| The MIMO radar system is composed of multiple spatial distributed transmitting/receiving elements. Making use of the characteristics of phased-array radar and synthetic impulse aperture radar (SIAR), Utilizing the spatial distributed elements and orthogonal waveforms to obtain spatial diversity and increased system degree of freedom, Utilizing the advanced signal processing technique, MIMO radar can achieve great improvements on target detecting, parameter estimation, clutter and jammer suppression, anti-destruction, anti-stealth.etc. There are two different types of MIMO radar systems: coherent MMIO radar system and noncoherent MIMO radar system. This dissertation investigates the coherent MIMO radar signal processing issues about the matched filtering, digital beam forming (DBF), space-time adptive processing (STAP), etc. The main research focus on the following issues:1. Study and analyze the principles and system structure of MIMO radar. The signal model of airborne coherent MIMO radar is builded. It can work on three different modes by setting the system parameters with different values. Then, the mainly characteristics of MIMO radar are analyzed.2. A general analysis is performed on MIMO radar signal processing. First, we analyze the relationship between virtual array and transmitting/receiving array for MIMO radar. Then, the matched filter and digital beam forming technology are investigated. And a detailed analysis is performed on cramer-rao bound (CRB) of angle estimation, the CRB of angle estimation for MIMO radar using space-time domain information is given. Lastly, the ground moving target indication (GMTI) of airborne MIMO radar is analyzed.3. The space-time adptive processing technique for airborne MIMO radar is studied. First, we compare the differences of STAP between phased-array radar and MIMO radar. Then, based on further analysis of clutter suppression principle of STAP, a reduced-rank STAP algorithm based on clutter subspace is derived. Then, the rank of clutter subspace for linear-array and arbitrary-array MIMO radar is analyzed. According to the characteristics of clutter signals, we utilize a set of prolate spheroidal wave functions (PSWF) to approximate the clutter signals, and this set of PSWF basis vectors form almostly the same subspace as clutter eigenvectors. Lately, combining with the former reduced-rank algorithm and the PSWF basis vectors, we propose a new reduced-rank STAP algorithm based on basis vectors estimation of clutter subspace, and compare it with the other reduced-rank STAP algorithms. The results show that the new algorithm can effectively reduce the computational complexity, meanwhile, it keeps the clutter suppression performance of STAP algorithm. |
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