Research On Adaptive Optimization Of Radar Waveform For Target Tracking

In order to improve the performance of the radar,adaptive technology is applied to the radar system,which effectively improves the radar environment adaptability and information processing performance.As a research hotspot in the field of radar,radar target tracking has been widely concerned by researchers for many years,and the key factor to improve the performance of radar tracking is the adaptive optimization of radar transmission waveform.In this thesis,the adaptive optimization of transmission waveform for radar target tracking in ideal environment,for radar target tracking in clutter environment and radar multi-target tracking in clutter environment are studied respectively,the specific content is summarized as follows:1.Aiming at the optimization of transmitting waveform for radar target tracking in ideal environment,this thesis proposes a transmitting waveform optimization method based on the maximum mutual information criterion.Firstly,based on the maximum mutual information criterion,this thesis takes the maximum mutual information between the target observation value and the predicted value as the optimization objective function.Then the Tent mapping and Gaussian perturbation are used to improve the bald eagle search algorithm,and the objective function is solved to obtain the optimal transmission waveform at the current moment.Finally,the Kalman filter algorithm is used to track the target,and the obtained target state is input into the optimization function to achieve adaptive waveform optimization.The simulation results show that the improved bald eagle search algorithm in this thesis has faster convergence speed and higher solution efficiency,and the tracking error can be significantly reduced by using the proposed algorithm.2.Considering the optimization of transmitting waveform for radar target tracking in clutter environment,this thesis proposes a waveform optimization method based on multitarget bald eagle search algorithm.First of all,the distance error and velocity error dimensions of target tracking are inconsistent,which leads to the coupling problem,this thesis proposes to take the minimum distance tracking error and minimum velocity tracking error as the optimization objective function,and establishes a multi-objective optimization function framework.According to the characteristics of the objective function,Pareto optimization principle is used to improve the bald eagle search algorithm to solve the objective function,so as to get the Pareto optimal solution set of the above multi-objective optimization function,and then the roulette principle is used to get the optimal transmission waveform parameters at the current time.Finally,the joint probabilistic data association algorithm is used to track the target,and the obtained target state is input into the optimization function to achieve adaptive waveform optimization.It can be seen from the simulation results that the proposed algorithm overcomes the coupling problem of distance and velocity error well,and can significantly improve the accuracy of target tracking in clutter environment.3.Based on the optimization of transmitting waveform for radar multi-target tracking in clutter environment,this thesis proposes a transmit waveform optimization method based on the improved branch and bound method.Firstly,in view of the clutter environment,this thesis introduces the clutter improvement factor under the framework of the minimum noise covariance,and the threat degree of each tracking target is obtained by grey correlation analysis method,which is used as the weight to construct the objective function of waveform optimization.Then,the branch-and-bound method is combined with the optimized bald eagle search algorithm to solve the above objective function,and the optimal transmit waveform parameters are obtained.Then,considering the solidification of the transition probability in the interactive multi-model algorithm,the logarithmic function is used to link the model transition probabilities of the two moments before and after,so the transfer probability matrix is weighted accordingly.Finally,the improved interactive multi-model algorithm and the joint probability data association algorithm are combined to track each target in the clutter environment,and the obtained target states are input into the optimization function to achieve adaptive waveform optimization.Simulation results show that the proposed method can significantly improve the performance of the system and reduce the multi-target tracking error in the clutter environment.