An active sonar jamming suppression method for suppressive jamming sources

Abstract

The application discloses a kind of active sonar interference suppression methods for suppressive jammer, it is related to acoustic signal processing target identification field.The method utilizes the periodicity of suppressive jammer, the periodic jamming signal in the direction of interference is extracted, and the beam signals in each direction in the interference range are adaptively filtered using the reference signal, to realize the interference suppression of full-space multi-beam signal.The method can effectively suppress the periodic suppressive jamming, greatly improve the active target detection rate under the interference background, and can support the improvement of the anti-interference capability of sonar equipment.

Description

Technical Field

[0001] This invention relates to the field of acoustic signal processing and target recognition, and more specifically, to an active sonar interference suppression method for suppressive interference sources. Background Technology

[0002] Active underwater acoustic target detection technology is one of the main techniques used by various countries for underwater target detection. To weaken or even suppress the effectiveness of underwater acoustic target detection, countries have successively developed a wide variety of underwater acoustic countermeasures equipment, making underwater countermeasures increasingly complex. Among these, using suppressive jamming equipment to emit high-power jamming signals to suppress the target's location is a typical underwater countermeasure technique. This can significantly increase the background noise at the target's location, effectively "flooding" the target. To address the challenge of sonar target detection under suppressive jamming, current methods include adaptive beamforming and spatial filtering. However, these methods primarily utilize the spatial differences between the jamming and the target, without considering the time-frequency characteristics of the jamming itself.

[0003] Common suppression jamming methods include frequency targeting jamming and noise jamming. Frequency targeting jamming is mainly used to suppress the echo signal of active targets. Since active sonar mostly uses pulse signals for detection, the frequency targeting jamming signal has the characteristics of a periodic pulse signal. Noise jamming uses broadband white noise as the jamming signal and can be used to suppress both the echo signal of active targets and the noise signal radiated by passive targets. Currently, some noise jamming equipment uses a pre-recorded white noise signal, which is played in a loop to generate a continuous suppression jamming effect when needed. Since the repetitive periodic characteristics of the above-mentioned suppression jamming are determined by the design of the suppression jamming equipment, while the periodic characteristics of the target under active sonar detection are based on the active sonar transmission period, the two are not consistent. This difference in characteristics can be used to suppress suppression jamming. Unlike the spatial interference suppression methods such as adaptive beamforming and spatial filtering mentioned earlier, the interference suppression method based on the time-frequency difference characteristics of the interference and target signals can suppress the interference when the interference and target azimuths overlap, and obtain a high signal-to-noise ratio active target echo signal under main lobe interference. Summary of the Invention

[0004] This invention addresses the difficulty of active sonar target detection under suppressive interference by providing a method for suppressing active sonar interference sources. This invention can effectively suppress periodic suppressive interference, greatly improving the active target detection rate under interference background and supporting the improvement of sonar equipment's anti-interference capability.

[0005] To achieve the above objectives, the present invention provides the following technical solution: an active sonar interference suppression method for suppressive interference sources, comprising the following steps:

[0006] S1: Process the array data to obtain multibeam data covering the entire spatial orientation;

[0007] S2: Determine the estimated value B(p,t) of the main lobe beam signal of the suppression interference;

[0008] S3: Extract at least one complete cycle of the suppressive interference signal.

[0009] S4: Yes Autocorrelation processing is performed to obtain the autocorrelation envelope X(τ) with correlation peaks. X(τ) is the autocorrelation envelope under the time delay τ condition, and the number of correlation peaks corresponds to the number of periods.

[0010] S5: Extract the peak values ​​of the relevant peaks in S4 to obtain the suppression interference cycle. ;

[0011] S6: Determine the range of influence of the suppression interference. ;

[0012] S7: Extract periodic interference from all beams within the range of suppressive jamming.

