Target feature difference-based maximum detection distance evaluation method in strong interference environment

Abstract

The present application relates to underwater acoustic signal processing technical field, especially a kind of maximum detection distance evaluation method under strong interference environment based on target feature difference, for the problem that strong interference leads to the failure of traditional sonar detection distance evaluation, by analyzing the time-frequency or spatial difference characteristics of interference and target, calculating interference suppression gain, correcting background noise level, and combining active sonar equation to deduce maximum detection distance, simulation and lake test results show that the present application can effectively eliminate the spatial influence of strong interference on background level, improve the detection distance evaluation precision, applicable to active sonar system in complex interference environment.

Description

TECHNICAL FIELD

[0001] The present application relates to the technical field of underwater acoustic signal processing, and particularly relates to a maximum detection distance evaluation method in a strong interference environment based on target feature difference. BACKGROUND

[0002] With the use of various types of underwater acoustic countermeasure equipment or devices, the underwater acoustic countermeasure technology of various countries has made great progress, which makes the detection capability of the existing sonar system decrease sharply. The strong suppression type underwater acoustic countermeasure device makes the background noise increase sharply by emitting a high sound source level interference signal, and there is a large detection blind zone in the vicinity. When there is strong interference, the target echo is shielded by the strong interference signal, and the effective detection range of the sonar system is greatly reduced. In the detection blind zone caused by strong interference, the traditional maximum detection distance evaluation method for the active sonar system is invalid.

[0003] From the perspective of energy detection, the traditional active target maximum detection distance evaluation method first performs time domain matched filtering and space domain beam forming on the received data to obtain the target echo processing gain. According to the active sonar equation, the maximum detection distance is greatly affected by the interference when the detection threshold is given. Because in the detection blind zone caused by strong interference, the above-mentioned traditional matched filtering and beam forming processing also outputs the interference energy close to distortionless, the propagation loss estimation of the maximum detection distance is seriously wrong, which is the main reason for the failure of the traditional active target maximum detection distance evaluation method. SUMMARY

[0004] The technical problem to be solved by the present application is to re-evaluate the maximum detection distance of the active target under strong interference, reduce the influence of the active detection blind zone caused by strong interference on the maximum detection distance evaluation, and solve the problem of invalid evaluation of the maximum detection distance of the active target under strong interference.

[0005] To achieve the above-mentioned purpose, the present application provides the following technical solution: a maximum detection distance evaluation method in a strong interference environment based on target feature difference, comprising the following steps:

[0006] S1: determining the sound source level SL, the receiving array directivity gain DI and the detection threshold DT according to the working parameters of the active sonar system; the directivity gain DI is calculated by the formula , wherein b (sinθ) is the directivity pattern of the receiving array of the detection platform;

[0007] S2: estimating the interference energy from the received data to determine the interference level IL0; the calculation formula of the interference level IL0 is: Where ISL is the interference source level, TL(r) is the one-way propagation loss from the interference source to the detection platform, r is the one-way propagation distance, f i and f s are the interference bandwidth and the detection platform operating bandwidth, respectively.

[0008] S3: The background interference level is corrected to calculate the background interference level IL(θ) in the interference direction; the corrected background interference level IL(θ) is calculated according to the following formula: Where NL is the background noise level.

[0009] S4: The interference suppression gain IPG(θ) is calculated based on the difference in the spatial direction and the time-frequency distribution of the interference and the target; the IPG(θ) is calculated according to the following formula: Where ISR in and ISR out are the interference-to-signal ratios before and after the difference-based interference suppression processing, respectively. and are the variances of the interference and the signal noise components, respectively, and in and out represent the results of the corresponding parameters before and after the difference-based processing, respectively.

[0010] S5: The background interference level IL(θ) and the background level BNL(θ) are corrected using the interference suppression gain IPG(θ); the corrected background interference level IL(θ) is calculated according to the following formula: When the corrected interference level is lower than the background noise level, the corrected background level BNL(θ) is: ;

[0011] S6: The maximum detection distance corresponding to the propagation loss TL(r max ) is calculated according to the optimized active sonar equation , where DI i is the array gain in the interference output direction, and TS is the target intensity.

