Study On Heterogeneous Clutter Suppression Algorithms For Airborne Radar

In the past years,the phased-array is widely applied in the airborne radar.The airborne radar clutter suppression catches more attention.The movement of airplane will make the clutter couple strongly spatially-temporally.In order to suppress airborne radar clutter effectively,the well-known STAP(space-time adaptive processing)algorithms are widely researched.As the dimension of the signals and the number of the array antennas increase,the problems of the high computational complexity becomes much more serious.In order to reduce the computational complexity,various suboptimal dimension-reduced STAP algorithms have been developed rapidly too.However,the conventional STAP algorithms and suboptimal dimension-reduced STAP algorithms are based on the conditions under which the clutter environment is homogeneous and the sample data is independently and identically distributed.Thus,under ideal conditions these algorithms can achieve good performance.In the practical engineering applications,the airborne radar usually faces inhomogeneous clutter environment.The clutter model under homogeneous environment is no longer applicable.In the meantime,the performances of the conventional STAP algorithms face serious degradation.Hence,this paper is based on the airborne phased-array radar and mainly research on the heterogeneous clutter and the algorithms of it.The main contributions of the thesis are summarized as follows:1.Chapter 2 mainly introduces the homogeneous clutter model and the theory of conventional STAP.First of all,we establish the geometry model,mathematical model and matrix-vector model under the homogeneous clutter environment and introduce some common parameters such as clutter power spectrum,clutter characteristic spectrum and IF(Improvement Factor).Then,we introduce the theory of the well-known STAP algorithms and several suboptimal dimension-reduced STAP including JDL(Joint Domain Localized algorithm),FA(Factored Approach),EFA(Extended Factored Approach).In the last,we change some parameters such yaw angle,speed of flight and so on in simulation experiments and analyze the characteristics of airborne radar homogeneous clutter with different parameters.And we also analyze the performance of some different STAP algorithms.2.Chapter 3 mainly introduces the method to establish the airborne radar heterogeneous clutter model and disscuss how this clutter model influences the performance of STAP algorithms.Firstly,we analyze the background of establishing the airborne radar heterogeneous clutter and raise a new concept — heterogeneous factor which can quantitatively analyze the heterogeneity of clutter to some extent.Then we establish different airborne radar heterogeneous clutter through changing the heterogeneous factor.Thirdly we come up with the process of calculating the airborne radar heterogeneous clutter.Finally in simulation experiments we analyze how the airborne radar heterogeneous clutter influences the performance of conventional STAP algorithms.3.Chapter 4 mainly introduces the method to suppress the cognitive airborne radar heterogeneous clutter.In the first,we introduce the theory and method of TDPC algorithm which is based on the cognitive radar.And we put TDPC algorithm as the pre-filter to improve the performance of STAP algorithms.Secondly we propose the method of suppressing the cognitive airborne phased-array radar heterogeneous clutter.We mainly introduce how to establish the covariance matrix of the cognitive airborne radar heterogeneous clutter and calculate the optimal weight of filter through calculating the linear constrained optimization problems.In the end,these methods are proved effectively through simulation experiments.TDPC(two-dimensional-pulse-to-pulse canceller)algorithm can be the pre-filter to suppress the most of clutter,reduce the degree of clutter freedom and improve the performance of suboptimal dimension-reduced STAP algorithms.We also consider the array element error.The simulation results prove that cognitive methods can improve the performance of clutter suppression comparing with non-cognitive methods.