Adaptive Covariance Feedback Cubature Kalman Filtering for Continuous-Discrete Bearings-Only Tracking System

Abstract

Bearings-only tracking is a continuous-discrete system, whose state of motion is in the continuous-time domain and the measurement is in the discrete-time domain. The unpredicted approximation errors are inevitable due to integration, discretization, and linearization of continuous model in many filtering methods. The adaptive covariance feedback framework is proposed for solving this kind of problem, in which the posterior covariance sequence is proved theoretically to be useful for prior covariance updating. In this framework, the covariance feedback framework is integrated with the continuous-discrete cubature Kalman filtering, and Chebyshev distance is applied to judge the proper condition for the start-up of the feedback channel. The numerical results illustrate the proposed method’s superior performance in accuracy and computational efficiency.