THE PARTITIONED EIGENVECTOR METHOD FOR TOWED ARRAY SHAPE ESTIMATION

The eigenvector method for estimating the positions of the receivers o f a towed array is based on an eigendecomposition of the cross-spectra l density matrix of the receiver outputs, The method assumes a signal scenario consisting of a single planewave source in the presence of in dependent noise, This paper derives expressions for the bias and varia nce of the position estimates and shows that for acceptable performanc e, the array needs to be relatively linear and the source direction aw ay from endfire, It also shows that the bias and variance is relativel y independent of the number of receivers in the array, This observatio n led to the partitioned eigenvector method introduced in this paper, It is shown that the partitioning approach substantially reduces the c omputational cost of the array shape estimation algorithm without adve rsely affecting the quality of the position estimates, The theoretical work is substantiated with numerical simulations and compared to the Cramer-Rao lower bound (CRLB). Further numerical simulations demonstra te the robustness of the technique against spatially correlated noise and an interference source.