. decoy Increase E by 50% dynamic will increase by 2, and other parameter changes will also affect E dynamic Have a significant impact;

[0248] Interval 4, E dynamic ∈[7,10], this interval indicates that the simulated decoy parameters have a great influence on beamforming; the transmit power P decoy More than 15dBm, relative distance Δr is between 0 and 10 meters; set E dynamic The threshold is 8.5, and the interference intensity is dynamically judged and adjusted to the maximum; when E dynamic When it is less than 8.5, make a comprehensive adjustment; when E dynamic When it is greater than or equal to 8.5, the maximum adjustment is made; the parameter change has an impact on E dynamic The impact is huge, ensuring that the system can adjust the antenna array to the maximum extent under extreme interference conditions, optimize signal reception, and provide the strongest interference suppression capability;

[0249] The specific description is as follows:

[0250] In E dynamicWhen the value is between 7 and 10, it means that the simulated bait parameters have a great influence on beamforming; within this range, the physical position r of the simulated bait decoy In the very close range of the antenna array, the relative distance Δr is between 0 and 10 meters, the reflection coefficient Γ is very high, and the transmission power P decoy More than 15dBm, frequency characteristics f decoy and modulation parameter M decoy The changes are dramatic; in terms of technical effects, the relative phase and amplitude of the antenna array need to be adjusted to the greatest extent to ensure that the best signal reception and interference suppression effects can be maintained under extremely high interference conditions;

[0251] Judging criteria and rules:

[0252] In this range, set E dynamic The threshold is 8.5; when E dynamic When it is less than 8.5, it means that the simulated bait has a great impact and the antenna array needs to be fully adjusted; the relative phase φ of the antenna array is adjusted to a range of 30 to 40 degrees, and the transmission power is adjusted to a range of 50% to 70%; when E dynamic When it is greater than or equal to 8.5, it means that the simulated decoy influence has reached the highest level and the maximum adjustment is required; for example, the relative phase adjustment exceeds 40 degrees and the transmit power adjustment exceeds 70%. By setting such a threshold, it is ensured that the system can make the most efficient adjustments under extremely high interference conditions and ensure the realization of technical effects;

[0253] Interaction rules description:

[0254] In this range, the changes in various parameters have a great impact on the dynamic evaluation index; specifically, when the physical position r decoy When the transmission power P changes by 25%, Δr changes by 20%, and the reflection coefficient Γ changes by no more than 15%. decoy Increase by 70%, E dynamic will increase by 2.5; the frequency characteristic f decoy and modulation parameter M decoy The change of has a great impact on the index. When the frequency characteristic changes by 40% and the modulation parameter changes by 30%, the dynamic index will increase by 4; when each parameter changes by more than 25%, the change of other parameters does not exceed 20%, ensuring the ultimate optimization of the overall technical effect, ensuring that the system can operate stably under extreme interference conditions, and providing the strongest signal reception and interference suppression capabilities; the dynamic index adjustment rule expression is as follows:

[0255] ΔE dynamic =0.25·ΔP decoy +0.20·Δf decoy +0.15·ΔΓ

[0256] Parameter explanation, ΔE dynamic is the change of dynamic evaluation index; ΔP decoy is the change in transmit power; Δf decoy is the change of frequency characteristics; ΔΓ is the change of reflection coefficient;

[0257] In this range, the change of parameters has an impact on E dynamic The influence of the transmission power P decoy Increase by 70%, E dynamic It will increase by 2.5; other parameter changes also have a great impact, ensuring the stable operation of the system under extreme interference.

[0258] Embodiment six:

[0259] Further explanation based on Example 5, this example aims to verify the actual effect of the adaptive beamforming algorithm in optimizing the interference signal of the antenna array simulating bait, and the experiment is specifically divided into the following steps:

[0260] Test preparation:

[0261] Choose an open test site and make sure there are no large metal objects around to interfere with the signal;

[0262] Prepare an antenna array containing 16 antenna elements, the antenna array layout is a 4x4 matrix, and each antenna element has an independent transmission power adjustment function;

[0263] Equipped with high-precision signal acquisition equipment to collect the received signals and interference signals of the antenna array in real time;

[0264] Signal delay and simulated bait settings:

[0265] The collected interference signals are appropriately delayed to simulate the multipath effects and delayed waves in a real battlefield environment;

[0266] Set the relative position r, relative phase φ and amplitude A data of the antenna array of the simulated bait. The specific setting parameters are as follows:

[0267] Initial physical location: r decoy = [10, 20, 5] meters;

[0268] Initial relative phase: φ = [0, π / 6, π / 4, π / 3];

[0269] Initial transmit power: P decoy =10dBm;

[0270] Adaptive beamforming algorithm application:

[0271] Use the Max-SINR Adaptive Beamforming Algorithm to adaptively adjust the antenna array; the specific steps are as follows:

[0272] Collect the relative position, relative phase and relative amplitude data of the antenna array.

[0273] Calculate the signal sample matrix S and signal covariance matrix R;

[0274] Calculate the interference covariance matrix D;

[0275] By solving the optimization formula Get the optimal weight vector w opt ;

[0276] According to the optimal weight vector w opt Adjust the transmit parameters of the antenna array, including relative phase and amplitude;

[0277] Dynamic evaluation index calculation:

[0278] Collect the characteristic parameters of the simulated bait, including physical position, relative distance, reflection coefficient, transmission power, frequency characteristics, and modulation parameters;

[0279] According to the collected data, calculate the dynamic evaluation index E dynamic ;

[0280] The dynamic evaluation index is used to evaluate the interference effect of the decoy on the antenna array and dynamically adjust the first adjustment strategy;

[0281] Test data collection and comparison:

[0282] Record the transmission parameters and received signal quality of the antenna array under different adjustment strategies;

[0283] Compare the signal reception quality before and after the adjustment to evaluate the effectiveness of the adaptive beamforming algorithm;

[0284] The following is an example of test data recorded in an Excel spreadsheet:

[0285] Table 1

[0286]

[0287]

[0288] By analyzing the test data of the five simulated decoys in the table, we can clearly see the effect of the adaptive beamforming algorithm on the antenna array adjustment under different simulated decoy parameters; the following is a detailed analysis:

[0289] 1. Comparison of initial parameters and adjusted parameters of simulated bait:

[0290] Simulated bait 1: initial position [10,20,5] meters, initial phase [0,30,45,60] degrees, transmit power 10dBm, dynamic evaluation index 2; after adjustment, phase [0,35,50,65] degrees, transmit power 12dBm, signal reception quality improved to 20dB;

[0291] Simulated bait 2: initial position [15,25,10] meters, initial phase [0,20,40,60] degrees, transmit power 12dBm, dynamic evaluation index 4, adjusted phase [0,25,45,65] degrees, transmit power 14dBm, signal reception quality improved to 18dB;

[0292] Simulated bait 3: initial position [20,30,15] meters, initial phase [0,25,50,75] degrees, transmit power 15dBm, dynamic evaluation index 6, adjusted phase [0,30,55,80] degrees, transmit power 16dBm, signal reception quality improved to 15dB;

[0293] Simulated bait 4: initial position [25,35,20] meters, initial phase [0,30,60,90] degrees, transmit power 18dBm, dynamic evaluation index 8, adjusted phase [0,35,65,95] degrees, transmit power 19dBm, signal reception quality improved to 12dB;

[0294] Simulated bait 5: initial position [30, 40, 25] meters, initial phase [0, 35, 70, 105] degrees, transmit power 20dBm, dynamic evaluation index 10, adjusted phase [0, 40, 75, 110] degrees, transmit power 22dBm, signal reception quality improved to 10dB;

[0295] Beneficial effect analysis:

[0296] 1. The role of dynamic evaluation index in adjusting strategy:

[0297] Dynamic evaluation index E dynamic It reflects the degree of interference of the simulated bait on the antenna array. From the table data, we can see that as E dynamic The adjusted phase and transmission power increased significantly; the dynamic evaluation indexes of simulated bait 1 and simulated bait 5 were 2 and 10 respectively, the adjusted phase changes were 5 degrees and 5 degrees respectively, and the transmission power increased by 2dBm and 2dBm respectively, which shows that the present invention can effectively dynamically adjust the first adjustment strategy according to different simulated bait situations;

[0298] 2. Specific expression of technical effects:

[0299] In E dynamic In the range below 2, refer to the simulated bait 1, the system only needs to fine-tune the phase and transmission power, which can significantly improve the signal reception quality, and the corresponding table data is improved by 20dB;

[0300] In E dynamic In the range of 2 to 5, refer to the simulated bait 2. The system needs to adjust the phase and transmission power appropriately. The signal reception quality is relatively high, and the corresponding table data is improved by 18dB.

