| Inspired by multiple-input multiple-output (MIMO) communication technique and synthetic impulse and aperture radar (SIAR), MIMO radar is proposed and becomes the research focus concerned by scholars from many countries. As a new radar, MIMO radar is capable of transmitting arbitrary waveform from each antenna element, so it can exploit waveform diversity and space diversity. By exploiting these potentials, MIMO radar has several advantages, such as excellent interference rejection, improved parameter identifiability, enhanced flexibility for transmit beampattern design, advanced ability of low speed target detection and weak target detection in clutter environment, improved performance on low probability of intercept and target recognition.In this dissertation, MIMO radar waveform design and signal processing algorithms are investigated, and the main research focus on the following issues:[1] Investigate the design method of transmitting waveforms for MIMO radar. Based on the analysis of the ambiguity function, the performance of discrete frequency coding waveform (DFCW) is studied. For full-code set DFCW, the normalized range autocorrelation sidelobe peak almost does not depend on the firing order of frequency, so waveform design method with low complexity is proposed which can only consider the range cross-correlation to design the DFCW full code set; for non-full code set DFCW, its bound of ASP is lower than full code set's, so waveform design method with better correlation performance based on minimax criteria is proposed, and then range resolution and velocity resolution are analyzed. Orthogonal frequency division multiplexity (OFDM) used in MIMO radar is analyzed, and OFDM-code waveform design method is proposed.[2] Investigate receive beamforming of colocated MIMO radar. Based on mathematical analysis, the connection of antenna spacing and beampattern for MIMO radar with standard linear array is given. For grating lobes, a novel algorithm which can synthesize least squares error (LSE) receiving pattern subject to a set of null constraints is proposed. For additional virtual sensors at receiver of MIMO radar, conventional beamformer and minimum variance distortionless response (MVDR) beamformer are extended and applied for MIMO radar. And the performance of beamformers is compared under MIMO radar and phased array radar. For improving the robustness of sample matrix invert algorithm, diagonal loading is applied under MIMO radar.[3] Investigate the transmit beamforming technology of MIMO radar. MIMO radar can synthesize a desired spatial transmit beampattern through the selection of signal sets with arbitrary cross-correlation properties. For a given transmit beampattern, it can be achieved by designing the cross-correlation matrix of the probing signal vector transmitted by MIMO radar. Using the designing idea, the methods based on least square (LS) criteria and minimax criteria are studied, and the optimizing models based on gradient search and genetic algorithms are built. For designing a signal set which can approximate a desired spatial transmit beampattern, the methods based on known cross-correlation matrix and desired spatial transmit beampattern are proposed respectively.[4] For separating the echoes of different transmitting waveforms of MIMO radar, the methods based on matched filter and mismatched filer are studied. Because the performance of the separating method based on matched filter is poor, it can be improved by using the idea of compound filter and the approach based on a minimum mean-square error (MMSE) formulation. Based on the idea of compound filter containing a pre-filter and an inverse filter, a novel method of separating the echoes of different transmitting waveforms of MIMO radar is proposed, but the loss of signal to noise ratio (SNR) is large. The approach based on a MMSE formulation exhibits small SNR loss and is robust to doppler mismatch.
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