3D generalized bias compensated pseudolinear Kalman filter for colored noisy bearings-only measurements

Bias compensated pseudolinear Kalman filter (BC-PLKF) degrades for bearings-only tracking if measurements are corrupted with time-correlated noises. Generalized bias compensated pseudolinear Kalman filter (GBC-PLKF), on the other hand, outperforms BC-PLKF and many other comparison filters for two-dimensional (2D) cases under colored noise. However, GBC-PLKF is not practicable for three-dimensional (3D) real-life problems and due to the coupling between lateral and longitudinal planes, its 3D extension is not trivial. In this paper, bias analysis of 3D pseudolinear Kalman filter (PLKF) with azimuth and elevation measurements including colored noise is performed. Then, the low-cost recursive filter, 3D-GBC-PLKF is proposed for 3D real-life applications. The performance and effectiveness of the proposed algorithm is demonstrated with an air-to-surface guided missile pursuing a typical target.