High-resolution rapid deconvolution sound source imaging algorithm

Abstract

The invention discloses a high-resolution rapid deconvolution sound source imaging algorithm which is characterized by comprising the following steps: calculating a point spread function of a sound source at the central position of a sound source calculation plane by utilizing approximation space translation invariance of the point spread function in the process of constructing a point spread function matrix of the deconvolution sound source imaging algorithm; constructing the point spread function matrix through a method for circularly shifting the point spread function at the central position upwards and downwards, so that calculation of the total point spread functions is avoided, the calculated amount, and the calculation speed and efficiency are improved; realizing rapid sparse deconvolution reconstruction of sound source intensity energy distribution through an orthogonal matching pursuit algorithm by utilizing space sparse prior of the sound source and combining compressed sensing in the deconvolution reconstruction process of the sound source intensity energy distribution, so that the iterations are reduced, and the calculation efficiency and resolution ratio are improved. The algorithm disclosed by the invention has high calculation efficiency and spatial resolution and is capable of well rapidly identifying and locating the position of the sound source in the space.

Description

technical field [0001] The invention is mainly used in the field of noise source location and analysis, and is a high-resolution fast deconvolution sound source imaging algorithm. Background technique [0002] The traditional beamforming technology is based on delay summation, cross-spectrum imaging function and other methods to post-process the received signals of each sensor, so that the output of the focal point corresponding to the real sound source on the sound source calculation plane is strengthened, while the output of other focal points The output volume is attenuated, thereby identifying the sound source. However, it will not only output a "main lobe" with a certain width at the real sound source position, but also output a "side lobe" at a non-sound source position. In order to effectively eliminate the influence of the main lobe width and side lobe interference, the anti-roll Acoustic Acoustic Source Imaging Method, or DAMAS, has significantly better spatial res...

AI Technical Summary

Problems solved by technology

First of all, both the DAMAS2 method and the FFT-NNLS method are iterative algorithms. In order to obtain more accurate results, thousands of loop iterations are usually required, and because the Fourier transform introduces a winding error, in order to reduce the winding error, the calculation Influenced by the results, it is usually necessary to pad the number of measurement data points to four times the original, resulting in a sharp increase in the calculation scale, so although the DAMAS2 method and the FFT-NNLS method are superior to the original deconvolution sound source imaging method in terms of computational efficiency, However, there are still deficiencies in computational efficiency and resolution.

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