Quadrature Filters for Underwater Passive Bearings-Only Target Tracking

Abstract

A typical underwater passive bearings-only target tracking problem is solved using nonlinear filters namely cubature Kalman filter (CKF), Gauss-Hermite filter (GHF) and sparse-grid Gauss-Hermite filter (SGHF). The performance of the filters is compared in terms of estimation accuracy, track-loss count and computational time. Theoretical Cramer-Rao lower bound (CRLB) is used to determine the maximum achievable performance and to compare the error bounds of various filters used.