[0013] S8: with Using the reference signal, adaptive filtering is performed on each beam within the current active transmission cycle within the interference influence range to achieve interference suppression;

[0014] S9: Using the transmitted signal as a reference, perform matching processing on the filtered result of the error signal. The present invention further specifies that S1 is as follows: The array data is processed using a conventional beamforming method to obtain multi-beam data covering all spatial azimuths, as follows:

[0015]

[0016] Where B(θ, t) represents the time-domain beam data at time t in the θ orientation. Let be the leakage component of the target signal at time t in the θ orientation. Let N(θ,t) be the leakage component of the interference signal at time t in the θ orientation, and let N(θ,t) be the background noise at time t in the θ orientation.

[0017] The present invention is further configured such that S2 specifically includes: determining the azimuth of the suppressive interference main lobe beam and performing omnidirectional energy detection on B(θ,t).

[0018]

[0019] Where E(θ) is the θ-azimuth beam energy; according to the suppression interference characteristics, the search azimuth p satisfies

[0020] E(p) = max(E(θ))

[0021] The beam signal at azimuth p is

[0022]

[0023] in, It is the time-domain data of the original interference signal at time t; because The energy intensity is far greater than and N(p,t), while It is an interference signal. An approximate estimate, therefore B(p,t) can be used as... The estimate.

[0024] The present invention is further configured such that S3 specifically is as follows: The periodicity of the suppression interference is estimated using B(p,t), and a time length of [value missing] is extracted from B(p,t). A piece of arbitrary data It needs to be long enough to ensure that it contains at least one complete cycle of interference data.

[0025] The present invention is further configured such that S4 specifically includes the following: [The following text appears to be incomplete and requires further context: "for..."] Perform autocorrelation processing to obtain

[0026]

[0027] Where X(τ) is the autocorrelation envelope under the time delay τ; since There is an interference signal with at least one period in X(τ), so there are a corresponding number of correlation peaks in X(τ).

[0028] The present invention is further configured such that step S5 specifically involves: extracting the peak values ​​of the relevant peaks, since... The interference noise ratio is extremely high, therefore, a threshold screening and maxima method is used for peak extraction to calculate the interference noise ratio at each point of X(τ).

[0029]

[0030] Where INR(τ) represents the noise-to-interference ratio at each point of X(τ); The autocorrelation envelope background can be obtained by performing a moving average on X(τ), and by thresholding and searching for the maximum value of INR(τ), a sequence of the positions of the correlation peaks can be obtained. ,but

[0031] ,

[0032] in, This represents the cycle period of the suppression interference, 1≤i <k。

[0033] The present invention is further configured such that step S6 specifically includes: determining the range of influence of the suppression interference, and calculating the omnidirectional interference-to-noise ratio based on E(θ) obtained in step 2.

[0034]

[0035] Where I(θ) is the θ-direction interference noise ratio. Let θ be the background noise energy at the azimuth position before the interference occurs, and let the range of the suppression interference be... ,but Need to meet

[0036]

[0037] Where δ is the interference-to-noise ratio threshold. To prevent the interference-to-noise ratio from being too small and affecting the interference suppression effect, δ is generally set to above 10dB.

[0038] The present invention is further configured such that S7 specifically includes: extracting periodic interference from all beams within the range of suppression interference; and, to avoid the influence of active transmission factors such as direct waves and reverberation, intercepting the active detection pulse before transmission. Time-period beam data, as periodic interference, is represented as...

[0039] The present invention is further configured such that S8 specifically includes the following: To suppress interference, adaptive filtering is performed on each beam within the interference-affected range of this active transmission cycle, using the reference signal. The Least Mean Square Error (LMS) algorithm with a transverse filter structure is employed. During the nth iteration, The directional filter weight coefficient vector is Then the (n+1)th iteration

[0040]

[0041] in for Directional step size, for Azimuth beam input sampling, for transpose, d * (n) is The conjugate of the samples; at this point, the error signal can be expressed as

[0042]

[0043] Where e(θI,n) is the error of the nth iteration in the θI direction, which includes the target echo signal after filtering out suppression interference.

[0044] The present invention is further configured such that S9 specifically includes: taking the transmitted signal as a reference, for... Perform matching processing.

