Improved Wiener Filter and Target Orientation Estimation Method Based on the Filter

Abstract

The invention relates to an improved Wiener filter and a method for estimating target azimuth based on the filter. Combined with the ability of a beamformer to suppress noise in the space domain and the improved ability of the Wiener filter to suppress noise in the time domain, it proposes that the received data First, by improving the Wiener filter, a certain gain is obtained in the time domain, and then the target azimuth estimation is obtained through the beamformer. This method is called beamforming after tradeoff filter (BATF). By controlling the parameters of the improved Wiener filter, the signal distortion and noise suppression are effectively controlled, so that the output signal of the improved Wiener filter is within the range of the beamformer's tolerance to signal distortion, thereby obtaining the best output, and making The root mean square error of target bearing estimation is reduced, the signal-to-noise ratio threshold of target bearing estimation is lowered, and the problem that the performance of target bearing estimation is degraded under low signal-to-noise ratio of existing methods is overcome.

Description

technical field [0001] The present invention relates to the field of underwater acoustic array signal processing and target azimuth estimation, and relates to an improved Wiener filter and a method for estimating target azimuth based on the filter. Background technique [0002] Target orientation estimation is the main task in underwater acoustic signal processing. Due to the complex underwater acoustic environment and the low signal-to-noise ratio of target signals, in underwater acoustic signal processing, it is generally necessary to suppress noise and improve processing gain by means of array signal processing. . Typically, target azimuths are estimated using subspace decomposition methods and beamforming methods. The biggest disadvantage of the algorithm based on the subspace decomposition method is that under low signal-to-noise ratio, the number of signal sources is estimated incorrectly, and its performance may be seriously degraded. Beamforming methods include Del...

AI Technical Summary

Problems solved by technology

The above-mentioned various improved methods based on the DAS beamforming method all deal with the covariance matrix, and do not fully exploit the noise suppression ability

Under low signal-to-noise ratio, the performance of orientation estimation based on these methods degrades

Images