Windowing two-dimensional unrolling multi-beam power spectrum estimation algorithm

Abstract

The invention belongs to the field of sonar signal processing, and discloses a windowing two-dimensional unrolling multi-beam power spectrum estimation algorithm, which comprises the following steps of: pre-calculating and storing a guide vector universal set, namely a point spread function, of each scanning direction (theta, F) according to an array structure and a processing frequency band; performing windowing Fourier transform by adopting the k-lattice element time domain data to obtain the nth batch of array element frequency domain data; adopting a pre-stored guide vector set to carry out windowing beam former processing to obtain a multi-beam power spectrum estimation result; carrying out two-dimensional unrolling processing on the multi-beam power spectrum windowed in the space domain-time domain by using an R-L iterative algorithm in a discrete two-dimensional integral form, and estimating the real energy distribution estimation PBout of the target; and after the unrolling processing is completed, carrying out two-dimensional spectrum peak search on the PBout, carrying out background estimation by taking the minimum value in the extreme points as background estimation, and carrying out background smoothing on all non-extreme points to obtain new multi-beam power spectrum estimation. According to the method, the performance of passive sonar narrowband warning is effectively improved, and the method has high engineering practical significance.

Description

technical field [0001] The invention belongs to the field of sonar signal processing, in particular to the narrowband line spectrum detection technology of passive sonar. Background technique [0002] Affected by strong interference energy and feature leakage in the air domain and frequency domain, the detection performance of passive sonar for weak target features is degraded. In order to avoid the line spectrum feature extraction error caused by strong line spectrum interference in the space domain and frequency domain sidelobe, the two-dimensional integral expression form of the multi-beam power spectrum is derived, and the output result of the multi-beam power spectrum is proposed in azimuth-frequency Dimensional deconvolution processing to reduce the impact of sidelobe leakage in the airspace and frequency domains. At the same time, in order to avoid the weak target under the condition of low signal-to-noise ratio, the strong interference side lobe is too strong, resul...

AI Technical Summary

Problems solved by technology

[0006] It can be seen that due to the influence of 30° strong interference side lobe leakage, CBF cannot effectively detect and correctly distinguish three weak targets at 45°, 93°, and 98°

Chebyshev window processing reduces the side lobe level, but sacrifices spatial resolution and widens the width of the main lobe. It cannot distinguish 30° interference from 45° targets, and cannot distinguish 93° and 98° targets.

Dcv processing uses the spatial spectrum of CBF for iterative deconvolution processing. Since the energy leaked by the interference in the 45° direction is much stronger than the output energy of the 45° target beam, the iterative operation cannot effectively detect the 45° target.

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