The Study And Hardware Implementation Of Adaptive Target Tracking Algorithm In Radar

Radar target tracking technology is widely applied in military and civilian areas,such as battlefield surveillance, remote forewarning, aviation and transportation.However, the complexity of the environment and uncertainty of moving targets would lead to the complexity of the radar target tracking system. In order to track the moving targets effectively, aiming at the problems above-mentioned, the main content of this paper is summarized as follows:Firstly, the target tracking system is analyzed at first, and the tracking system is divided into linear system and non-linear system. According to the different system models of moving targets, corresponding algorithms are analyzed and applied for estimating the optimal state of moving target. State variable selection and data preprocessing are studied via coordinate transformation.Secondly, for the linearization motion target, it can be distinguished from clutter interference by information of velocity and amplitude. Based on Hough transform,the information above is utilized for calculation of adds weighting factor, and then amplitude accumulates are conducted. Thus, the linear target track initiation can be realized. For the target maneuver caused by the clutter and noise, ant colony similarity algorithm is employed to detect deviate points of target trajectory. In addition, the proposed algorithm for linear target track initiation is realized via the FPGA in this paper, mainly including the design of sine or cosine signal generator and the weighted Hough transform domain. The simulation results of Matlab and the design of the FPGA indicate that the weighted Hough transform is effective for linearization target track initiation.Finally, for the non-linearization motion target, due to the strong mobility of motion target, based on particle filter algorithm, an adaptive strong tracking particle filter method is proposed in this study. To solve particle degradation in particle filter problem and track abrupt motion state of targets, an adaptive strong tracking PF algorithm is presented in this paper. According to the residual between the actual measurement values and predicted measurement values, the proposed algorithm adaptively changes the forgetting factor and the softening factor, then, by calculating the fading factor, transfer function and the filter gain, updating the importance density function, the bootstrap fission(BF) is used to suppress the particle degradation of PF in the re-sampling stage. Simulation results show that the algorithm can track the target abrupt motion state, enhance the system stability and improve the tracking accuracy of the system.