A Cross-Correlation Threshold Based Direction-of-Arrival Estimator for Active Sensing Systems

In this paper, we aim to improve the direction-of-arrival (DOA) estimation performance at low signal-to-noise ratios (SNRs) for active underwater sensing systems. A cross-correlation based Multiple Signal Classification (MUSIC) method is proposed, which perform matrix decomposition over the spatial covariance calculated from the cross-correlation sequences between the transmit waveform and the array output. It is shown via theoretical analysis that crosscorrelation processing preserves the phase information between array elements while suppressing the noise. Inspired by endpoint detection, a cross-correlation threshold based method is also developed to reduce the computation burden and further improve the performance of DOA estimation. Simulation results illustrate the superior performance of the proposed methods.