Microwave Imaging Technique Based On The Dynamic Characteristics Of The Target Under Complex Electromagnetic Environment

Through-the-Wall Radar(TWR) plays an important role in some key fields such as modern warfare battle, anti-terrorism and disaster relief. For its unique capability which could detect and image human beings in areas behind walls or obstacles where is hard to reach under normal situation, TWR provides crucial information before the launch of the operation and ensures the effectiveness during the whole operating period. So it’s necessary to do more research no matter on its theoretical level or application level.For the demands of a better imaging quality, both of the aperture of antenna and bandwidth of transmitting signal need to be enlarged. As a result, the complexity of the hardware and software system such as high sampling rate and heavy transporting burden increases which restricts the performance of the system.With respect to the problems mentioned above, two key points have been studied based on the principle of the Single-Input and Multi-Output(SIMO) TWR radar and the physical process of transmitting signal, one of which is the influence of walls and the corresponding compensating method. And the other one is the utilizing of moving targets’ characteristic during image acquisition. Aiming at these problems, the research of this thesis lies as below:1. Made an introduction of the synthesis aperture radar imaging which is based on SIMO radar. Discussed the relation between the main radar parameters and the imaging performance and provided numerical simulation result.2. Study traditional TWR radar as well as the influence of the walls to the electromagnet wave. With the established model, an improved wall parameter estimation method was provided which is based on the minimum entropy of the image under two different array positions. Numerical simulation verified the effectiveness of the method which could improve the performance of the focusing and imaging of the targets.3. A CS imaging method was proposed based on the spatial sparsity of the targets after Change Detection(CD). Within the proposed method, the sampling rate of the signal was much lower than the request based on the Nyquist Sampling Theory and the information of the targets was obtained successfully as traditional TWR did. Numerical simulation verified the effectiveness on decreasing the sampling rate of the system. Finally, conclusions were draw based on the discussion of the relation between the system parameters and the CS imaging performance.