A sparrow search algorithm-based interference detection integrated waveform design method

Abstract

The application provides a sparrow search algorithm-based interference detection integrated waveform design method.The method establishes an optimization model according to the joint minimization criterion of the time delay resolution constant, the Doppler resolution constant and the discrete degree of the signal amplitude after pulse compression, and constructs a corresponding target function; the target function is solved by using the sparrow search algorithm, so that the optimized interference detection integrated signal is obtained. The integrated signal designed by the method has interference performance and detection performance at the same time, not only stimulates the potential of the electronic countermeasure system, and enhances the concealment of the signal; meanwhile, it is proved that the sparrow search algorithm has better global optimization ability. A new solution is provided for the development direction of the electronic countermeasure system in the direction of miniaturization, intelligentization and integration.

Description

Technical Field

[0001] This invention belongs to the field of electronic countermeasures and involves using the intermittent sampling and forwarding processing of the opponent's signal received by the jammer, and using intelligent algorithms to optimize the signal emitted by the jammer transmitter, so that the emitted signal has both jamming capability and a certain detection capability, thereby realizing an optimized design method for an integrated jamming and detection signal. Background Technology

[0002] With the continuous advancement of informatization and intelligentization, electronic warfare systems face increasingly complex electromagnetic environments. To meet the demands of effectively attacking enemy equipment and enhancing the protection of friendly equipment, electronic warfare systems are gradually exhibiting a trend towards multi-functionality. Integrated multi-functional systems combine the functions of single platforms such as detection, communication, reconnaissance, and jamming, enabling the integration of detection and jamming, detection and reconnaissance, and communication jamming functions.

[0003] Research on integrated jamming detection systems began earlier abroad. In the 1980s, the US Air Force's "Gemstone Pillar" and "Gemstone Platform" projects on the F-22 enabled the F-22's avionics system to have integrated jamming detection capabilities. However, the detection and jamming signals in this system were completely independent and operated in a time-division multiplexing manner, not a true integrated jamming detection system. Compared to foreign countries, domestic research on integrated jamming detection started later. Li Qihu, Wang Ying, and others proposed an integrated jamming detection signal based on dual-carrier pseudo-random binary phase-coded signals, and analyzed the detection and jamming performance of the integrated signal from the ambiguity function and frequency characteristics. Zhong Fan proposed an integrated SAR jamming detection signal based on intra-pulse linear frequency modulation signals, and analyzed the detection and jamming performance of the integrated signal from the ambiguity function and frequency domain characteristics. It is not difficult to see that existing integrated jamming detection research implements jamming by actively transmitting signals, while the integrated jamming detection signal of this invention implements jamming by receiving the opponent's signal and intermittently sampling and forwarding it.

[0004] To improve radar's range, resolution, and measurement accuracy, pulse compression radar has been widely adopted. Linear frequency modulated (LFM) signals, as the most common pulse compression radar signals, offer advantages such as a large bandwidth for improved range resolution, a large time width for improved velocity resolution, and a large time-bandwidth product for improved radar range.

[0005] The metrics for evaluating the integrated interference detection signal are the time delay ambiguity function, the Doppler ambiguity function, and the dispersion of the signal amplitude after pulse compression. The time delay ambiguity function and Doppler resolution are used to evaluate the signal's detection performance, while the dispersion of the signal amplitude after pulse compression is used to evaluate the signal's interference performance.

[0006] The optimization design process of the integrated interference detection signal involves using an optimization algorithm to intermittently sample and forward the pulse sequence of the signal, outputting an integrated signal with optimal interference detection performance. The optimization algorithm is the Sparrow Search algorithm, a novel intelligent optimization algorithm proposed by Xue Jiankai et al. in 2019. To address the issue of traditional optimization algorithms easily getting trapped in local optima, the Sparrow Search algorithm features good stability, few parameters, strong global search capability, and strong local exploitation capability. Summary of the Invention

[0007] This invention presents an integrated waveform design method for interference detection based on the sparrow search algorithm. Its purpose is to unleash the potential of electronic countermeasures systems, enabling them to possess multi-functional capabilities. This invention intermittently samples, forwards, and optimizes the opponent's signal received by the jamming receiver, allowing the transmitted signal to simultaneously possess detection and jamming capabilities. This fusion not only unleashes the potential of the electronic system but also eliminates the need for the radar system's local oscillator, reducing the structure of the electronic countermeasures system, lowering usage and maintenance costs, and enhancing the survivability of friendly equipment in electronic warfare.

