Moving Target Detection Algorithm For Airborne Radar

STAP is an effective technique for airborne radar to detect moving targets in strong clutter environment.The performance of STAP depends on the construction precision of the clutter covariance matrix.According to the RMB criterion,when the training sample to estimate the clutter covariance matrix is sufficient and satisfies the independent and identical distribution,the detection performance of the moving target will not be affected.However,airborne radar actually works in nonhomogeneous environment.It is difficult to meet the above conditions,resulting in decrease in the estimation accuracy of the clutter covariance matrix and affect the detection performance of the airborne radar moving target.How to improve the estimation precision of the clutter covariance matrix and improve the detection performance of the airborne radar moving target is the main research content of this paper.The specific research contents are as follows:1.A moving target detection algorithm based on training sample selection and sparse recovery for airborne radar is proposed,that overcomes interfering target in selected training samples,to solve the degradation of moving target detection probability in heterogeneous training samples.It makes full use of the sparse property of samples,attempts to select training samples whose clutter locations are similar to that of the sample in the unit under test.Eliminating the interfering target in the selected training samples to overcome the influence on moving target detection probability.Using the processed training samples and the data of the undetected distance cell to construct covariance matrix.2.Aiming at solving the problems of larger computational complexity and larger search space on sparse recovery algorithm,a fast robust sparse recovery STAP algorithm based on moving target protection constraint is proposed.On the one hand,this algorithm can use a priori knowledge of the clutter to reduce the dimension of space-time oriented Dictionary.On the other hand,this algorithm adds moving target protection constraints in space-time oriented Dictionary when recovers the unit under test.This algorithm reduces the dimension of space-time oriented Dictionary and adds moving target protection constraints.3.In order to improve the performance of moving target detection,local searching spectral characteristics of the moving target detection algorithm is proposed based on image feature-based space-time processing for ground moving target detection algorithm.This algorithm makes full use of the different characteristics of clutter and target in angle doppler domain,using region growingimage segmentation algorithm and local optimization algorithm to pick up target information in angle doppler domain.All above methods are guaranteed their validities by computer simulation.