Continuous-discrete shifted Rayleigh filter for underwater passive bearings-only target tracking

In this work, we develop shifted Rayleigh filter (SRF) for continuous-discrete (CD) systems. The proposed filter is applied to a real-life underwater passive bearings-only target tracking problem, where the discretization error is accounted for. The stochastic differential equation describing the process dynamics is approximated using Ito-Taylor expansion of order 1.5. Inorder to make a fair comparative study, the performance of the proposed algorithm, which we refer to as CD-SRF, is examined with other popular filters like the unscented Kalman filter (UKF), cubature Kalman filter (CKF) and Gauss-Hermite filter (GHF) in the CD domain. The filtering performance has been studied in terms of root mean square error (RMSE), trackloss and computational time. Theoretical Cramer-Rao lower bound (CRLB) is also implemented to determine the maximum achievable accuracy.