[0008] The optimization algorithm used in this invention is the Sparrow Search algorithm. The purpose of using this algorithm is to demonstrate that, compared to other optimization algorithms, the Sparrow Search algorithm has advantages such as better convergence speed, better global search capability, and better local exploitation capability. Furthermore, it provides a novel method for solving complex global optimization problems.

[0009] The objective of this invention is achieved as follows: The steps are as follows:

[0010] Step 1: Initialize the integrated signal. The integrated waveform signal is obtained by intermittently sampling the linear frequency modulated (LFM) signal. The expression for the LFM signal is:

[0011]

[0012] In the formula, For a rectangular signal, its expression is: f c B is the carrier signal frequency; B is the signal bandwidth. The LFM signal frequency modulation slope is represented by T; the radar signal length is represented by T.

[0013] The integrated waveform set contains N signal waveforms, and the amplitude symbol encoding width of each signal waveform is P. Then the nth signal waveform is represented as:

[0014] y m =[y m (1),y m (2),...,y m (w),...,y m (W)]

[0015] In the formula: 1≤m≤N, y m (w) represents the w-th symbol pulse of the integrated signal waveform; the random sequence encodes the binary amplitude of the signal waveform as follows:

[0016]

[0017] In the formula, β k The value is either 0 or 1, τ is the minimum sampling time, and g τ The expression for (t) is:

[0018]

[0019] In amplitude-coded binary sequences, I represents the number of consecutive 0s in the sequence, and J represents the number of consecutive 1s in the sequence, with the length of I being less than the length of J. The short pulse y corresponds to the w-th symbol of the m-th signal waveform. m (w) is represented as:

[0020]

[0021] In equation (9), c iw The w-th symbol representing the binary encoding of the signal amplitude is located at the i-th element in the consecutive zero sequence I, where i ∈ [1, 2, ..., I]; c jw The w-th symbol representing the binary encoding of the signal amplitude is located at the j-th element in the consecutive-1 sequence J, where j∈[1,2,...,J]; s w (t) represents the linear frequency modulated signal pulse corresponding to the w-th symbol of the amplitude binary encoding, as shown in the formula:

[0022] s w (t)=s(t)c(w)

[0023] In the formula, c(w) = c w g τ (t-wτ),c w Represents the w-th amplitude binary code element.

[0024] Step 2: Use the Sparrow Search algorithm to find the optimal waveform;

[0025] Step 21: Initialize algorithm parameters, including the population size N of sparrows, the proportion of searchers, joiners, and guards in the population, and the number of iterations;

[0026] Step 22: Calculate fitness. Calculate the fitness function for each population. The formula for calculating the fitness function is:

[0027]

[0028] Steps 2 and 3: Fitness sorting. Sort the fitness functions and record the best fitness value and its corresponding coordinates.

[0029] Step 24: Calculate the location of sparrows, including the locations of searchers, joiners, and watchers within the sparrow population;

[0030] Step 25: Perform iterations, repeatedly executing steps 22 to 24 until the iteration error is less than 0.1 and the number of iterations is reached. Then, output the optimal position, i.e., the optimal integrated signal waveform.

[0031] Compared with the prior art, the beneficial effects of the present invention are: (1) Multi-functional: The present invention designs an integrated signal that can detect while interfering with the opponent's signal. The jamming transmitter is used as the source of both the detection signal and the jamming signal, saving the radar's local oscillator and providing a solution for the future development of electronic countermeasures systems towards miniaturization and integration.

[0032] (2) Signal Stealth: This invention utilizes intermittent sampling and forwarding technology to achieve amplitude coding modulation, dividing the received linear frequency modulated signal from the pulse compression radar into several short pulses with uneven pulse widths for forwarding. By fusing the detection signal into the jamming signal, the target may mistakenly believe it is just a simple jamming signal, thus reducing the probability of the detection signal being intercepted and improving the survivability of one's own electronic countermeasures equipment.

