Research On UWB MIMO Radar Signal Processing Technology Based On Compression Sensing

UWB MIMO radar systems with the characteristics of waveform diversity and space diversity have advantages on anti-interference and anti-stealth. But due to the multiple array structures adopting by the transmitter and the receiver, it will bring the huge challenges to signal acquisition and processing for the radar system. If we use the signal acquisition and processing method based on traditional Nyquist sampling theorem, it is bound to cause difficulties on system implementation and real-time processing. Recently, compressed sensing (CS) technology is a new rapidly developing technology based on the compressed transform and data reconstruction. Recent studies have shown that CS technique can reduce the rate of signal sampling and the overall amount of data effectively. It has wide application prospects in the UWB MIMO radar signal processing. The thesis focus on aspects of transmitting signal waveform, system architecture, sparse transform and signal reconstruction based on the need of relevant research subject of a UWB MIMO radar.This thesis mainly focus on the following aspects:Firstly, orthogonal waveform design for the UWB MIMO radar transmitting signal. The transmit signals in this thesis adopt the ultra-wideband OFDM-LFM signals and Morlet wavelet signals. And then the thesis calculates and simulates the transmit signals’ auto-correlation and cross-correlation properties for verifying the feasibility of the above two kinds of waveform as the transmitting signals of MIMO radar.Secondly, system structure analyzing and radar signal modeling for MIMO radar. On modeling, the locations of transmitting arrays are random spatial diversity distribution, and the receiving arrays are co-located distribution. The main purpose of adopting transmit diversity structure is to exploit the spatial diversity gain to improve the target detection performance. Furthermore, the thesis analyzes and establishes a model in radar system under certain scenarios with sparse target distribution.Thirdly, researches on sparse transform methods of UWB MIMO radar signal. When the transmitting signals are UWB OFDM-LFM signals, the echo signals are processed in the receiver terminals by the Stretch transform. Similarly, when the transmitting signals are ultra-wideband Morlet wavelet signals, the echo signals are processed by inverse Morlet wavelet transform.Lastly, target reconstruction modeling based on compressed sensing. Sparse matrix and measurement matrix are derived on the basis of the compressed sensing reconstruction model. Then, three kinds of reconstruction algorithms are researched to reconstruct the targets. By MATLAB simulating, the thesis verifies the feasibility of the signal processing design based on compressed sensing for UWB MIMO radar and compares their qualities of target reconstruction.