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Method for judging closest distance to target by acoustic sensor and performing intercepting by using a deep bomb

An acoustic sensor and distance target technology, which is applied in the field of maneuvering target interception to achieve the effects of reducing the computational complexity of algorithms, improving data processing efficiency, and enhancing real-time performance.

Pending Publication Date: 2022-02-08
中国船舶重工集团公司七五0试验场
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  • Abstract
  • Description
  • Claims
  • Application Information

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Problems solved by technology

When the speed exceeds 20km, although the flow noise increases with the increase of the speed, the propeller noise begins to dominate, and the propeller cavitation noise will be the main noise source in the kilohertz frequency band

Method used

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  • Method for judging closest distance to target by acoustic sensor and performing intercepting by using a deep bomb
  • Method for judging closest distance to target by acoustic sensor and performing intercepting by using a deep bomb
  • Method for judging closest distance to target by acoustic sensor and performing intercepting by using a deep bomb

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Experimental program
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Effect test

Embodiment 1

[0044] In this embodiment, the acoustic sensor is a vector hydrophone.

[0045] Based on the above-mentioned Doppler effect, such as figure 1 As shown, the present invention provides a method for acoustic sensor to judge that the target is the closest and utilize deep bomb interception, including:

[0046] Step S1: Establish a signal processing model of the vector hydrophone based on the principle of Doppler motion; and obtain the vector hydrophone t based on the signal processing model k moment and t 0 The relationship between the weighted outputs at times.

[0047] Specifically, it is assumed that there is additive white Gaussian noise in the output signal of the vector hydrophone, and the noise is a zero-mean wide stationary random process and is not correlated with each other. Assuming that at time t, an M irrelevant Doppler signal is incident on the vector hydrophone, the azimuth angle is denoted as The complex envelope of the signal is denoted as s 0 (t),s 1 (t),....

Embodiment 2

[0065] Using ideal simulation data for simulation description, the known simulation data satisfies the law of sinusoidal signal variation, and the simulation results are as follows Figure 2-4 shown.

[0066] figure 2 The two figures (a) and (b) in the figure show the results of signal envelope demodulation and bandpass filtering, respectively. image 3 Figures (a) and (b) in (b) show the resampled and smoothed curves respectively, from figure 1 and figure 2 It can be seen that the changing trends of the four block diagrams are basically the same, but the number of data points gradually decreases with different preprocessing steps. Figure 4 The results of the slope ratio are shown. Since the simulated data used is relatively ideal, and according to the change characteristics of the sinusoidal signal, it can be known that the change law of the slope is the same as that of the basic data.

Embodiment 3

[0068] In this actual test, the data sampling rate f s =200kHz, if the data whose length is T_length=0.1s is selected for analysis, the number of sampling points of the original data is f s ×T_length, that is, 20000 points.

[0069] Perform signal envelope demodulation and bandpass filtering on the data, the results are as follows Figure 5 In (a) and (b) shown.

[0070] Assume that the re-recovery rate and smoothing step are the same as those in the above simulation, that is, the re-recovery rate is 1 / 10 and the smoothing step is 30. After resampling, the number of sampling data points changes from the original 20000 points to 20000 / 10=2000 points; after smoothing, the sampling data points change from 2000 points to 2000 / 30=660 points. The results are as follows Figure 6 In (a) and (b) shown.

[0071] Carry out slope ring ratio on the preprocessed data, that is, perform linear fitting to find the slope, such as Figure 7 The slope change curve of the test data obtained...

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Abstract

The invention discloses a method for judging the closest distance to a target by an acoustic sensor and performing intercepting by using a deep bomb, and the method for judging the closest distance to the target comprises the steps: S1, building a signal processing model of the acoustic sensor based on a Doppler motion principle, and based on the signal processing model, acquiring a relationship between weighted outputs of the acoustic sensor at the tk moment and the t0 moment; S2, based on the relation between the weighted outputs of the acoustic sensor at the tk moment and the t0 moment, analyzing and processing target noise collected by the acoustic sensor; and S3, determining a nearest point by using a slope ring ratio method. The characteristics of target noise are fully utilized, a data analysis means is comprehensively utilized, the noise collected by the acoustic sensor is processed and analyzed to judge the point closest to the target, the data processing efficiency is improved, the algorithm operand is reduced, the real-time performance is high, and the important application value is achieved.

Description

technical field [0001] The invention relates to the technical field of maneuvering target interception, in particular to a method for judging the closest distance to a target by a vector hydrophone based on the principle of Doppler motion and intercepting a maneuvering target with a deep bomb. Background technique [0002] A maneuvering target is a vehicle that can automatically propel and sail according to a predetermined course and depth, and can automatically guide the target and achieve damage to it. Compared with mines, artillery, missiles and other weapons, mobile targets have the characteristics of strong offensiveness, good concealment, and great destructive power, and are widely used in weapon battles. [0003] The self-noise of the maneuvering target usually refers to the noise generated during the navigation of the maneuvering target that interferes with the work of its own detection system, and is related to the speed, depth, operating frequency and sea condition...

Claims

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Application Information

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IPC IPC(8): G01S15/08G01S7/537F42B21/00F41H13/00
CPCG01S15/08G01S7/537F41H13/00F42B21/00
Inventor 殷冰洁赵勰石海泉
Owner 中国船舶重工集团公司七五0试验场
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