A novel hybrid estimator for real-time bearings-only target tracking

This paper puts forward a novel hybrid estimator considering the real-time bearings-only target tracking problem. Bias analysis of the Pseudolinear Kalman filter is performed to guarantee the performance of its application to the bearings-only tracking problem in a recursive fashion. A prevailing Instrumental Variable Pseudolinear estimator is reviewed and a similar estimator is derived for the constant turn target motion condition. Feasibility of the hybrid estimator is analyzed and the inherent advantage of their combination for real-time tracking is pointed out. The algorithm flow is given. Simulation results verify the analytical findings.