Application Research On Space-Time Compressive Sampling In Radar

Multiple-input multiple-output (MIMO) radar is currently an important point in theradar field. It has many advantages when compared with conventional radars. However,with the development of the broadband radar signal processing technology, theresponding sampling, transporting and processing of the signals are under tremendouspressure. This paper has focused on the application of the compressive sampling (CS) inMIMO radar.Two methods of CS for the direction of the arrival (DOA) estimation areintroduced in this paper, which are CS in time domain and spatial domain. These twomethods compress the number of samplings and arrays, respectively. It can be seenfrom a detailed simulation that both methods could significantly reduce the computationburden, and a high angular resolution could be maintained as well. Then, this paperdescribes an approach of CS in time domain to estimate the Angle-Doppler. TheAngle-Doppler domain is discrete, and then the received signal is projected in thisdomain. At last, the information of targets can be got by sparse reconstruction. Thismethod not only reduces the number of samplings, but also realizes the high resolutionestimation of space-time.Afterwards, a design of measurement matrix by transmitting waveforms for CSbased on MIMO radar is presented. Compared with the traditional Gauss randommeasurement matrix, this method has a higher signal-to-interference ratio (SIR) andlower correlation of compressing matrix. In the research of simulations, the SIRbetween this method given and traditional measurement is compared, and theperformance of the parameter estimation is also described.