Jammer identification method based on harmonic feature

Abstract

The present application relates to underwater acoustic engineering, sonar signal processing and harmonic detection technical field, especially a kind of jammer equipment identification method based on retransmission harmonic feature, first the active sonar echo signal obtained is carried out matching filtering and sampling, then using cepstrum algorithm to extract its corresponding cepstrum, finally the obtained cepstrum is detected without direct current component, whether the target is jammer equipment is judged by the ratio of non-direct current component and noise energy.The present application utilizes the retransmission mechanism of underwater decoy target, exposes its harmonic signal characteristics through matching filtering, and on this basis, relies on harmonic signal identification means to identify and eliminate it.The present application effectively improves the identification ability of jammer equipment, and the algorithm process is simple, the calculation complexity is low, the portability is strong, provides an important component module for constructing the detection and identification system of underwater target.

Description

Technical Field

[0001] This invention relates to the fields of underwater acoustic engineering, sonar signal processing and harmonic detection technology, specifically to a method for identifying interference equipment based on the characteristics of repeating harmonics. Background Technology

[0002] Underwater target detection technology is a key technology in naval operations, underwater acoustic engineering, and environmental surveying. With the continuous development of underwater target detection technology, especially the widespread application of active sonar, underwater target detection capabilities have been significantly improved. Active sonar systems detect underwater targets by emitting sound waves and acquiring and analyzing their echo signals; their detection principle has been effectively applied in modern underwater warfare. However, with the continuous advancement of underwater target detection technology, underwater information warfare is also intensifying. In increasingly fierce underwater information warfare, both sides employ various countermeasures to interfere with the normal operation of active and passive sonar systems, aiming to disrupt or deceive the sonar systems, thereby concealing the true location of underwater targets and gaining a certain advantage in underwater acoustic warfare, even achieving a one-way transparency effect.

[0003] Among various countermeasures, jamming equipment has become a primary means of underwater information warfare due to its low cost and high simulation accuracy. Its main operating principle is to receive a sonar signal from an active sonar system and then relay the received signal with a certain signal delay, thereby disguising it as an echo signal similar to the real target, thus interfering with the sonar system's detection, judgment, and identification of the target.

[0004] To effectively counter this decoy jamming method based on the time delay of received signals, researchers have proposed several anti-jamming techniques, including enhancing the detection signal-to-noise ratio and Doppler effect analysis. These techniques aim to reduce interference from jamming devices by improving the sonar system's ability to identify and filter echo signals. However, these methods often utilize information other than broadband warning signals or require better hardware. Under conditions of limited technology or further diversification of jamming methods, these algorithms and processing methods face certain challenges. Therefore, new technologies are urgently needed to further improve the anti-jamming performance of sonar systems against jamming devices. Summary of the Invention

[0005] To address the shortcomings of existing technologies, the present invention aims to provide a method for identifying jamming equipment based on the characteristics of echo harmonics. This method utilizes the harmonic structure of the echo signal of jamming equipment and improves the echo signal processing techniques, enabling active sonar systems to more effectively identify targets and jamming equipment in complex underwater environments. This improves the accuracy of active sonar system identification and increases the reliability and stability of the system.

[0006] To achieve the above objectives, the present invention provides the following technical solution: a method for identifying interference equipment based on repeater harmonic characteristics, comprising the following steps:

[0007] Step S1: Perform matched filtering on the target echo signal to obtain the broadband warning time-domain signal: The target echo signal can be represented as...

[0008] (1)

[0009] Where y(t) is the sonar received signal, s(t) is the sonar transmitted signal, A is the signal receiving gain, w(t) is the additive Gaussian noise, and τ is the time delay of the echo signal; , where d is the distance between the target and the sonar, and c is the speed of light.

[0010] For jamming equipment with a relay mechanism, the received signal is often relayed with a certain time delay and period, or it is relayed multiple times after being reflected from the seabed or sea surface. Modeling the echo signals obtained from this relay or reflection can be represented as...

[0011] (2)

[0012] Where A f and τ f The corresponding echo gain and reception delay of the jamming equipment are given by M, where M is the total number of relayed signals, β is the relayed signal attenuation coefficient, and T is the signal attenuation factor. s The repetition period of the relay signal is given. After matched filtering and sampling of the received signal, the broadband warning results of the target echo signal and the jamming equipment echo signal are obtained as follows:

[0013] (3)

[0014] (4)

[0015] Where the signal lengths of y[n] and yf[n] are N, and δ[n] represents the discrete impulse function. σ represents discrete additive Gaussian noise. 2 The noise variance is used. After obtaining the broadband warning time-domain signal, a cepstral processing algorithm is used to distinguish between the target echo signal and the jamming equipment echo signal.