[0012] S7: The maximum detection distance r max is solved based on the propagation loss model and the frequency variation characteristics of the absorption loss coefficient α.

[0013] Preferably, the directivity pattern b(sinθ) in step S1 is a uniform linear array directivity pattern, which is calculated according to the following formula: , where M is the number of array elements, β = 2πd sin θ / λ θ is the signal arrival direction, d is the array element spacing, and λ is the signal wavelength.

[0014] Preferably, the interference suppression gain IPG (θ) in step S4 is realized by spatial filtering or adaptive interference suppression algorithm.

[0015] Preferably, the absorption loss coefficient α in step S7 is determined by an empirical formula , wherein f is the signal frequency.

[0016] Preferably, the propagation loss TL (r max ) in step S6 is determined by .

[0017] Preferably, the interference bandwidth f I in step S2 satisfies I / f s ≥ 1.

[0018] Preferably, the method further comprises a simulation verification step: by computer simulation of the maximum detection distance trend under different interference source parameters, target azimuth and system parameters, a target azimuth related detection blind area distribution map is generated, and the effectiveness of the corrected background level is verified.

[0019] Preferably, when the method is applied in lake or sea test, it specifically comprises: extracting the interference azimuth and energy through measured data; based on the interference suppression gain after difference feature processing, correcting the background level in real time; outputting the target detection distance evaluation result, and comparing and verifying with the traditional method.

[0020] Compared with the prior art, the beneficial effects of the present application are: for the problem of invalid evaluation of the maximum detection distance of active target caused by strong interference, a method for evaluating the maximum detection distance of active target after strong interference suppression based on difference features is given. Based on the interference suppression gain brought by the difference feature processing of interference and target, combined with the active sonar equation, an effective method and process for correcting the background noise level by interference level and interference suppression gain under the influence of strong interference is designed;

[0021] After correcting the background noise level and eliminating the change of the background noise level by strong interference in the spatial azimuth, the azimuth related background level under the influence of strong interference can be correctly obtained, and the maximum detection distance of active target under strong interference is re-evaluated;

[0022] Simulation and lake test data analysis results show that after the background noise level is corrected by the method proposed in the present application, the maximum detection distance of active target can be better re-evaluated under the condition of strong interference, which is a beneficial expansion of the traditional maximum detection distance evaluation method of active target under strong interference. BRIEF DESCRIPTION OF DRAWINGS

[0023] Figure 1 : flowchart of the present application;

[0024] Figure 2 : Influence evaluation of maximum detection distance of active target under strong interference

[0025] Figure 3 : a represents the change of detection distance of active target with target echo azimuth under strong interference; b represents the change of detection distance of active target with target echo signal-to-noise ratio under strong interference

[0026] Figure 4 : a represents the change of detection distance of active target with interference source level under strong interference; b represents the change of detection distance of active target with interference distance under strong interference

[0027] Figure 5 : a represents the change of detection distance of active target with system array element number under strong interference; b represents the change of detection distance of active target with time-bandwidth product of transmitted signal under strong interference

[0028] Figure 6 : Verification result of lake test data of active target under strong interference

[0029] Figure 7 : Verification result of lake test data of active target detection under strong interference based on difference characteristic DETAILED DESCRIPTION

[0030] The specific embodiments of the present application 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 application. Although the present application is described in connection with its preferred specific embodiments, these embodiments are merely illustrative, and not restrictive, of the scope of the present application.

[0031] (I) Implementation process

[0032] Reference Figure 1 In order to realize the flowchart of the present application, the present application discloses a maximum detection distance evaluation method under strong interference environment based on target characteristic difference, and the specific implementation steps are as follows:

[0033] S1, determine the sound source level SL, array directivity gain DI, and detection threshold DT according to the working parameters of the active sonar system.