[0033] (3) Global optimization capability: The detection performance of the integrated signal optimized by the sparrow search algorithm in this invention is better than that of the integrated signal optimized by the genetic algorithm under the same parameter conditions. See Figure 5 , Figure 6 , Figure 7 The Sparrow Search algorithm possesses superior global search capabilities compared to the Genetic Algorithm. Therefore, the integrated signal obtained by this invention effectively improves detection and jamming performance. This invention provides a new method for integrated signal optimization algorithms and offers a solution for the development of multi-functional electronic countermeasures systems. Attached Figure Description

[0034] Figure 1 This is a flowchart of the method of the present invention;

[0035] Figure 2 This is an intermittent sampling and forwarding mechanism for linear frequency modulated signals with pulse amplitude modulation.

[0036] Figure 3 The fitness function curve for the sparrow search algorithm;

[0037] Figure 4 The optimal waveform for integrated signal;

[0038] Figure 5A comparison of the time delay resolution constants of the integrated signal obtained by different optimization algorithms and the uniform intermittent sampling and forwarding interference signal;

[0039] Figure 6 A comparison of the Doppler resolution constants of the integrated signal obtained by different optimization algorithms and the uniform intermittent sampling and forwarding interference signal;

[0040] Figure 7 A time-domain comparison of the pulse compression amplitude of the integrated signal obtained by different optimization algorithms and the uniform intermittent sampling and forwarding interference signal. Detailed Implementation

[0041] The present invention will now be described in further detail with reference to the accompanying drawings and specific embodiments.

[0042] This invention proposes an integrated signal waveform optimization design method for interference detection based on the sparrow optimization algorithm, which, while intermittently sampling and forwarding linear frequency modulated signals, also possesses a certain detection capability. The waveform optimization design scheme is as follows:

[0043] 1. Set optimization function

[0044] The optimization function setting for the integrated interference and detection signal needs to simultaneously meet the conditions for optimizing interference performance and detection performance. Therefore, evaluation indicators for interference and detection performance need to be determined.

[0045] (1) Determine the performance evaluation index of interference detection

[0046] After intermittent sampling and relaying, the linear frequency modulated signal, upon pulse compression, generates a certain number of pulse signals with relatively large amplitudes, i.e., false target signals. The greater the number of false targets and the higher the pulse amplitude, the better the interference effect. Therefore, the dispersion 'd' of the pulse-compressed signal amplitude is used to evaluate the interference performance of the integrated signal.

[0047] The pulse dispersion d of the signal after pulse compression is defined as:

[0048]

[0049] In equation (1), x(t) is the result of integrated signal pulse compression, and σ 2 (·) represents variance calculation, and E(·) represents mean calculation. A smaller d indicates better interference performance.

[0050] (2) Determine the detection performance evaluation index

[0051] Detection performance evaluation metrics are divided into range resolution and velocity resolution. Radar range resolution is complex in real-world electromagnetic environments, with the main lobe and side lobes of the time-delay autocorrelation function significantly influencing it. Therefore, a time-delay ambiguity function is used to describe range resolution, where the time-delay constant represents the ratio of the total energy of the ambiguity function to the main peak. A smaller time-delay resolution constant indicates a smaller sum of energy between the main peak and side lobes, resulting in higher range resolution.

[0052] Time delay resolution constant C μ Defined as:

[0053]

[0054] Similarly, the Doppler ambiguity function is used to describe the velocity resolution of radar. The smaller the Doppler resolution constant, the smaller the energy of the main peak and side lobes, and the higher the velocity resolution.

[0055] Doppler resolution constant C ν Defined as:

[0056]

[0057] (3) Expression of the optimization function

[0058] The integrated signal possesses both interference and detection capabilities, and its performance parameter C... ν C μ The smaller and d are, the better. Therefore, the objective function R(t) is constructed as follows:

[0059] R(t)=α1C v +α2C μ +α3d (4)

[0060] Where α1, α2, and α3 are normalization coefficients.

