Research On Space-Time Adaptive Processing For Airborne Cognitive Radar

Cognitive radars are intelligent radars which forming a closed-loop system from transmitter optimization,environment perception,receiver processing to feedback control.Transmit adaption and knowledge-aided signal processing are the two principal characteristics of cognitive radar.Knowledge-aided space-time adaptive processing(KA-STAP)can improve the performance of radar in heterogeneous clutter environment by introducing priori knowledge.Existing KA-STAP algorithms mainly focus on the receiver.In the framework of airborne cognitive radars,the combination of transmit adaptive processing and KA-STAP is a new idea of heterogeneous clutter suppression.This paper studies the airborne cognitive radar space-time adaptive processing algorithms,and the main works are as follows:1.A clutter covariance matrix estimation method based on receiver signal information and priori knowledge is proposed.This method uses array priori knowledge and receiver signal to estimate clutter track,CNR and clutter spectrum width.A priori clutter covariance matrix based on the GCM model is obtained.This method improves the accuracy of the priori clutter covariance matrix,which is helpful to improve the clutter suppression performance of KA-STAP.The effectiveness of the algorithm is verified by the measured data processing.2.A cognitive transmit space-time weight design method is proposed.Firstly,a method of knowledge-based transmit space-time weight design is introduced.This method can set nulls in the clutter ridge on pattern.Secondly,another transmit space-time weight optimization method based on the principle of MVDR filter is introduced.This method utilizes priori knowledge such as clutter spectrum width and clutter energy information,which have a better performance of clutter suppression.However,this method does not conducive to the extraction of clutter information at the receiver,which affects the feedback control of the loop from the receiver to the transmitter.In the case of the priori information mismatch,transmit space-time weight cannot be further adjusted,which due to a bad closed-loop control chain.For above considerations,a cognitive transmit space-time weight design method is proposed which suppresses main-lobe clutter and side-lobe clutter.This method can not only effectively reduce clutter energy at the transmitter,but also retain some clutter information for the receiver.The effectiveness of the method is verified by the simulation.3.The received signal processing model and the optimized transmitting KA-STAP algorithm are proposed.The received signal processing model after transmit space-time optimization considers the effects of transmit space-time weight.Then extends the General Clutter Model,a clutter covariance matrix estimation method contains transmit space-time weight is presented.Finally,compare and discuss the difference between optimized transmitting KA-STAP and conventional transmitting KA-STAP.