A Review of Non-Linear Kalman Filtering for Target Tracking

Abstract

Target Tracking (TT) with Non-Linear (NL) Kalman Filtering (NLKF) has recently become a hot research hotspot, particularly in the field of Marine Engineering and air traffic control. This paper presents a comprehensive investigation of NLKF algorithms, with emphases on a proposed theoretical framework to significantly improve its implementation results with regards to accuracy and efficiency. Further, the proposed framework demonstrates potential superior performance in terms of robustness, convergence speed, effective computation and tracking accuracy, comparatively with prior state-of-the-art NLKF techniques. It is anticipated that this study will be beneficial to researchers studying Kalman Filtering (KF) algorithms and also serve as the bedrock for future research, especially for those pursuing their career in Electronics and Information Engineering. Some conclusions and possible research directions of NLKF are proposed in the end.