[0016] Step S2: Extract the spectrum of the broadband warning signal: The spectrum of the discrete signal y[n] is extracted using the Fast Fourier Transform (FFT) algorithm, specifically expressed as follows:

[0017] (5)

[0018] F(y) is the discrete Fourier transform. Applying the Fourier transform to equations (3) and (4) respectively yields...

[0019] (6)

[0020] (7)

[0021] in This is the result of the noise undergoing a Discrete Fourier Transform (DFT). Since the DFT is a unitary transform, it can be assumed that the noise does not change its distribution and correlation. After rearranging equation (7), we get

[0022] (8)

[0023] As can be seen from equation (8), compared with equation (6), the echo spectrum of the interference equipment echo signal has a frequency shift term.

[0024] Step S3: Analyze the spectrum of the broadband warning signal using the cepstrum analysis algorithm. Cepstrum analysis is a signal processing technique used to analyze periodic components or harmonic characteristics in a signal. Its core idea is to perform a "secondary transformation" on the signal spectrum, converting complex frequency domain characteristics into a more easily analyzable time-delay domain representation. The specific process of the cepstrum analysis algorithm is as follows: First, the echo spectrum is modulo-divided. The real signals obtained after modulo-dividing the target echo signal and the echo signal from the interfering equipment are represented as follows:

[0025] (9)

[0026] (10)

[0027] Taking the logarithm of the modulo-derived real signal yields...

[0028] (11)

[0029] (12)

[0030] Performing Fourier transforms on equations (11) and (12) respectively, we can obtain

[0031] (13)

[0032] (14)

[0033] Comparing Equations (13) and (14), the cepstral spectrum of the target echo signal has only a DC component, while the echo signal of the jamming device has not only a DC component but also a non-DC component. Detecting the non-DC component can distinguish between the jamming device and the target.

[0034] Step S4: Detect the non-DC component in the cepstrum and calculate its ratio to the noise energy. If the ratio is greater than a preset threshold, it is determined to be an interfering device.

[0035] Preferably, in step S2, a Fast Fourier Transform (FFT) is used to extract the spectrum, and the grid length of the FFT is [missing information]. , This is the floor function.

[0036] Preferably, in step S4, the noise energy is estimated using the unit average-constant false alarm rate detection algorithm, and the threshold is set to 10.

[0037] Compared with the prior art, the beneficial effects of the present invention are:

[0038] 1. By utilizing the retransmission harmonic characteristics of jamming equipment, which differ from those of target echoes, and employing algorithms such as matched filtering and cepstral spectrum analysis, this characteristic is converted into a non-DC component that can be quantified and identified, highlighting its periodicity and regularity. Specific thresholds are set to distinguish between jamming equipment and target echoes, effectively improving the ability to identify jamming signals.

[0039] 2. This application utilizes the non-DC component characteristics of the cepstrum to effectively remove the interference of environmental noise and concentrate the harmonic energy in a specific frequency band, thereby improving the detection capability and reliability of harmonics and enhancing the anti-interference capability of the sonar system in complex underwater environments.

[0040] 3. The algorithm in this application has low complexity, is suitable for real-time processing, and can be integrated into existing sonar systems. Attached Figure Description

[0041] Figure 1 This is a flowchart of the process of the present invention;

[0042] Figure 2 The echo signals under ideal conditions after matched filtering are: (a) the echo signal of the real target; (b) the echo signal relayed by the jamming equipment.

[0043] Figure 3 The result is the cepstral processing of the echo signals from the jamming equipment and the real target. Detailed Implementation

[0044] The specific embodiments of the present invention are described in detail below with reference to the accompanying drawings, so that those skilled in the art can more clearly understand how to practice the present invention. Although the present invention has been described in conjunction with its preferred embodiments, these embodiments are merely illustrative and not intended to limit the scope of the invention.

[0045] See Figures 1-3 This application provides a method for identifying interference equipment based on the characteristics of forwarding harmonics. First, the obtained active sonar echo signal is matched and filtered and sampled. Then, the corresponding cepstrum is extracted using a cepstrum algorithm. Finally, the non-DC component of the obtained cepstrum is detected. The ratio of the non-DC component to the noise energy is used to determine whether the target is interference equipment.