[0301] In E dynamic In the range of 5 to 7, refer to simulated bait 3, the system needs significant adjustment, the signal reception quality is good, and the corresponding table data is improved by 15dB;

[0302] In E dynamic In the range of 7 to 10, refer to simulated bait 4 and simulated bait 5. The system needs to be fully and maximally adjusted. The signal reception quality has declined, but it is still significantly better than the unadjusted state. The corresponding table data are improved by 12dB and 10dB respectively.

[0303] Analysis of numerical changes:

[0304] 1. Numerical relationship between phase and transmit power adjustment:

[0305] The weight vector w in the formula opt The changes in the signal / interference covariance matrix R and D directly affect the adjustment of phase and transmit power;

[0306] With E dynamic As the interference level increases, the adjusted phase change and transmit power show a positive correlation trend. The phase adjustments of simulated decoys 1 to 5 are 5 degrees, 5 degrees, 5 degrees, 5 degrees, and 5 degrees, respectively. The transmit power adjustments are 2dBm, 2dBm, 1dBm, 1dBm, and 2dBm, respectively. This shows that as the interference level increases, the system needs a larger adjustment to optimize the received signal.

[0307] 2. Impact of dynamic evaluation index on signal reception quality:

[0308] In the low interference range E dynamic ∈[0,2), the signal reception quality is significantly improved by 20dB;

[0309] In the moderate interference interval E dynamic ∈[2,5), the signal reception quality remains at a high level and is improved by 18dB;

[0310] In the higher interference range E dynamic ∈[5,7), the signal reception quality has decreased, but is still within a good range, with an improvement of 15dB;

[0311] In the extremely high interference zone E dynamic ∈[7,10], the signal reception quality has decreased, and has increased by 12dB and 10dB respectively, but it is still significantly improved compared to the unadjusted state;

[0312] The present invention can dynamically optimize the transmission direction and signal characteristics of the antenna array by using the SINR maximization adaptive beamforming algorithm, making it more difficult for the interference signal to be detected and identified by the enemy radar. This adaptive adjustment ensures that the system can achieve the best signal reception effect under different interference intensities;

[0313] Dynamic evaluation index E dynamic The introduction of enables the system to adjust the first adjustment strategy in real time according to different simulated bait situations. This innovative design ensures that the system is more flexible and adaptable in practical applications.

[0314] The examples record and analyze in detail the adjustment strategies and effect data under different simulated bait parameters, demonstrating the excellent performance of the present invention in practical applications. The specific technical effects and numerical percentages of each interval are quantitatively expressed, further proving the practical effectiveness and innovation of the present invention.

[0315] To sum up, the data in the table clearly demonstrates the adaptive adjustment effect of the present invention under different interference intensities, and reflects the innovation and advantages of the present invention in optimizing the emission direction and signal characteristics of interference signals. At the same time, the introduction of the dynamic evaluation index enables the adjustment strategy to be adjusted dynamically in real time, ensuring the efficiency and flexibility of the system in practical applications.

[0316] Embodiment seven:

[0317] Further explanation based on the sixth embodiment, for the first noise working mode, the analysis and processing of the stored intercepted electromagnetic wave characteristic data to generate an interference noise signal specifically includes the following contents:

[0318] Analyze the stored intercepted electromagnetic wave characteristic data in detail, extract the statistical characteristics of the noise component, and determine the mean μ and variance σ of the noise signal 2 ;

[0319] According to the signal characteristics of the interference target, set the frequency f of the noise signal noise For example, if the target signal is mainly concentrated at 1 GHz, set f noise Set to a value close to 1 GHz, such as 999 MHz;

[0320] Set the amplitude of the noise signal A noise To ensure that the strength of the noise signal is sufficient to interfere with the target signal; Amplitude A noiseThe setting should take into account the strength of the target signal and the desired interference effect;

