Acoustic vector circular array mode-domain robust direction estimation method

An azimuth estimation and acoustic vector technology, which is applied to various directional systems, direction finders using ultrasonic/sonic/infrasonic waves, etc., and can solve the azimuth estimation method in the circular array modal domain of acoustic vector. Poor robustness, inability to meet the needs of long-range passive detection of underwater targets, etc., to achieve the effect of strong background noise suppression, small calculation amount, and high resolution

Active Publication Date: 2016-12-07
HARBIN ENG UNIV
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Problems solved by technology

Based on the theory of phase-mode transformation, Zhu Zhongrui et al. used the anti-noise ability of sound-pressure-vibration-velocity joint processing, combined with subspace algorithms to realize the long-range target orientation estimation of sound vector circular array (Yang Desen, Zhu Zhongrui, Shi Shengguo, Mo Shiqi . Acoustic vector circular array phase modal domain target orientation estimation[J]. Acoustica Sinica, 2014, 39(1): 19-26), but only studied the case where the array manifold is known, the robustness of the orientation estimation method is relatively low. Poor, still unable to meet the needs of long-range passive detection of underwater targets
[0005] The joint processing method of sound pressure and vibration velocity has made great progress in underwater target detection, and has great potential in practical engineering applications, but there is no report on the robust sound vector circular array modal domain orientation estimation method

Method used

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  • Acoustic vector circular array mode-domain robust direction estimation method

Examples

Experimental program
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Effect test

example 1

[0083] Simulation example 1: Comparative analysis of real-valued and non-real-valued sound pressure and vibration velocity joint processing space spectrum

[0084] The simulation parameters are set as follows: the number of uniform circular array elements is 11 elements, the radius r=0.7λ, the frequency is 2kHz, the integration time T=1s, the signal-to-noise ratio (abbreviated as SNR) is 0dB, and the incident direction of the sound source is Figure 3(a)-(b) shows the joint processing MVDR of non-real-valued sound pressure and vibration velocity in the modal domain (referred to as M-VMVDR), the joint processing MVDR of real-valued sound pressure and vibration velocity in the modal domain (referred to as RM-VMVDR) and the model The orientation estimation results of the three methods of Robust MVDR (RM-RVMVDR for short) are jointly processed by using the real-valued sound pressure and vibration velocity, where μ is the constraint parameter of the RM-RVMVDR algorithm.

[0085] Co...

example 2

[0086] Simulation Example 2: Effect of Signal-to-Noise Ratio on Spatial Spectrum Estimation in the Presence of Steering Vector Mismatch

[0087] The simulation parameters are set as follows: the number of elements of the uniform circular array is 11 elements, the radius r=0.7λ, the frequency is 2kHz, the integration time T=1s, the incident direction of the sound source Mismatch error dis=-10dB. Figure 4(a)-(d) shows the real-valued sound pressure MVDR (referred to as RM-PMVDR), RM-VMVDR and RM-RVMVDR (constraint parameter μ=0.5) under different SNRs based on phase-mode transformation theory The spatial spectrum results were compared. Table 1 corresponds to Figure 4(a)-(d) and shows the half-power beamwidths of the spatial spectrum under different SNR conditions for the three methods.

[0088] Table 1 Half-power beamwidth of different methods (unit: / °)

[0089]

[0090] Comparing the spatial spectrum results under different SNRs, it can be seen that: (1) The RM-PMVDR alg...

example 3

[0091] Simulation Example 3: Analysis of Dual-Target Azimuth Estimation Results

[0092] The simulation parameters are set as follows: the number of elements of the uniform circular array is 11 elements, the radius r=0.7λ, the frequency is 2kHz, the integration time T=1s, SNR=0dB, the relevant dual sound sources (correlation coefficient e π / 4 ) incident direction Figure 5(a)-(b) is a comprehensive comparative analysis of the spatial spectrum results of the three algorithms for the acoustic vector circular array.

[0093] Comparing the spatial spectrum, it can be seen that: (1) When the sound sources are related, the M-VMVDR algorithm cannot estimate the orientation of the two sound sources, but the RM-VMVDR algorithm can effectively estimate the orientation of the related sound sources. (2) In the same situation, the RM-RVMVDR algorithm improves the robustness of the RM-VMVDR algorithm, and the spatial spectrum shows a larger dynamic range, a sharper main lobe and a stronger...

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Abstract

The present invention provides an acoustic vector circular array mode-domain robust direction estimation method. The method includes the following steps that: the received signals P(t), Vx (t) and Vy (t) of an acoustic vector circular array acoustic pressure channel, an acoustic vector circular array vibration velocity x channel and an acoustic vector circular array vibration velocity y channel are obtained; the received signals Pe (t), Vex (t) and Vey(t) of a phase mode-domain acoustic pressure channel, a phase mode-domain vibration velocity x channel and a phase mode-domain vibration velocity y channel are obtained; Vex (t) and Vey(t) are rotated electronically, so that a combined vibration velocity Vec (t) can be obtained, a covariance matrix Repv is obtained based on Pe (t) and Vec (t), an unitary matrix Q is introduced to transform the matrix Repv, so that a real-value covariance matrix Rpv of mode-domain acoustic pressure and vibration velocity combined processing can be obtained; a steering vector a<~>r(Phi<~>) which has been subjected to mode-domain transformation and real-value processing is constrained, second-order cone programming is adopted to carry out solving, so that an optimal weight vector Omegarob can be obtained; and an output space spectrogram can be obtained based on the steering vector Omegarob which has been subjected to mode-domain transformation and unitary matrix real-value transformation, and a target direction can be obtained based on a spectrum peak position. With the method of the invention adopted, the problems of performance degradation and high signal-to-noise ratio processing threshold of a minimum variance distortionless response algorithm under a condition that related sound sources are difficult to distinguish and mismatching occurs can be solved. The method has the advantages of high resolution, high robustness, small amount of calculation, strong background noise suppression ability and the like.

Description

technical field [0001] The invention relates to a sensor array signal processing method, in particular to an acoustic vector sensor circular array orientation estimation method. Background technique [0002] Passive sonar azimuth estimation is an important issue in underwater acoustic array signal processing. Most acoustic arrays are used to obtain target azimuth information. Since uniform circular arrays can obtain 360° omnidirectional and unambiguous azimuth information, they are widely used in sonar system. In addition, the sound vector sensor can pick up the scalar and vector information at a certain point in the sound field synchronously and co-located in space, and can obtain more sound field information than the sound pressure sensor. Therefore, it is of great significance to carry out the research on the azimuth estimation method of the acoustic vector circular array for underwater target detection. [0003] Acoustic vector signal processing technology provides a s...

Claims

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G01S3/80
CPCG01S3/8003
Inventor 时胜国李赢杨德森朱中锐时洁胡博张昊阳莫世奇张揽月方尔正
Owner HARBIN ENG UNIV
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