[0061] 2. Determine the optimization algorithm

[0062] The optimization of an integrated signal involves iteratively searching for the optimal solution using an optimization function, resulting in a stable improvement in the performance of the integrated signal, ultimately leading to the optimal integrated signal. Optimization algorithms need strong global optimization capabilities, local optimization capabilities, and good robustness. The Sparrow Search algorithm, in addition to these, possesses good adaptability and flexibility, capable of optimizing for different problems without altering its structure. Furthermore, the Sparrow Search algorithm exhibits randomness, providing novel solutions to complex practical problems when faced with numerous local optimization issues.

[0063] Therefore, the Sparrow Search algorithm was chosen as the optimization algorithm.

[0064] 3. Expected Results

[0065] (1) The integrated signal interference detection performance is better than that of uniform intermittent sampling and forwarding signals.

[0066] Regarding interference performance, compared to uniform intermittent sampling and forwarding signals, the integrated signal after pulse compression generates more false signals, with larger false signal amplitudes and higher false signal density.

[0067] Regarding detection performance, the integrated signal has smaller sidelobe peaks in both the Doppler resolution constant and the time delay resolution constant compared to the uniformly sampled and forwarded signal.

[0068] (2) The Sparrow Search algorithm has better global optimization capabilities.

[0069] The integrated signal interference and detection performance obtained by the sparrow search algorithm should be better than other optimization algorithms. The comparative algorithm in this invention is the genetic optimization algorithm.

[0070] This invention is based on the condition of intermittent sampling and forwarding of linear frequency modulated signals.

[0071] The specific implementation steps of an integrated waveform optimization method for interference detection based on the sparrow search algorithm are as follows:

[0072] Step 1: Initialize the integrated signal

[0073] The integrated waveform signal is obtained by intermittent sampling of the linear frequency modulated signal.

[0074] The expression for a linear frequency modulated signal is:

[0075]

[0076] In equation (5), For a rectangular signal, its expression is: f c B is the carrier signal frequency; B is the signal bandwidth. denoted as LFM signal frequency modulation slope; T is the radar signal length.

[0077] The integrated waveform set contains N signal waveforms, and the amplitude symbol encoding width of each signal waveform is P. Then the nth signal waveform can be represented as:

[0078] y m =[y m (1),y m (2),...,y m (w),...,y m (W)] (6)

[0079] In equation (6), 1 ≤ m ≤ N, where y m(w) represents the w-th symbol pulse of the integrated signal waveform. The random sequence can encode the binary amplitude of the signal waveform as follows:

[0080]

[0081] In equation (7), β k The value is either 0 or 1, and τ is the minimum sampling time. τ The expression for (t) is:

[0082]

[0083] In amplitude-coded binary sequences, I represents the number of consecutive 0s in the sequence, and J represents the number of consecutive 1s in the sequence, with the length of I being less than the length of J, such as... Figure 2 As shown. Therefore, in equation (6), the short pulse y corresponding to the w-th symbol of the m-th signal waveform. m (w) can be represented as:

[0084]

[0085] In equation (9), c iw The w-th symbol representing the binary encoding of the signal amplitude is located at the i-th element in the consecutive zero sequence I, where i ∈ [1, 2, ..., I]; c jw The w-th symbol representing the binary encoding of the signal amplitude is located at the j-th position in the consecutive-1 sequence J, where j ∈ [1, 2, ..., J]. w (t) represents the linear frequency modulated signal pulse corresponding to the w-th symbol of the amplitude binary encoding, as shown in the formula:

[0086] s w (t)=s(t)c(w) (10)

[0087] In equation (10), the linear frequency modulated signal s(t) is the same as in equation (5), and c(w) = c w g τ (t-wτ),c w This represents the w-th amplitude binary code element, and this code element is encoded as 1.

[0088] Step 2: Use the Sparrow Search Algorithm to find the optimal waveform.