[0321] Use the following formula to generate a noise signal N(t) with interference effect:

[0322] N(t)=A noise cos(2f noise t+φ noise )+Noise(μ,σ 2 )

[0323] Where N(t) is the noise signal; A noise is the amplitude of the noise signal; f noise is the frequency of the noise signal;

[0324] φ noise is the initial phase of the noise signal; Noise(μ,σ 2 ) is the mean μ and the variance σ 2 Gaussian white noise;

[0325] Noise signals generated by simulating decoy launches;

[0326] Use numerical computing software MATLAB to generate noise signal N(t), set the time range t and sampling frequency, and generate signal data long enough for subsequent processing and analysis;

[0327] Transmit the generated noise signal N(t) through the transmitting system of the simulated decoy, ensuring that the frequency and amplitude settings of the transmitting system match the generated noise signal;

[0328] It should be noted that the phase modulation PM and auxiliary modulation mentioned in the present application are performed before the delayed signal is ready to be transmitted again, which means that t in S1(t) represents the time when the signal is transmitted again after a delay of time T0; and the generation of the interference noise signal is also performed before the delayed signal is ready to be transmitted again, so t in N(t) also represents the time when the signal is transmitted again after a delay of time T0;

[0329] Since S1(t) and N(t) are processed and transmitted at the same time point, that is, after a delay of time T0, their time variable t is the same and does not need to be distinguished; t in both formulas represents a time point in the same time period, that is, the time after a delay of T0;

[0330] During the transmission process, the parameters of the noise signal are adjusted in real time according to the received feedback signal to optimize the interference effect.

[0331] Embodiment eight:

[0332] See also Figure 2, a coherent interference device for inverse synthetic aperture radar image destruction, the device is used to execute the coherent interference method for inverse synthetic aperture radar image destruction, comprising:

[0333] Data interception module: used to release several groups of simulated baits in the electromagnetic wave coverage area of ​​the radar to be interfered. After the simulated baits intercept the electromagnetic wave signals emitted by the radar to be interfered, they perform signal analysis to obtain the electromagnetic wave characteristic data of the radar to be interfered, and store the data. The electromagnetic wave characteristic data includes the operating frequency and pulse width of the electromagnetic wave signal;

[0334] Data modulation interference module: used to obtain and store intercepted electromagnetic wave characteristic data and perform phase modulation and auxiliary modulation in sequence, then select an antenna array of simulated bait as a reference array, and collect the relative index of all antenna arrays of simulated bait relative to the reference array, the relative index includes relative position, relative phase and relative amplitude data;

[0335] Adaptive adjustment module: used to analyze and process the relative indexes of all simulated decoys using an adaptive beamforming algorithm to generate a first adjustment strategy for adjusting the transmission parameters of the simulated decoy antenna array, and at the same time, analyze and process the electromagnetic wave characteristic data to generate an interference noise signal;

[0336] Index evaluation module: used to collect, analyze and process the self-characteristic parameters of the simulated bait, generate a dynamic evaluation index for dynamically adjusting the first adjustment strategy, and the dynamic evaluation index can generate the final emission parameters of each simulated bait in a dynamic adjustment manner. The self-characteristic parameters include the physical position, relative distance, reflection coefficient, emission power, frequency characteristics and modulation parameters of the simulated bait;

[0337] Transmitting module: used to simulate the decoy to generate a modulated signal based on the final transmission parameters, and after a delay of a specific length of time, simulate the decoy to synchronously transmit electromagnetic waves generated based on the interference noise signal and the modulated signal to the radar to be interfered.

[0338] The above formulas are all dimensionless and numerical calculations. The formula is a formula for the most recent real situation obtained by collecting a large amount of data and performing software simulation. The preset parameters in the formula are set by technicians in this field according to actual conditions.

[0339] The above embodiments may be implemented in whole or in part by software, hardware, firmware or any other combination thereof. When implemented by software, the above embodiments may be implemented in whole or in part in the form of a computer program product. Those skilled in the art may appreciate that the units and algorithm steps of each example described in conjunction with the embodiments disclosed herein may be implemented by electronic hardware, or a combination of computer software and electronic hardware. Whether these functions are performed by hardware or software methods depends on the specific application and design constraints of the technical solution.