[0034] The transmitting sound source level SL of the active sonar system is determined by the working parameters, and the detection threshold DT is determined by the detection probability and false alarm probability of the sonar system during operation. The maximum detection distance is evaluated under the condition of the same target intensity TS. The receiving array directivity gain DI is related to the array, and satisfies

[0035] (1)

[0036] Where b (sinθ) is the directivity pattern of the receiving array of the detection platform. Taking the uniform linear array directivity pattern as an example, b (sinθ) is given as

[0037] (2)

[0038] Where M is the number of array elements, β = 2πdsinθ / λ, θ is the signal direction of arrival, d is the array element spacing, and λ is the signal wavelength.

[0039] S2, estimate the interference energy from the received data, and determine the interference level IL0.

[0040] When there is a suppressive jamming, let the jammer level be ISL, and assume that the jamming is non-directional, then when the jamming signal reaches the detection platform, the interference level IL0 received by the detection platform is

[0041] (3)

[0042] Where TL(r) is the one-way propagation loss from the jammer to the detection platform, and r is the one-way propagation distance. I and f S are the jamming bandwidth and the detection platform operating bandwidth, respectively. Generally, the jamming bandwidth covers at least the detection platform operating bandwidth, i.e. I / f s ≥ 1.

[0043] S3, correct the background interference level, and calculate the background interference level IL(θ) in the direction of the jamming.

[0044] Under strong jamming conditions, there is a significant difference between the jamming and the isotropic noise signal, and the jamming energy is concentrated in a specific spatial direction. The difference characteristic processing gain correction is the directivity gain in the direction of the jamming arrival. The received jamming level is equivalent to the background noise with directionality in the influence on target detection, and according to the incoherence of noise and jamming, the received jamming level and the background noise level at the detection platform are incoherently superimposed to form a new "background level", and the corrected background interference level IL is

[0045] (4)

[0046] Generally, there is .

[0047] S4, calculate the jamming background level suppression gain IPG(θ) according to the difference characteristic.

[0048] The interference output energy is suppressed by spatial filtering, adaptive interference suppression and other methods based on the differences in spatial orientation, time-frequency distribution characteristics and other difference characteristics of strong interference and targets, so as to reduce the interference background and improve the active target detection distance. The interference suppression processing gain obtained after difference characteristic processing is defined as IPG, and IPG = ISR

[0049] (5)

[0050] where ISR in and ISR out are the signal-to-interference ratios before and after difference characteristic interference suppression processing, respectively, and are the variances of interference and signal noise components, respectively, and in and out represent the results of the corresponding parameters before and after difference characteristic processing. The interference suppression processing gain is obtained for interference suppression in a specific direction, and thus is related to the direction .

[0051] S5, correct the background interference level IL ， (θ) and the background level BNL(θ) according to the interference suppression gain after difference characteristic processing.

[0052] Since the interference suppression gain depends on the signal processing algorithm of the detection platform and directly acts on the background noise level, it is a function of the direction θ, and the corrected background level IL is

[0053] (6)

[0054] When the detection platform receives an interference level less than the background noise level after difference characteristic processing, the interference background level IL(θ) is still dominated by the background noise level, and the corrected background level BNL(θ) is

[0055] (7)

[0056] S6, calculate the maximum distance propagation loss TL(r max ) that can detect a target after difference characteristic processing according to the active sonar equation.

[0057] The traditional active sonar equation under suppressive jamming can be optimized as

[0058] (8)

[0059] where DI i is the array gain in the interference output direction, which can be obtained from equation (1). After difference characteristic processing, the corresponding propagation loss TL(r max ) at the maximum detection distance satisfies

[0060] (9)

[0061] S7. Determine the maximum detection range r based on the propagation loss estimation results. max .

[0062] Propagation loss can be calculated based on spherical wave attenuation.

[0063] (10)

[0064] Where α is the absorption loss coefficient, which is related to the signal frequency. According to the empirical formula for the absorption loss coefficient...

