Velocity-Independent 1-D DOA Estimation Method Using Double Parallel Linear Arrays

Abstract

With the development of sensor technology, underwater acoustic technology has also thrived. In this case, higher requirements for underwater direction of arrival (DOA) estimation are proposed. The traditional underwater DOA method uses the acoustic velocity as a constant number during the estimating procedure. However, the calculated result deviates from the actual value. This letter proposes a velocity-independent one-dimensional (1-D) DOA estimation method to address this problem. The method generates an extended covariance matrix using the received data model as a foundation. The extended matrix is then used to obtain automatically matched eigenvalues. The azimuth angle estimation value can be produced after processing the eigenvalues based on the parallel properties between the linear arrays. In contrast to the traditional 1-D DOA estimation algorithm, the estimated value provided by the suggested algorithm is not affected by the acoustic velocity. In comparison to the existing velocity-independent methods, the recommended method offers improved estimation accuracy without significantly adding to complexity. The efficacy and dependability of the suggested algorithm are confirmed by the simulation results.