[0045]

[0046] in, for Matched envelope sampling of directional delay τ To sample the transmitted signal Perform time delay conjugation; for each orientation The warning process is used to detect targets and obtain information about the target's azimuth and distance. Since the interference has been suppressed at this time, the target echo detection performance is better than before the interference was suppressed.

[0047] In summary, compared with the prior art, the above-described technical solutions conceived by this invention can achieve the following beneficial effects:

[0048] This invention can effectively suppress periodic suppression interference, greatly improve the detection rate of active targets under interference background, and support the improvement of the anti-interference capability of sonar equipment. Attached Figure Description

[0049] Appendix Figure 1 This is a schematic diagram illustrating the interference suppression principle of periodic suppression interference;

[0050] Appendix Figure 2 This is a block diagram of the technical solution of the present invention;

[0051] Appendix Figure 3 This is a schematic diagram of periodic interference extraction;

[0052] Appendix Figure 4 This is a diagram showing the active target detection effect before periodic suppression of interference.

[0053] Appendix Figure 5 This is a diagram showing the effect of active target detection after periodic suppression of interference. Detailed Implementation

[0054] The following combination Figures 1-5 Detailed descriptions of specific embodiments of the present invention are provided to enable those skilled in the art to more clearly understand how to practice the invention. Although the 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.

[0055] like Figures 1-3As shown, an active sonar interference suppression method for suppressive interference sources includes the following steps:

[0056] S1: Process the array data to obtain multibeam data covering the entire spatial orientation;

[0057] S2: Determine the estimated value B(p,t) of the main lobe beam signal of the suppression interference;

[0058] S3: Extract at least one complete cycle of the suppressive interference signal.

[0059] S4: Yes Autocorrelation processing is performed to obtain the autocorrelation envelope X(τ) with correlation peaks. X(τ) is the autocorrelation envelope under the time delay τ condition, and the number of correlation peaks corresponds to the number of periods.

[0060] S5: Extract the peak values ​​of the relevant peaks in S4 to obtain the suppression interference cycle. ;

[0061] S6: Determine the range of influence of the suppression interference. ;

[0062] S7: Extract periodic interference from all beams within the range of suppressive jamming.

[0063] S8: with Using the reference signal, adaptive filtering is performed on each beam within the current active transmission cycle within the interference influence range to achieve interference suppression;

[0064] S9: Using the transmitted signal as a reference, perform matching processing on the filtered result of the error signal.

[0065] The present invention is further configured such that S1 specifically involves processing the array data using a conventional beamforming method to obtain multi-beam data covering all spatial orientations, as follows:

[0066]

[0067] Where B(θ, t) represents the time-domain beam data at time t in the θ orientation. Let be the leakage component of the target signal at time t in the θ orientation. Let N(θ,t) be the leakage component of the interference signal at time t in the θ orientation, and let N(θ,t) be the background noise at time t in the θ orientation.

[0068] S2 specifically involves: determining the location of the main lobe beam of the suppression interference and performing omnidirectional energy detection on B(θ,t).

[0069]

[0070] Where E(θ) is the θ-azimuth beam energy; according to the suppression interference characteristics, the search azimuth p satisfies

[0071] E(p) = max(E(θ))

[0072] The beam signal at azimuth p is

[0073]

[0074] in, It is the time-domain data of the original interference signal at time t; because The energy intensity is far greater than and N(p,t), while It is an interference signal. An approximate estimate, therefore B(p,t) can be used as... The estimate.

[0075] S3 is specifically as follows: The periodicity of the suppression interference is estimated using B(p,t), and a time length of [value missing] is extracted from B(p,t). A piece of arbitrary data It needs to be long enough to ensure that it contains at least one complete cycle of interference data.

[0076] Specifically, S4 is as follows: [Regarding...] Perform autocorrelation processing to obtain

[0077]

[0078] Where X(τ) is the autocorrelation envelope under the time delay τ; since There is an interference signal with at least one period in X(τ), so there are a corresponding number of correlation peaks in X(τ).

