Target signal extraction method based on frequency domain-wave number domain deconvolution

Abstract

The invention relates to the field of underwater acoustic signal processing and particularly relates to a target signal extraction method based on frequency domain-wave number domain deconvolution. The method comprises steps of receiving a time domain array signal collected by an underwater acoustic uniform linear array, and converting the array signal from an array element domain-time domain to a frequency domain-wave number domain; establishing a spatial modal sensing matrix; estimating a spatial modal spectrum contained in the frame of data by using a deconvolution algorithm in combination with the spatial modal sensing matrix on a frequency domain-wave number domain; and enabling the wave number to correspond to the azimuth at different frequency points, converting the spatial modal spectrum into an azimuth-frequency domain beam spectrum, and extracting a frequency domain signal of the target according to the azimuth of the target. According to the method, a problem of target signal aliasing of conventional beam forming under the multi-target condition is solved to a certain extent, the quality of extracted signals is good, the occupied memory is small, the method can be deployed in actual equipment more quickly, and a stable and reliable target signal extraction function is provided for signal processing of an underwater unmanned platform.

Description

technical field [0001] The invention relates to the field of underwater acoustic signal processing, in particular to a target signal extraction method based on frequency domain-wavenumber domain deconvolution. Background technique [0002] In recent years, underwater target recognition technology based on underwater unmanned platforms has received extensive attention. However, in complex underwater environments with small apertures, multiple targets, and high self-noise, the signal characteristics of multiple targets overlap and interact with each other. For interference, the accurate extraction of underwater target signals is fully limited, which brings great difficulties to the subsequent feature extraction processing and identification; therefore, signal extraction under the condition of multiple targets on underwater UUV is an extremely important difficulty. [0003] Most of the existing target signal extraction technologies in practical applications are conventional bea...

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Problems solved by technology

[0002] In recent years, underwater target recognition technology based on underwater unmanned platforms has received extensive attention. However, in complex underwater environments with small apertures, multiple targets, and high self-noise, the signal characteristics of multiple targets overlap and interact with each other. For interference, the accurate extraction of underwater target signals is fully limited, which brings great difficulties to subsequent feature extraction processing and identification; therefore, signal extraction under the condition of multiple targets on underwater UUV is an extremely important difficulty

[0003] Most of the existing target signal extraction technologies in practical applications are conventional beamforming and MVDR. Although conventional beamforming is very stable and simple, in fact, in a multi-target complex environment, signal aliasing is serious when extracting multi-target signals. MVDR is in practice Although it can effectively reduce side lobes, it is very sensitive to various errors such as array element position error, steering vector error, etc.

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