Title :
MIMO radar waveform design for multiple extended targets using compressed sensing
Author :
Daniel, Andy ; Popescu, Dimitrie C.
Author_Institution :
ECE Dept., Old Dominion Univ., Norfolk, VA, USA
Abstract :
In this paper we study joint radar waveform and receiver filter design to detect the presence of multiple extended targets with known impulse responses. Our approach uses a novel vector channel framework for multiple-input multiple-output (MIMO) radar, which makes the problem of detecting multiple targets equivalent to reconstructing a spatially sparse radar scene and allows the use of a compressed sensing procedure to jointly optimize the radar waveforms and receiver filters with respect to a mutual coherence criterion. The proposed approach is illustrated with numerical results obtained from simulations, which show that the reconstruction error when the jointly optimized radar waveforms and receiver filters are used is less than when statically defined waveforms and receiver filters typically used in compressed sensing are employed.
Keywords :
MIMO radar; compressed sensing; filtering theory; radar detection; radar receivers; radar signal processing; signal reconstruction; MIMO radar waveform design; compressed sensing procedure; joint radar waveform and receiver filter design; multiple extended target detection; multiple-input multiple-output radar; mutual coherence criterion; novel vector channel framework; reconstruction error; spatially sparse radar scene; Algorithm design and analysis; Compressed sensing; Noise; Radar detection; Receivers; Vectors; MIMO Radar; compressed sensing; detection; extended targets; waveform design;
Conference_Titel :
Radar Conference, 2014 IEEE
Conference_Location :
Cincinnati, OH
Print_ISBN :
978-1-4799-2034-1
DOI :
10.1109/RADAR.2014.6875656