Research on High Robustness Underwater Target Estimation Method Based on Variational Sparse Bayesian Inference

Abstract

Pulse noise (such as glacier fracturing and offshore pile driving), commonly seen in the marine environment, seriously affects the performance of Direction-of-Arrival (DOA) estimation methods in sonar systems. To address this issue, this paper proposes a high robustness underwater target estimation method based on variational sparse Bayesian inference by studying and analyzing the sparse prior assumption characteristics of signals. This method models pulse noise to build an observation signal, completes the derivation of the conditional distribution of the observed variables and the prior distribution of the sparse signals, and combines Variational Bayes (VB) theory to approximate the posterior distribution, thereby obtaining the recovered signal of the sparse signals and reducing the impact of pulse noise on the estimation system. Our simulation results showed that the proposed method achieved higher estimation accuracy than traditional methods in both single and multiple snapshot scenarios and has practical potential.

Conceptos Básicos de la Ciencia del Sonido en el Mar

“…Sonar (SOund Navigation And Ranging) es el nombre genérico de la tecnología que se utiliza para localizar objetos bajo el agua [18,102,103]. Existen dos tipos de sistemas sonar: activos y pasivos.…”

Direction of Arrival Estimation Method Based on Eigenvalues and Eigenvectors for Coherent Signals in Impulsive Noise

“…The angle information of the target is one of the important parameters that are required by modern communications. DOA information is widely used in radar, sonar, wireless communications, and other fields [1][2][3][4]. Therefore, algorithm research on DOA estimation has received widespread attention.…”