[0089] Step 21: Initialize algorithm parameters

[0090] Initialize the sparrow population size N, the proportion of searchers, joiners, and guards in the population, and the number of iterations;

[0091] Step 22: Calculate fitness

[0092] Calculate the fitness function for each population. The formula for the fitness function is:

[0093]

[0094] Steps 2 and 3: Fitness Ranking

[0095] Sort the fitness functions and record the best fitness value and its corresponding coordinates.

[0096] Step Two Four: Calculate the Sparrow's Position

[0097] Calculate the locations of searchers, joiners, and watchers in a sparrow population;

[0098] Step 25: Perform iterations

[0099] Repeat steps 22 to 24 until the iteration error is less than 0.1 and the number of iterations is reached, then output the optimal position, i.e., the optimal integrated signal waveform.

[0100] The effectiveness of the method of the present invention is verified as follows:

[0101] The integrated signal parameters are set as follows:

[0102] The linear frequency modulated signal has a length of 20 μs, a bandwidth of 10 MHz, a sampling frequency of 40 MHz, and a modulation slope of 5 × 10⁻⁶. 11 Hz / s. The amplitude binary encoded sequence length W is 40 bits, and the minimum sampling time τ is 500ns. The normalization coefficient of the optimization function is...

[0103] The parameters for the sparrow search algorithm are set as follows:

[0104] The sparrow population size N is 40, the proportion of searchers in the population is 0.7, the proportion of joiners is 0.3, the proportion of vigilants is 0.2, and the number of iterations is 100.

[0105] The parameters of the genetic optimization algorithm are as follows:

[0106] The population size is 40, the selection probability is 0.5, the hybridization probability is 0.7, and the mutation rate is 0.001.

[0107] The simulation results are analyzed as follows:

[0108] Figure 3 This represents the optimal fitness value as the number of iterations changes, which is also the value of the objective function R(t) of the integrated signal waveform. As the number of iterations increases, the objective function value of the integrated signal waveform gradually converges to a minimum, i.e., the optimal integrated signal waveform.

[0109] Figure 4The waveform of the integrated interference detection signal is obtained after optimization by the sparrow search algorithm.

[0110] Figure 5 The graph compares the time delay resolution constants of the integrated interference detection signal and the uniform intermittent sampling and forwarding interference signal optimized by different algorithms. Orange represents the uniform intermittent sampling and forwarding signal, green represents the integrated signal optimized by the genetic algorithm, and purple represents the integrated interference detection signal optimized by the sparrow search algorithm. It can be seen that the sidelobe peak value of the time delay ambiguity function of the optimized integrated interference detection signal is significantly reduced, and the range resolution is improved. Meanwhile, the sidelobe peak value of the integrated signal optimized by the sparrow search algorithm is slightly lower than that of the integrated signal optimized by the genetic algorithm. Therefore, the sparrow search algorithm slightly outperforms the genetic algorithm in optimizing the range resolution of the integrated signal.

[0111] Figure 6 The image shows a comparison of the Doppler resolution constants of the integrated interference detection waveform optimized by different algorithms and the uniform intermittent sampling and forwarding interference signal. Orange represents the uniform intermittent sampling and forwarding signal, green represents the integrated signal optimized by the genetic algorithm, and purple represents the integrated interference detection signal optimized by the sparrow search algorithm. It can be seen that the sidelobe peak of the Doppler blur function of the integrated signal optimized by the sparrow search algorithm is significantly reduced, and the velocity resolution is improved. However, the genetic algorithm optimization does not improve the velocity resolution. Therefore, the sparrow search algorithm significantly outperforms the genetic algorithm in optimizing the range resolution of the integrated signal.

[0112] Figure 7 The image shows the time-domain amplitude of pulse-compressed integrated interference detection signals and uniform intermittent sampling-forwarding interference signals optimized by different algorithms. Orange represents the uniform intermittent sampling-forwarding signal, green represents the integrated signal optimized by the genetic algorithm, and purple represents the integrated interference detection signal optimized by the sparrow search algorithm. It can be seen that the optimized integrated signal, after pulse compression, increases the number and amplitude of false targets, thus improving interference performance. Regarding the interference performance of the integrated signal, the sparrow search algorithm optimizes the signal by producing more false targets with a denser distribution after pulse compression. Therefore, the sparrow search algorithm outperforms the genetic algorithm in optimizing the interference performance of the integrated signal.