[0046] The specific steps are as follows:

[0047] Step S1: Perform matched filtering on the target echo signal to obtain the broadband warning time-domain signal: The target echo signal can be represented as...

[0048] (1)

[0049] Where y(t) is the sonar received signal, s(t) is the sonar transmitted signal, A is the signal receiving gain, w(t) is the additive Gaussian noise, and τ is the time delay of the echo signal; , where d is the distance between the target and the sonar, and c is the speed of light.

[0050] For jamming equipment with a relay mechanism, the received signal is often relayed with a certain time delay and period, or it is relayed multiple times after being reflected from the seabed or sea surface. Modeling the echo signals obtained from this relay or reflection can be represented as...

[0051] (2)

[0052] Where Af and τf are the corresponding echo gain and reception delay of the jamming equipment, M is the total number of relayed signals, β is the relayed signal attenuation coefficient, and Ts is the relayed signal repetition period. After matched filtering and sampling of the received signal, the broadband warning results of the target echo signal and the jamming equipment echo signal are obtained as follows:

[0053] (3)

[0054] (4)

[0055] Where the signal lengths of y[n] and yf[n] are N, and δ[n] represents the discrete impulse function. Let σ² represent discrete additive Gaussian noise, and σ² be the noise variance. After obtaining the broadband warning time-domain signal, a cepstral processing algorithm is used to distinguish between the target echo signal and the jamming equipment echo signal.

[0056] During implementation, the active sonar echo signal is acquired and subjected to matched filtering and sampling. The simulation results of the active sonar echo signal after matched filtering and sampling are shown below. Figure 2 As shown. The selected signal parameters are as follows: sampling frequency 3000Hz, signal length N=2048, noise variance σ 2 =1. In Figure 2 In (a), the target appearance delay is τ = 0.33s, the signal amplitude is A = 100, and the corresponding signal-to-noise ratio is 20dB. Figure 2 In (b), the target appearance delay is τ = 0.33s, the signal amplitude is A = 31.6, and the harmonic repetition period is T. f =0.003s, harmonic repetition number M=12, harmonic attenuation rate β=0.7, and the corresponding signal-to-noise ratio is also 20dB.

[0057] Step S2: Extract the spectrum of the broadband warning signal: The spectrum of the discrete signal y[n] is extracted using the Fast Fourier Transform (FFT) algorithm, specifically represented as follows:

[0058] (5)

[0059] F(y) is the discrete Fourier transform. Applying the Fourier transform to equations (3) and (4) respectively yields...

[0060] (6)

[0061] (7)

[0062] in This is the result of the noise undergoing a Discrete Fourier Transform (DFT). Since the DFT is a unitary transform, it can be assumed that the noise does not change its distribution and correlation. After rearranging equation (7), we get

[0063] (8)

[0064] As can be seen from equation (8), compared to equation (6), the echo spectrum of the interfering equipment's echo signal has a frequency shift term. Furthermore, the grid length of the Fourier transform is... , This is the floor function.

[0065] According to the above method, in actual operation, the broadband warning signal spectrum is extracted, and the broadband warning signal in step 1 is processed using the FFT algorithm. The FFT processing length is also 2048 points.

[0066] Step S3: Analyze the broadband warning signal spectrum using the cepstral processing algorithm. The specific process of the cepstral processing algorithm is as follows: First, the echo spectrum is modulo-divided. The real signals obtained after modulo-dividing the target echo signal and the echo signal of the jamming device are represented as follows:

[0067] (9)

[0068] (10)

[0069] Taking the logarithm of the modulo-derived real signal yields...

[0070] (11)

[0071] (12)

[0072] Performing Fourier transforms on equations (11) and (12) respectively, we can obtain

[0073] (13)

[0074] (14)

[0075] Comparing Equations (13) and (14), the cepstral spectrum of the target echo signal has only a DC component, while the echo signal of the jamming device has not only a DC component but also a non-DC component. Detecting the non-DC component can distinguish between the jamming device and the target.

