High Resolution Radar Imaging Based On Higher-Order Statistics

The research presented investigates the use of higher-order statistics to the imaging techniques of high resolution radar targets.After briefly reviewing the developments of radar imaging and harmonic retrieval based on higher-order statistics, the first chapter discusses the main problems in these areas and introduces the main contents of this dissertation.Motion compensation of space target is studied in chapter 2. Firstly the influence on HRRP (high resolution range profile) of space target because of its translation and rotation is analyzed after the mc-PPS model of radar echoes is derived. Based on product high-order ambiguity function (PHAF), two methods to compensate the motion are proposed.Super resolution imaging methods for one-dimensional imaging is studied using fourth-order mixed c umulants (FOMC) in chapter3.At first, we extended the FOMC of sinusoids to damped exponential model (DE) and prove its asymptotic blind Gaussian noise character, then two efficient methods named FOMCMP and FOMCESPRIT for estimating the parameter of DE model in the presence of colored Gaussian noise are proposed. Monte Carlo simulations are demonstrated lastly.In the next chapter 4, the definitions and methods are extended to the two-dimensional (2d) ISAR imaging. Similar results of blind Gaussian noise character of 2d-FOMC are derived. The computation efficiency of the proposed method named 2d-FOMCESPRIT is greatly improved by holding the feature matrix's dimension in the condition of a long data record. Simulation results show that 2d-FOMC can suppress the colored Gaussian noise more effectively and has higher efficiency than former super resolution methods.In chapter 5, the cyclic statistics based radar imaging is discussed in the presence of additive and multiplicative stationary noise with any statistic distribution. The concepts of product and cumulate cyclic statistics are introduced and their asymptotic character is proved. A new approach based on product cyclic average for multi-component harmonic retrieval with random or time-varying amplitudes is presented. Finally, tests based on simulation data and real data validate the new method.At last, Summary of this dissertation is made and the problems which need further research are pointed out in chapter 6.