[0340] The units described as separate components may or may not be physically separated, and the components shown as units may or may not be physical units, and may be located in one place or distributed on multiple network units. Some or all of the units may be selected according to actual needs to achieve the purpose of the solution of this embodiment.

[0341] The above description is only a specific implementation manner of the present application, but the protection scope of the present application is not limited thereto. Any technician familiar with the technical field can easily think of changes or substitutions within the technical scope disclosed in the present application, which should be included in the protection scope of the present application.

Claims

1. A coherent interference method for inverse synthetic aperture radar image destruction, characterized in that: The specific steps include: Step S1, releasing a plurality of groups of simulated decoys in the electromagnetic wave coverage area of ​​the radar to be interfered, and performing signal analysis after the simulated decoys intercept the electromagnetic wave signal emitted by the radar to be interfered to obtain the electromagnetic wave characteristic data of the radar to be interfered, and storing the data, wherein the electromagnetic wave characteristic data includes the operating frequency and pulse width of the electromagnetic wave signal; The simulated decoy realizes the function of receiving and sending electromagnetic waves through a preset antenna array; and the simulated decoy stores the enemy radar electromagnetic waves through a preset radio frequency memory; Step S2, acquiring and storing the intercepted electromagnetic wave characteristic data and performing phase modulation and auxiliary modulation in sequence, then selecting an antenna array of the simulated bait as a reference array, collecting relative indexes of the antenna arrays of all simulated baits relative to the reference array, wherein the relative indexes include relative position, relative phase and relative amplitude data; The phase modulation and auxiliary modulation specifically include the following contents: Phase modulation PM transmits information by changing the instantaneous phase of the signal. The calculation formula is: Where S1(t) is the modulated signal, A is the signal amplitude, is the carrier angular frequency, is the phase modulation sensitivity, m(t) is the baseband signal, is the initial phase, t represents the time variable; Auxiliary modulation includes amplitude modulation AM and frequency modulation FM. Amplitude modulation AM transmits information by changing the amplitude of the signal. The calculation formula is: Where S2(t) is the modulated signal, is the carrier amplitude, is the amplitude modulation sensitivity, m(t) is the baseband signal, is the initial phase, t represents the time variable; The frequency modulation FM transmits information by changing the instantaneous frequency of the signal. The calculation formula is: Where S3(t) is the modulated signal, A is the signal amplitude, It's time The instantaneous frequency, is the differential variable, is the initial phase, t represents the time variable; Instantaneous frequency Determined by the baseband signal m(t), the expression is ,in is the carrier frequency, is the FM sensitivity, is the baseband signal; Step S3, using an adaptive beamforming algorithm to analyze and process the relative indexes of all simulated decoys to generate a first adjustment strategy for adjusting the simulated decoy antenna array transmission parameters, and at the same time, analyzing and processing the electromagnetic wave characteristic data to generate an interference noise signal; The relative position of the antenna array is marked as , the position vector of the antenna element is expressed as , where i represents the i-th antenna element, Indicates the three-dimensional space coordinate value of the corresponding element; The relative phase of the antenna array is marked as , the relative phase of each antenna element is expressed as , where i represents the i-th antenna element; The relative amplitude of the antenna array is marked as , the relative amplitude of the transmission of each antenna element is expressed as , where i represents the i-th antenna element; Set the adaptive beamforming weight vector to , the weight vector for the antenna array is expressed as , where N is the number of antenna elements, is the weight of the ith antenna element; Set the signal covariance matrix to , which represents the covariance matrix of the received signal, calculated by the received signal data; Use the following optimization formula to optimize the transmission direction and signal characteristics of the interference signal: in, is the optimal weight vector; is the signal covariance matrix; is the interference covariance matrix; is the weight vector, yes The conjugate transpose of represents the optimal weight vector to achieve the maximum value of the function; Step S4, collecting the self-characteristic parameters of the simulated bait and analyzing and processing them to generate a dynamic evaluation index for dynamically adjusting the first adjustment strategy, the dynamic evaluation index can generate the final emission parameters of each simulated bait in a dynamic adjustment manner, the self-characteristic parameters include the physical position, relative distance, reflection coefficient, emission power, frequency characteristics and modulation parameters of the simulated bait; Step S5, the simulated decoy generates a modulation signal according to the final transmission parameters, and after a delay of a specific time length, the simulated decoy synchronously transmits electromagnetic waves generated based on the interference noise signal and the modulation signal to the radar to be interfered.

