Converted state equation Kalman filter for nonlinear maneuvering target tracking

• DOI: 10.1016/j.sigpro.2022.108741
• Publication Date: 2022-08-20T23:12:39Z
• Authors: Wen Zhang; Xuanzhi Zhao; Zengli Liu; Kang Liu; Bo Chen
• Keywords: Polar coordinate system; State vector; Tracking (education)

Handling the nonlinearity between measurement and kinematic states is core issue in target tracking based on radar or sonar. The main novelty of this paper proposal a new filter with linear structure to achieve nonlinear by integrating information polar coordinate system. state vectors composed range, bearing their differentials are constructed make equations linear. After discretizing ordinary differential dynamic system, time-varying transition matrixes established for two common Cartesian motions: constant velocity (CV) acceleration (CA). For process noises converted from system first second moments derived closed form. Consequently, conventional so that can be conducted standard Kalman filter. Several simulation scenarios show such effectively improves accuracy. reasons superior performance proposed method analyzed exemplified. In addition, different posterior Cramer–Rao lower bounds (PCRLBs) fusion estimation coordinates given compared.