Study On Clutter Suppress And Tracking Algorithm Of Airborne Surveillance Radar

Airborne surveillance radar not only possess the capability of making early warning to aircrafts and missiles,but is able to detect the ship on the sea,so it plays an important role in the war.Airborne radar is located in the high altitude,the echo airborne radar receives when it looks down contains a large number of clutter which we don't need.Due to the motion of the platform,the spread of the clutter in the Doppler space is very serious,and the power of the clutter itself is very large so the long distance small target is easily submerged in the clutter.These phenomenon will result in the degradation of the radar system's detection performance,and will make it difficult for radar to estimate the targets' parameters and track targets.Among the airborne radar signal processing technologies,space-time adaptive processing(STAP)technology aims at the space-time distribution characteristics of the clutter in the airborne condition.It combines the spatial and temporal sampling data to suppress the clutter and improve the target detection performance of airborne radar,so it is a vital technology for airborne radar to fit the complex geographical conditions.In the airborne radar data processing,the clutter is dense and the tracks of large amounts of targets may cross each other due to the complex battlefield environment,in that case,the multi-objective data association algorithm is needed to realize the accurate association between the measured data and the target track in order to develop the performance of target tracking.A good tracking association algorithm is a key technology for airborne radar to adapt to complex target environments.In this thesis,the airborne radar clutter suppression and multi-target tracking theory is studied,we not only improve the existing methods but put forward a new method.The research results include:1.Based on the clutter model of airborne radar,the Doppler characteristics of clutter and the two-dimensional azimuth-Doppler distribution of clutter at different crabs are studied.On this basis,the basic principle and analysis of two common STAP reduction methods are studied.The performance of these two methods are analyzed and compared through simulation experiments.2.Aiming at the problem of clutter heterogeneity airborne radar encounters in the practical application,the reasons of clutter heterogeneity are analyzed,and two common non-homogeneity detectors are studied.A method of clutter suppression under the condition of non-sidelooking array is proposed.The method makes full use of the system's spatial degrees of freedom,it makes adaptive processing in the element-pulse domain,and selects few training samples to estimate the covariance matrix combing FRACTA algorithm,trying to develop the suppress performance of sidelobe clutter.Through the processing of the measured data,we validate the advantages the proposed method has in the aspect of sidelobe clutter suppression.3.This thesis studies the target tracking theory and designs a system frame of multi-target tracking.We focus on the analysis of common data association algorithms based on Bayes theory and improve two of them.Simulation results show that these improvements can significantly improve the tracking performance of radar systems.