[0079] S5 specifically involves extracting the peak values ​​of relevant peaks, since... The interference noise ratio is extremely high, therefore, a threshold screening and maxima method is used for peak extraction to calculate the interference noise ratio at each point of X(τ).

[0080]

[0081] Where INR(τ) represents the noise-to-interference ratio at each point of X(τ); The autocorrelation envelope background can be obtained by performing a moving average on X(τ), and by thresholding and searching for the maximum value of INR(τ), a sequence of the positions of the correlation peaks can be obtained. ,but

[0082] ,

[0083] in, This represents the cycle period of the suppression interference, 1≤i <k。

[0084] S6 specifically involves: determining the range of influence of the suppression interference, and calculating the omnidirectional interference-to-noise ratio based on E(θ) obtained in step 2.

[0085]

[0086] Where I(θ) is the θ-direction interference noise ratio. Let θ be the background noise energy at the azimuth position before the interference occurs, and let the range of the suppression interference be... ,but Need to meet

[0087]

[0088] Where δ is the interference-to-noise ratio threshold. To prevent the interference-to-noise ratio from being too small and affecting the interference suppression effect, δ is generally set to above 10dB.

[0089] Specifically, S7 involves: extracting periodic interference from all beams within the range of suppressive interference; and, to avoid the influence of active transmission factors such as direct waves and reverberation, intercepting the active detection pulse before its transmission. Time-period beam data, as periodic interference, is represented as...

[0090] The specific details of S8 are as follows: To suppress interference, adaptive filtering is performed on each beam within the interference-affected range of this active transmission cycle, using the reference signal. The Least Mean Square Error (LMS) algorithm with a transverse filter structure is employed. During the nth iteration, The directional filter weight coefficient vector is Then the (n+1)th iteration

[0091]

[0092] in for Directional step size, for Azimuth beam input sampling, for transpose, d * (n) is The conjugate of the samples; at this point, the error signal can be expressed as

[0093]

[0094] Where e(θI,n) is the error of the nth iteration in the θI direction, which includes the target echo signal after filtering out suppression interference.

[0095] Specifically, S9 is as follows: taking the transmitted signal as a reference, for... Perform matching processing.

[0096]

[0097] in, for Matched envelope sampling of directional delay τ To sample the transmitted signal Perform time delay conjugation; for each orientation The warning process is used to detect targets and obtain information about the target's azimuth and distance. Since the interference has been suppressed at this time, the target echo detection performance is better than before the interference was suppressed.

[0098] See results Figure 4 , 5 As shown in the figure, before interference suppression, the interference signal completely suppressed the target echo signal, and the target could not be detected. After interference suppression, the interference was basically eliminated, and the target echo was clearly visible.

[0099] The above description is merely a preferred embodiment of the present invention and is not intended to limit the invention. Various modifications and variations can be made to the present invention by those skilled in the art. Any modifications, equivalent substitutions, improvements, etc., made within the spirit and principles of the present invention should be included within the scope of protection of the present invention.

Claims

1. An active sonar jamming suppression method against a suppressive jammer, characterized in that, Includes the following steps: S1: Process the array data to obtain multi-beam data B(θ,t) covering all spatial azimuths, where θ represents azimuth and t represents time. B(θ,t) is the estimated value of the θ azimuth beam at time t. S2: Determine the estimated value B(p,t) of the main lobe beam signal of the suppression interference; S3: Extract at least one complete cycle of the suppressive interference signal. S4: Yes Autocorrelation processing is performed to obtain the autocorrelation envelope X(τ) with correlation peaks. X(τ) is the autocorrelation envelope under the time delay τ condition, and the number of correlation peaks corresponds to the number of periods. S5: Extract the peak values ​​of the relevant peaks in S4 to obtain the suppression interference cycle. ; S6: Determine the range of influence of the suppression interference. ; S7: Extract periodic interference from all beams within the range of suppressive jamming. S8: with Using the reference signal, adaptive filtering is performed on each beam within the current active transmission cycle within the interference influence range to achieve interference suppression; S9: Using the transmitted signal as a reference, perform matching processing on the filtered result of the error signal.