[0065] (11)

[0066] Then the maximum detection distance r max It can be obtained by combining formulas (9) and (10) numerically.

[0067] (II) Simulation and Actual Data Test Results

[0068] Based on "(I) Implementation Process", the effects of the present invention are presented through simulation and actual data analysis, such as... Figures 2-7 As shown.

[0069] Computer Simulation 1: Taking the detection of underwater targets by a linear array sonar as an example, the number of array elements is M=96. During the simulation, a suppressive jamming source with an interference level of 160dB is set up 20km away from the detection platform. First, under the condition of no strong interference, according to the active sonar equations, the maximum detection range is 34.4km. However, under the presence of strong interference, the actual maximum detection range is much less than 34.4km. This is because the jamming source forms a directional "interference background" in the detection area that is much higher than the background noise level. Under the influence of strong interference, the actual detection range of the active sonar is reduced to varying degrees within the detection area, with the most significant reduction in the direction of the interference main lobe. Overall, a detection blind zone is formed near the interference main lobe region, which masks the target signal. Far from the strong interference, the maximum detection range is close to that under the condition of no strong interference. After processing based on a difference of approximately 6dB, the detection range of active targets near the interference direction is improved, and the impact of strong interference on the assessment of the maximum detection range of active targets is reduced. The simulation results are consistent with the analysis of the impact of strong interference on the assessment of the maximum detection range.

[0070] Computer Simulation 2: Based on the active sonar equation (Formula (8)), the influence of each element on the predicted range under the suppression interference is simulated and analyzed from the aspects of interference, signal, environment and equipment. Figure 3This section describes the change in detection range as a function of target echo parameters, including target azimuth and echo signal-to-noise ratio (SNR). Due to the directional nature of the jamming, a detection blind zone is formed in the vicinity of the jamming area. In other azimuths, the impact of the jamming on the detection range assessment weakens with increasing distance from the jamming sector. Regarding the change in target SNR, the maximum detection range increases with increasing target echo intensity, and the increasing trend is more pronounced the further away from the jamming azimuth. Figure 4 The maximum detection range varies with the parameters of the interference source. As the level of the interference source increases, the maximum effective range of the active sonar decreases rapidly. Due to the influence of the propagation loss curve, the rate of decrease varies in different directions. As for the change of interference distance, the interference effect weakens as the interference is further away from the detection platform, and the weakening rate is relatively slow. Figure 5 For the maximum detection range depending on the processing parameters, the performance of different sizes of detection arrays under suppression jamming is mainly related to the target's azimuth. When the target and jamming azimuths overlap, changing the array size will not increase the effective range. This is because the jamming, as one of the targets, has a 10log... 10 The gain of the M-array increases rapidly as the target distance from the interference increases, which is consistent with the inverse relationship between the array beamwidth and aperture. As for the changes in the transmitted signal parameters, the detection threshold decreases continuously and the effective range increases continuously as the product of the transmitted signal time and bandwidth increases.

[0071] Actual Data Analysis 1: The effectiveness of this invention was compared with the results of actual lake test data processing. Strong interference was located at 76° azimuth, and the target was located at 87° azimuth. Figure 6 In conventional broadband surveillance, strong interference completely obscures the target, making it impossible to extract effective features, and the maximum detection range cannot be assessed. Figure 7 Based on the broadband warning processing results after differential feature processing, the target is clearly visible against a relatively flat background, allowing for good target detection at a range of 1020m. After differential feature processing and background noise level correction, it is evident that the maximum detection range of active targets can exceed 1000m under strong interference, thus achieving an assessment of the maximum detection range of active targets under this strong interference condition.

[0072] The above analysis results demonstrate the effectiveness of the proposed method for evaluating the maximum detection range of active targets under strong interference, based on differential characteristics. The method and process provided by this invention for correcting interference levels and background noise levels under strong interference can effectively eliminate the influence of strong interference on the background noise level in spatial orientation, and better determine the orientation-related background level under strong interference. After correcting the background noise level, it is possible to re-evaluate the maximum detection range of active targets in the presence of strong interference, representing a beneficial extension of traditional methods for evaluating the maximum detection range of active targets under strong interference conditions.

