Research On Knowledge-Aided Space-Time Adaptive Processing

Airborne early warning radar can accurately and rapidly detect targets,monitor changes in the battlefield,and provide support for battle command and control system,which plays an important role in the modern battlefield.However,in the process of searching and tracking moving targets,airborne radar inevitably receives a large number of ground clutter.Due to the motion of the radar platform,ground clutter echoes in different directions have different radial velocity,which results in the broadening of the clutter spectrum in the Doppler domain.Consequently,the weak target is submerged in clutter and difficult to detect.Space-time adaptive processing(STAP),as a two-dimensional filter combining space and time domain,can effectively suppress clutter and improve target detection performance.In order to obtain the STAP filtering weight vector,enough statistically independent and identically distributed(IID)secondary samples selected from the surrounding the cell under test are required to es-timate clutter covariance matrix.However,realistic clutter appears heterogeneous due to radar array configuration,heterogeneous environment and other non-ideal factors.As a re-sult,the secondary samples are no longer IID,leading to the shortage of secondary samples and inaccurate estimation of the CCM.The dissertation focuses on improving the suppres-sion performance of STAP for heterogeneous clutter.The main contents are summarized as follows:1.The research on ground clutter characteristics and heterogeneous clutter simulation based on a priori knowledge.First,the echo signal model of airborne radar is estimated,and the characteristics of the clutter are analyzed.Then,the heterogeneous clutter simulation method for a specific scene using elevation data and land cover data is discussed.Finally,the simulation of the clutter simulation method is carried out,and the results show that the method can effectively simulate heterogeneous clutter received by airborne radar.2.The research on knowledge-aided heterogeneous clutter suppression method.The basic principle of STAP is introduced,and the causes and effects of heterogeneous clutter are an-alyzed.In order to suppress the heterogeneous clutter caused by radar configuration and the radar-illuminated environment,a clutter covariance matrix reconstruction algorithm using other beam received data is proposed.In the proposed algorithm,the echo data of different beam pointing are exploited to obtain the clutter power by spectrum estimation methods,and then the CCM is reconstructed.The algorithm only uses the data of the same distance on different beams,which avoids the adverse effects caused by heterogeneous clutter in other range gate data and thus improve the suppression performance of heterogeneous clutter.3.The research on algorithm of reducing the number of false alarms.The echo data are detected after clutter suppression.However,the residual clutter still has an adverse effect on target detection,especially the discrete clutter.Therefore,we analyze the mechanism of false alarm caused by strong discrete clutter,and propose a false alarm removal algorithm.In the proposed algorithm,the clutter in the range-Doppler cell whose output is higher than the detection threshold is suppressed and the output is used to distinguish whether there are real targets in the cell.The output after clutter suppression is used to determine whether it is a false alarm point or not.Finally,simulations are carried out and the results verify that the proposed algorithm can eliminate false alarms caused by strong sidelobe clutter.