Hydroacoustic Array Beamforming Technique Based on KPM-LCMV Algorithm

The adaptive beamforming algorithm, Linearly Constrained Minimum Variance (LCMV), is improved and implemented in simulation. In this paper, we propose an adaptive beamforming algorithm based on Kalman filtering with special matrix processing (KPM-LCMV, Kalman filtering & PID control & Matrix processing based on LCMV) for PID control optimization, and its main research contents are as follows: Firstly, to reduce the directional angle estimation error, this paper firstly iterates the classical DOA (Direction of Arrival) estimation algorithm by using Kalman filtering algorithm and corrects it by error. This paper further optimizes the above algorithm by using Proportion Integration Differentiation (PID) control to obtain more accurate directional angles. Kalman algorithm optimization based on PID technology: It is based on PID technology to eliminate the steady-state error in Kalman algorithm to optimize the accuracy of DOA estimation, and some direction-of-arrival estimation algorithms can be further optimized by this technology; secondly, for how to reduce the computational effort and stability of the covariance matrix, in this paper, optimization is performed by a special matrix processing method. Optimization of the adaptive beamforming method based on linear constrained minimum variance: that is, based on the linear constrained minimum variance criterion, the covariance matrix of the signal is optimized by frequency domain transformation and generalized inverse correction to reduce the computational effort, improve the convergence speed, and reduce the effect of small eigenvalue perturbations on beamforming when the signal-to-noise ratio is elevated.