Claims

1. A method for evaluating the maximum detection range under strong interference conditions based on target feature differences, characterized in that, Includes the following steps: S1: Determine the source level SL, receiver array directivity gain DI, and detection threshold DT based on the operating parameters of the active sonar system; the directivity gain DI is determined using the formula... The calculation is performed, where b(sinθ) is the directional pattern of the receiving array of the detection platform; S2: Estimate the interference energy from the received data and determine the interference level IL0; the calculation formula for the interference level IL0 is: Where ISL is the interference source level, TL(r) is the one-way propagation loss from the interference source to the detection platform, r is the one-way propagation distance, and f I and f S These are the interference bandwidth and the detection platform's operating bandwidth, respectively. S3: Correct the background interference level and calculate the background interference level IL(θ) at the interference azimuth; the formula for calculating the corrected background interference level IL(θ) is as follows: Where NL is the background noise level; S4: Based on the differences in spatial orientation and time-frequency distribution between the interference and the target, calculate the interference suppression gain IPG(θ); the formula for calculating IPG(θ) is: Among them, ISR in and ISR out These are the interference-to-signal ratios before and after interference suppression processing based on differential characteristics. and These are the variances of the interference and signal-noise components, respectively. in and() out These represent the results of the corresponding parameters before and after differential feature processing; S5: Correct the background interference level IL(θ) and background level BNL(θ) using the interference suppression gain IPG(θ); the corrected expression for the background interference level IL(θ) is: When the corrected interference level is lower than the background noise level, the corrected background level BNL(θ) is: ； S6: Based on the optimized active sonar equations Calculate the propagation loss TL(r) corresponding to the maximum detection range. max In the formula, DI i The array gain is the output azimuth of the interference, and TS is the target strength. S7: Based on the propagation loss model By combining the frequency-varying characteristics of the absorption loss coefficient α, the maximum detection range r can be solved. max .

2. The method for evaluating the maximum detection distance under strong interference conditions based on target feature differences according to claim 1, characterized in that, The directional pattern b (sinθ) mentioned in step S1 is a uniform linear array directional pattern, and its expression is: In the formula, M is the number of array elements, β=2πdsinθ / λ, θ is the direction of signal arrival, d is the spacing between array elements, and λ is the signal wavelength.

3. The method for evaluating the maximum detection distance under strong interference conditions based on target feature differences according to claim 1, characterized in that, The interference suppression gain IPG(θ) mentioned in step S4 is achieved through spatial filtering or an adaptive interference suppression algorithm.

4. The method for evaluating the maximum detection distance under strong interference conditions based on target feature differences according to claim 1, characterized in that, The absorption loss coefficient α mentioned in step S7 is obtained through an empirical formula. Calculate, where f is the signal frequency.

5. The method for evaluating the maximum detection distance under strong interference conditions based on target feature differences according to claim 1, characterized in that, The propagation loss TL(r) mentioned in S6 max )pass Sure.

6. The method for evaluating the maximum detection distance under strong interference conditions based on target feature differences according to claim 1, characterized in that, The interference bandwidth f mentioned in step S2 I Satisfy f I / f s ≥1.

7. The method for evaluating the maximum detection range under strong interference conditions based on target feature differences according to claim 1, characterized in that, The method also includes a simulation verification step: by simulating the maximum detection distance variation trend under different interference source parameters, target azimuth and system parameters, a azimuth-related detection blind zone distribution map is generated, and the effectiveness of the corrected background level is verified.

8. The method for evaluating the maximum detection range under strong interference conditions based on target feature differences according to claim 1, characterized in that, When the method is applied in lake or sea trials, it specifically includes: extracting the location and energy of interference from measured data; correcting the background level in real time based on the interference suppression gain after processing the differential characteristics; outputting the target detection range assessment result and comparing and verifying it with traditional methods.

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