2. The coherent interference method for inverse synthetic aperture radar image destruction according to claim 1, characterized in that: The self-characteristic parameters of the simulated bait are collected and analyzed and processed to generate a dynamic evaluation index for dynamically adjusting the first adjustment strategy. The dynamic evaluation index can generate the final emission parameters of each simulated bait in a dynamic adjustment manner. The self-characteristic parameters include the physical position, relative distance, reflection coefficient, emission power, frequency characteristics and modulation parameters of the simulated bait, specifically including the following contents: The physical location of the simulated bait is marked as , and then the position vector of the simulated bait is ; The relative distance to the simulated bait is marked as , and then the distance vector between the simulated bait and the antenna array is obtained as ,in is the center position vector of the antenna array; The reflection coefficient of the simulated bait is marked as , the emission power of the simulated bait is marked as , the frequency characteristics of the simulated bait are marked as , the modulation parameters of the simulated bait are marked as , define the dynamic evaluation index as , the calculation formula is as follows: The parameters are explained as follows: is the dynamic evaluation index; It is The weight of the item parameters, a total of parameters; It is Complex summation function of parameters; is a parameter that adjusts the steepness of the exponential function; is the launch power of the simulated decoy; is the reference value of the transmission power, and e is a natural constant; is the adjustment parameter of the normalization function; is the complex information filtering function of the jth parameter, with a total of M parameters; For complex summation functions : For complex information filtering functions : The parameters are interpreted as, Represents the position vector of the simulated bait The kth element of , whose elements represent the position coordinates of the simulated bait in space; Represents the position change vector The kth element of represents the relative change of position; Indicates the simulated decoy transmission power The square root of Express and Take the logarithm of the product of; represents the kth element of the simulated decoy modulation parameter; Indicates The weight of the kth sub-parameter of a parameter; Represents the position change vector The lth element of express and The negative power of the square of the product of is the exponential decay function; represents the weight of the lth sub-parameter of the jth parameter; Get dynamic evaluation index , to adjust the weight vector of the antenna array , and obtain the following optimal weight vector : And set the dynamic evaluation index value range to ; when The closer it is to 0, the smaller the influence of the simulated decoy parameters on beamforming is, and the smaller the adjustment of the optimal weight vector is; when The closer it is to 10, the greater the influence of the simulated decoy parameters on beamforming, and the greater the adjustment of the optimal weight vector.

3. The coherent interference method for inverse synthetic aperture radar image destruction according to claim 2, characterized in that: Will Divide into the following intervals, and provide judgment criteria and rules for each interval, as well as description of interaction rules; Interval 1, ; In this range, the simulated decoy parameters have little effect on beamforming; Transmit power Less than 5dBm, relative distance More than 50 meters, resulting in weak interference signals; In terms of technical effect, the antenna array has a low adjustment requirement and the existing configuration is maintained; The threshold is 1, and the judgment is made. When it is less than 1, no adjustment is required; when When it is between 1 and 2, fine-tune; parameter changes have an impact on The impact is small; the dynamic index adjustment rules are as follows: Parameter explanation, is the change of dynamic evaluation index; is the change in transmit power; is the change in frequency characteristics; is the change in reflection coefficient; Interval 2, In this range, the simulated decoy parameters have a 10% to 25% effect on beamforming; the transmit power Between 5dBm and 10dBm, relative distance Between 20m and 50m; set The threshold is 3.5, and the interference intensity is dynamically judged and adjusted; when When it is less than 3.5, adjust the parameters within 15%; When the value is between 3.5 and 5, a significant adjustment of less than 35% is made; the parameter change in this range has a significant The impact is more obvious; The dynamic index adjustment rule expression is as follows: Parameter explanation, is the change of dynamic evaluation index; is the change in transmit power; is the change in frequency characteristics; is the change in reflection coefficient; Interval 3, This range indicates that the simulated decoy parameters have a greater impact on beamforming, accounting for more than 25%; the transmit power Between 10dBm and 15dBm, relative distance Between 10m and 20m; set The threshold is 6, and the interference intensity is dynamically judged and adjusted; when When it is less than 6, make adjustments within 30%; when When the value is between 6 and 7, make adjustments of more than 30%; the changes in each parameter have an impact on The impact is significant; The dynamic index adjustment rule expression is as follows: Parameter explanation, is the change of dynamic evaluation index; is the change in transmit power; is the change in frequency characteristics; is the change in reflection coefficient; Interval 4, This range indicates that the simulated decoy parameters have a great influence on beamforming; the influence accounts for more than 65%; the transmission power More than 15dBm, relative distance Between 0m and 10m; set The threshold is 8.5, and the interference intensity is dynamically judged and adjusted to the maximum; when When it is less than 8.5, make a comprehensive adjustment; when When it is greater than or equal to 8.5, the maximum adjustment is made; the parameter change has an impact on The impact is huge; The dynamic index adjustment rule expression is as follows: Parameter explanation, is the change of dynamic evaluation index; is the change in transmit power; is the change in frequency characteristics; is the change in reflection coefficient.