2. The active sonar interference suppression method for suppressive interference sources according to claim 1, characterized in that, S1 is specifically as follows: The array data is processed using a conventional beamforming method to obtain multi-beam data covering all spatial orientations, as follows: in Let be the leakage component of the target signal at time t in the θ orientation. Let N(θ,t) be the leakage component of the interference signal at time t in the θ orientation, and let N(θ,t) be the background noise at time t in the θ orientation.

3. The active sonar interference suppression method for suppressive interference sources according to claim 2, characterized in that, S2 specifically involves: determining the location of the main lobe beam of the suppression interference and performing omnidirectional energy detection on B(θ,t). Where E(θ) is the θ-azimuth beam energy; according to the suppression interference characteristics, the search azimuth p satisfies E(p) = max(E(θ)) The beam signal at azimuth p is in, It is the time-domain data of the original interference signal at time t.

4. The active sonar interference suppression method for suppression-type interference sources according to claim 1, characterized in that, S3 is specifically as follows: The periodicity of the suppression interference is estimated using B(p,t), and a time length of [value missing] is extracted from B(p,t). A piece of arbitrary data It needs to be long enough to ensure that it contains at least one complete cycle of interference data.

5. The active sonar interference suppression method for suppression-type interference sources according to claim 1, characterized in that, Specifically, S4 is as follows: [Regarding...] Perform autocorrelation processing to obtain 。 6. The active sonar interference suppression method for suppressive interference sources according to claim 1, characterized in that, S5 specifically involves extracting the peak values ​​of relevant peaks, since... The interference noise ratio is extremely high, therefore, a threshold screening and maxima method is used for peak extraction to calculate the interference noise ratio at each point of X(τ). Where INR(τ) represents the noise-to-interference ratio at each point of X(τ); The autocorrelation envelope background is obtained by performing a moving average on X(τ), and by thresholding and searching for the maximum value of INR(τ), a sequence of the positions of the correlation peaks is obtained. ,but ， in, This represents the cycle period of the suppression interference, 1≤i <k。 7. The active sonar interference suppression method for suppressive interference sources according to claim 3, characterized in that, S6 specifically involves: determining the range of influence of the suppression interference, and calculating the omnidirectional interference-to-noise ratio based on E(θ) obtained in step 2. Where I(θ) is the θ-azimuth interference-to-noise ratio. Let θ be the background noise energy at the azimuth position before the interference occurs, and let the range of influence of the suppression interference be... ,but Need to meet Where δ is the noise-to-interference ratio threshold.

8. The active sonar interference suppression method for suppressive interference sources according to claim 1, characterized in that, Specifically, S7 involves: extracting periodic interference from all beams within the range of suppressive interference; and, to avoid the influence of active transmission factors such as direct waves and reverberation, intercepting the active detection pulse before its transmission. Time-period beam data, as periodic interference, is represented as...

9. The active sonar interference suppression method for suppressive interference sources according to claim 1, characterized in that, The specific details of S8 are as follows: To suppress interference, adaptive filtering is performed on each beam within the active transmission cycle of the current period, using the reference signal as the basis for the adaptive filtering. A minimum mean square error algorithm and a transverse filter structure are employed. During the nth iteration, The directional filter weight coefficient vector is Then the (n+1)th iteration in for Directional step size, for Azimuth beam input sampling, for transpose, d * (n) is The conjugate of the samples; at this point, the error signal can be expressed as Where e(θI,n) is the error of the nth iteration in the θI direction, which includes the target echo signal after filtering out suppression interference.

10. The active sonar interference suppression method for a suppressive interference source according to claim 9, characterized in that, Specifically, S9 is as follows: taking the transmitted signal as a reference, for... Perform matching processing. in, for Matched envelope sampling of directional delay τ To sample the transmitted signal Perform time delay conjugation; for each orientation The surveillance process is used to detect targets and obtain information about the target's location and distance.

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