Estimation of multipath parameters of underwater acoustic signals based on weighted compressed sensing with dictionary singular value decomposition

In order to improve the estimated parameter resolution of the underwater channels,a method using weighted compressed sensing based on singular value decomposition,is proposed.For active sonar,the proposed algorithm applies singular value decomposition on dictionary which is created based on transmit signal,and then,constructs signal subspace by eigenvectors corresponding to big eigenvalues.To obtain the multipath parameter estimation,the proposed algorithm performs weighted compressed sensing convex optimization on received data filtered by signal subspace.The simulation and lake experiment show that the created signal subspace could filter noise mixed into received data.The proposed algorithm could estimate the underwater acoustic multipath time delay,number and amplitude more accurately.The proposed method is suitable for any pulse signal.