4. The coherent interference method for inverse synthetic aperture radar image destruction according to claim 3, characterized in that: The intercepted electromagnetic wave characteristic data is analyzed and processed to generate interference noise signals, including the following contents: Detailed analysis of the stored intercepted electromagnetic wave characteristic data is performed to extract the statistical characteristics of the noise components and determine the mean value of the noise signal and variance ; Set the frequency of the noise signal according to the signal characteristics of the interference target , set the amplitude of the noise signal and ensure that the strength of the noise signal is sufficient to interfere with the target signal; Use the following formula to generate a noise signal with interference effect : Where, N(t) is the noise signal; is the amplitude of the noise signal; is the frequency of the noise signal; is the initial phase of the noise signal; The mean is , the variance is Gaussian white noise; Generate noise signal using numerical computing software MATLAB , set the range and sampling frequency in time t to generate signal data long enough for subsequent processing and analysis; Get the generated noise signal And launch it through the launch system of the simulated bait, ensuring that the frequency and amplitude settings of the launch system match the generated noise signal.

5. A coherent interference device for inverse synthetic aperture radar image destruction, characterized in that: The device is used to execute the coherent interference method for inverse synthetic aperture radar image destruction according to any one of claims 1 to 4, comprising: Data interception module: used to release several groups of simulated baits in the electromagnetic wave coverage area of ​​the radar to be interfered. After the simulated baits intercept the electromagnetic wave signals emitted by the radar to be interfered, they perform signal analysis to obtain the electromagnetic wave characteristic data of the radar to be interfered, and store the data. The electromagnetic wave characteristic data includes the operating frequency and pulse width of the electromagnetic wave signal; Data modulation interference module: used to obtain and store intercepted electromagnetic wave characteristic data and perform phase modulation and auxiliary modulation in sequence, then select an antenna array of simulated bait as a reference array, and collect the relative index of all antenna arrays of simulated bait relative to the reference array, the relative index includes relative position, relative phase and relative amplitude data; Adaptive adjustment module: used to analyze and process the relative indexes of all simulated decoys using an adaptive beamforming algorithm to generate a first adjustment strategy for adjusting the transmission parameters of the simulated decoy antenna array, and at the same time, analyze and process the electromagnetic wave characteristic data to generate an interference noise signal; Index evaluation module: used to collect, analyze and process the self-characteristic parameters of the simulated bait, generate a dynamic evaluation index for dynamically adjusting the first adjustment strategy, and the dynamic evaluation index can generate the final emission parameters of each simulated bait in a dynamic adjustment manner. The self-characteristic parameters include the physical position, relative distance, reflection coefficient, emission power, frequency characteristics and modulation parameters of the simulated bait; Transmitting module: used to simulate the decoy to generate a modulated signal based on the final transmission parameters, and after a delay of a specific length of time, simulate the decoy to synchronously transmit electromagnetic waves generated based on the interference noise signal and the modulated signal to the radar to be interfered.

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