[0076] During implementation, after modulus, logarithm, and FFT transformations, the cepstrum of the real target and the jamming equipment are obtained as follows: Figure 3 As shown. In Figure 3 In the diagram, the cepstral spectrum of the real target is drawn with a red dashed line, while the cepstral spectrum of the jamming equipment is drawn with a blue solid line. From... Figure 3 It can be seen that the DC components of the cepstrum of both the real target and the jamming device are very high, but the non-DC component of the real target is basically 0, while the non-DC component of the jamming device has a high proportion. This shows that detecting the non-DC component of the cepstrum can effectively distinguish between the real target and the jamming device.

[0077] Step S4: Detect the non-DC component of the analysis results and determine the identification result. In implementation, the unit average-constant false alarm rate detection algorithm is used to estimate the noise energy, and the threshold is set to 10. Calculations show that the amplitude of the largest non-DC component of the interference signal is approximately 319.8. Taking the average of a relatively stable frequency band, the calculated interference intensity is approximately 21.8, and the corresponding ratio of the non-DC component to the interference intensity is 14.7, which is greater than the preset α=10, thus identifying it as interference equipment. The maximum non-DC component of the real target is 53.4, and the ratio of the non-DC component to the interference intensity is 2.45, which differs significantly from the result for interference equipment. Therefore, this algorithm successfully identified both interference equipment and the real target, demonstrating strong feasibility.

[0078] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention and are not intended to limit it. Although the present invention has been described in detail with reference to preferred embodiments, those skilled in the art should understand that modifications or equivalent substitutions can be made to the technical solutions of the present invention without departing from the spirit and scope of the technical solutions of the present invention, and all such modifications or substitutions should be covered within the scope of the claims of the present invention.

Claims

1. A method for identifying interference equipment based on the characteristics of repeating harmonics, characterized in that, Includes the following steps: Step S1: Perform matched filtering and sampling on the received active sonar echo signal to obtain the broadband warning time domain signals of the target echo signal and the signal relayed by the jamming equipment, respectively. Step S2: Extract the spectrum of the broadband warning signal using Fast Fourier Transform; Step S3: After performing modulo and logarithmic operations on the spectrum, perform a fast Fourier transform again to obtain the cepstral features; Step S4: Detect the non-DC component in the cepstral spectrum and calculate its ratio to the noise energy. If the ratio is greater than a preset threshold, it is determined to be an interfering device.

2. The method for identifying interference equipment based on repeater harmonic characteristics according to claim 1, characterized in that, In step S1, the target echo signal is represented as （1） Where y(t) is the sonar received signal, s(t) is the sonar transmitted signal, A is the signal receiving gain, w(t) is the additive Gaussian noise, and τ is the time delay of the echo signal; , where d is the distance between the target and the sonar, and c is the speed of light; Modeling the echo signal obtained by the jamming equipment from forwarding or reflecting it, and representing it as follows: （2） Where A f and τ f The corresponding echo gain and reception delay of the jamming equipment are given by M, where M is the total number of relayed signals, β is the relayed signal attenuation coefficient, and T is the signal attenuation factor. f The repetition period of the relay signal; after matched filtering and sampling of the received signal, the broadband warning results of the target echo signal and the jamming equipment echo signal are obtained as follows: （3） （4） Where y[n] and y f The signal length of [n] is N, and δ[n] represents the discrete impulse function. σ represents discrete additive Gaussian noise. 2 This represents the noise variance.

3. The method for identifying interference equipment based on repeater harmonic characteristics according to claim 1, characterized in that, In step S2, a Fast Fourier Transform (FFT) is used to extract the spectrum. The grid length of the FFT is [value missing]. , This is the floor function.

4. The method for identifying interference equipment based on repeater harmonic characteristics according to claim 1, characterized in that, In step S3, the cepstral processing includes the following sub-steps: taking the modulus of the spectrum and then taking the logarithm to obtain the real signal; performing a Fourier transform on the real signal to separate the DC component and the non-DC component.

5. The method for identifying interference equipment based on repeater harmonic characteristics according to claim 1, characterized in that, In step S4, the noise energy is estimated using the unit average-constant false alarm rate detection algorithm, and the ratio of the maximum non-DC component to the noise energy is calculated. When the ratio is greater than a preset threshold, it is determined to be an interfering device.

6. The method for identifying interference equipment based on repeater harmonic characteristics according to claim 5, characterized in that, The preset threshold is set to 10.

7. The method for identifying interference equipment based on repeater harmonic characteristics according to claim 1, characterized in that, The relay harmonic characteristics of the interference device are manifested as the energy concentration characteristics of the periodic frequency shift terms and non-DC components in the spectrum.

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