A new Modified Algorithm for Target Tracking in Polar Coordinates Based on Equivalent Noise Methodology

An innovation technique is presented to transform the maneuvering target tracking problems from Polar coordinates to Cartesian coordinates, therefore a standard linearKalman filter can be easily applied to them. Extended Kalman filter and unscented Kalman filter are two conventional methodologies for nonlinear estimation. In this paper a new relation between measurement noise covariance in sensor coordinates and the measurement noise covariance in Cartesian coordinates for Kalmanfilter implementation is proposed.In addition the proposed technique is based on the well-known equivalent noise approaches. The simplicity of implementation and target tracking improvement with computation effort reduction, are three important advantages of the new approach comparing with extended Kalman filter and unscented Kalman filter. Simulation results show this modified filter can predict target parameters more effectively and accurately than EKF and UKF