[0113] The above are specific embodiments of the present invention and are not intended to limit the present invention. Some adjustments and optimizations may be made without departing from the spirit and scope of the present invention. The scope of protection of the present invention is determined by the claims.

[0114] In summary, this invention discloses a waveform optimization design method for integrated interference and detection based on the sparrow search algorithm. The method first establishes an optimization model based on the joint minimization criterion of the time delay resolution constant, Doppler resolution constant, and the dispersion of the signal amplitude after pulse compression of the integrated interference and detection signal, constructing a corresponding objective function. The objective function is then solved using the sparrow search algorithm, thereby obtaining the optimized integrated interference and detection signal. The integrated signal designed by this method possesses both interference and detection performance, not only stimulating the multi-functional potential of electronic countermeasures systems and enhancing signal concealment, but also demonstrating that the sparrow search algorithm has better global optimization capabilities. This provides a new solution for the miniaturization, intelligence, and integration of electronic countermeasures systems.

Claims

1. A waveform design method for integrated interference detection based on the sparrow search algorithm, characterized in that, The steps are as follows: Step 1: Initialize the integrated signal. The integrated waveform signal is obtained by intermittently sampling the linear frequency modulated (LFM) signal. The expression for the LFM signal is: In the formula: For a rectangular signal, its expression is: f c B is the carrier signal frequency; B is the signal bandwidth. The LFM signal frequency modulation slope is represented by T; the radar signal length is represented by T. The integrated waveform set contains N signal waveforms, and the amplitude symbol encoding width of each signal waveform is P. Then the nth signal waveform is represented as: y m =[y m (1),y m (2),...,y m (w),...,y m (W)] In the formula: 1≤m≤N, y m (w) represents the w-th symbol pulse of the integrated signal waveform; the random sequence encodes the binary amplitude of the signal waveform as follows: Where: β k The value is either 0 or 1, τ is the minimum sampling time, and g τ The expression for (t) is: In amplitude-coded binary sequences, I represents the number of consecutive 0s in the sequence, and J represents the number of consecutive 1s in the sequence, with the length of I being less than the length of J. The short pulse y corresponds to the w-th symbol of the m-th signal waveform. m (w) is represented as: In the formula: c iw The w-th symbol representing the binary encoding of the signal amplitude is located at the i-th element in the consecutive zero sequence I, where i ∈ [1, 2, ..., I]; c jw The w-th symbol representing the binary encoding of the signal amplitude is located at the j-th element in the consecutive-1 sequence J, where j∈[1,2,...,J]; s w (t) represents the linear frequency modulated signal pulse corresponding to the w-th symbol of the amplitude binary encoding, as shown in the formula: s w (t)=s(t)c(w) In the formula: c(w)=c w g τ (t-wτ),c w Represents the w-th amplitude binary code element. Step 2: Use the Sparrow Search algorithm to find the optimal waveform; Step 21: Initialize algorithm parameters, including the population size N of sparrows, the proportion of searchers, joiners, and guards in the population, and the number of iterations; Step 22: Calculate fitness. Calculate the fitness function for each population. The formula for calculating the fitness function is: The integrated signal possesses both interference and detection capabilities, and its performance parameter C... ν C μ The smaller and d are, the better. Therefore, the objective function R(t) is constructed as follows: R(t)=α1C v +α2C μ +α3d Where α1, α2, α3 are normalization coefficients; C ν The Doppler resolution constant is... C μ Let be the time delay resolution constant. d represents the degree of signal pulse dispersion after pulse compression. x(t) is the result of integrated signal pulse compression, σ 2 (·) represents variance, and Ε(·) represents mean. Steps 2 and 3: Fitness sorting. Sort the fitness functions and record the best fitness value and its corresponding coordinates. Step 24: Calculate the location of sparrows, including the locations of searchers, joiners, and watchers within the sparrow population; Step 25: Perform iterations, repeatedly executing steps 22 to 24 until the iteration error is less than 0.1 and the number of iterations is reached. Then, output the optimal position, i.e., the optimal integrated signal waveform.

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