Marine Radar Target Tracking Filtering Algorithm Based On Polar Coordinate System

Marine radar is an indispensable navigational device for ships at sea.The judgment of collision risk between ships largely depends on the target tracking and filtering process.With the continuous development of filtering theory,more and more non-linear filtering algorithms are applied in marine radar target tracking,and the algorithm complexity is also getting higher and higher.For the large ships,due to their small maneuverability,they can be approximated as a uniform linear motion in a radar scanning period.There is no specific research on whether complex non-linear tracking filtering algorithm is needed.In this thesis,a detailed theoretical analysis of this problem is carried out.Based on the analysis results,a target tracking filtering algorithm for marine radar based on state equation in polar coordinate system is proposed.(1)The filtering algorithm in marine radar target tracking is introduced,and the non-linear problem is analyzed in detail.According to the simulation experiment results of the target ship making uniform linear motion under different headings,speeds and initial distances,the problem of non-linearity exists in the filtering algorithm,whether the state equation of the target is established in Cartesian coordinate system or polar coordinate system.It shows that the problem of non-linearity in marine radar target tracking is unavoidable.(2)The filtering algorithm for establishing the target state equation in polar coordinates is introduced.Due to the non-linear filtering algorithm currently applied in the target tracking of marine radar,most of them are for the non-linear problem of establishing state equation in Cartesian coordinate system,such as EKF algorithm.There are few literature studies on the non-linear problem of establishing state equation in polar coordinate system.But the equation of state established in polar coordinates is decoupled in distance and azimuth,indicating that the filtering effects on the distance and azimuth do not affect each other,and the filtering result directly corresponds to the location information of the target,so the coordinate conversion error will not be caused.By analyzing the non-linear motion equation of the target in polar coordinates,we can know that the non-linear motion equation of the target can be linearized when the target is moving in uniform line motion.Therefore,combining Taylor series expansion processing and standard Kalman filtering algorithm,this thesis proposes a filtering algorithm based on the first,second and third order expansion formal state equation in polar coordinates.The simulation results show that the filtering algorithm based on the second-order expanded formal state equation has the best filtering effect.The filtering algorithm effectively solves the problem of filtering divergence caused by the error of Taylor series expansion processing.At the same time,the filtering algorithm is simple in calculation and suitable for real-time tracking filtering.(3)The filtering algorithm and EKF algorithm are compared and simulated under different conditions.The results show that:1)the filtering algorithm has less dependence on the initial value of the filter;2)the filtering stability is better when the observation noise or disturbance noise is large;3)the observation noise will not have cross-influence on the filtering effect of the state variables;4)the filtering accuracy on the target location is higher than the EKF algorithm,and the filtering accuracy on the heading and the speed is basically the same as the EKF algorithm.