Anti-interference Algorithm Based on the Projection Matrix and Gray Wolf Optimization

In the case of high intensity of main flap interference and the desired signal in the sampled data, the traditional anti-dominant flap interference algorithm will have the problems that the main flap interference feature vector is not easily distinguished, the desired signal is self-cancelling and the side flap zero trap is easily affected. To address this problem, an anti-interference algorithm based on the projection matrix and gray wolf optimization is proposed in this paper. Firstly, the spectral estimation and the integration of the spectral estimation are used to obtain the covariance matrix of the main flap interference and the desired signal region, which enables to accurately obtain the main flap interference eigenvector and eliminate the desired signal self-cancellation problem; secondly, the weigh-t vector is optimized by the improved gray wolf optimization (IGWO) algorithm to deepen the flap interference trapping. The simulation validation of this algorithm is carried out under the BELLHOP simulated hydroacoustic channel model. The algorithm improves the correlation coefficient difference by at least 0.638 compared with the traditional anti-interference algorithm, can extract the main flap interference eigenvector more accurately, deepens the side flap zero trap, improves the output signal-to-noise ratio by at least 3.054 dB, and can solve the useful signal self-cancellation problem.