In order to solve the problem of performance degradation when radar system is influenced by clutter from mainlobe and sidelobe, MIMO radar waveform design algorithm based on knowledge of range-spread target and clutter is investigated. Firstly, an optimization cost function is established, which includes mainlobe gain, sidelobe clutter suppression capability and Signal to Clutter plus Noise Ratio (SCNR) improvement. Secondly, to tackle the optimization problem, a relaxation is made to decouple spatial and temporal domain of the waveform matrix, beamforming and waveform design can be solved independently. Thirdly, L-BFGS algorithm is used to design the unimodular waveform matrix, beampattern with lower sidelobe and deep null is got. Based on maximization of SCNR, transmitted waveform and receiving filter are designed by iterative algorithm. Finally, the effectiveness of the proposed algorithm is verified by electromagnetic simulation of range-spread target.
VESPE M, JONES G, and BAKER C J. Lessons for radar: waveform diversity in echolocating mammals[J]. IEEE Signal Processing Magazine, 2009, 26(1): 65-75.
[2]
YANG Y and BLUM R S. Minimax robust MIMO radar waveform design[J]. IEEE Journal of selected Topics in Signal Processing, 2007, 1(1): 147-155.
[3]
COCHRAN D, SUVOROVA S, HOWARD S D, et al.. Waveform libraries: measures of effectiveness for radar scheduling[J]. IEEE Signal Processing Magazine, 2009, 26(1): 12-21.
[4]
JIU Bo, LIU Hongwei, ZHANG Lei, et al. Wideband cognitive radar waveform optimization for joint target radar signature estimation and target detection[J]. IEEE Transactions on Aerospace and Electronic Systems, 2015, 51(2): 1530-1546.
[5]
YAN Junkun, JIU Bo, LIU Hongwei, et al. Prior knowledge- based simultaneous multibeam power allocation algorithm for cognitive multiple targets tracking in clutter[J]. IEEE Transactions on Signal Processing, 2015, 63(2): 512-527.
[6]
YAN Junkun, LIU Hongwei, JIU Bo, et al. Power allocation algorithm for target tracking in unmodulated continuous wave radar network[J]. IEEE Sensors Journal, 2015, 15(2): 1098-1108.
[7]
TURLAPATY A and JIN Yuanwei. Bayesian sequential parameter estimation by cognitive radar with multiantenna arrays[J]. IEEE Transactions on Signal Processing, 2015, 63(4): 974-987.
[8]
AUBRY A, DE MAIO A, FARINA A, et al. Knowledge- aided (potentially cognitive) transmit signal and receive filter design in signal-dependent clutter[J]. IEEE Transactions on Aerospace and Electronic Systems, 2013, 49(1): 93-116.
[9]
AUBRY A, DE MAIO A, JIANG Bo, et al. Ambiguity function shaping for cognitive radar via complex quartic optimization[J]. IEEE Transactions on Aerospace and Electronic Systems, 2013, 61(22): 5603-5619.
[10]
CHEN Chunyang and VAIDYANATHAN P P. MIMO radar waveform optimization with prior information of the extended target and clutter[J]. IEEE Transactions on Signal Processing, 2009, 57(9): 3533-3544.
[11]
GUERCI J R. Cognitive Radar: The Knowledge-Aided Fully Adaptive Approach[M]. Norwood, MA, USA, Artech House, 2010, Chapter 2.
[12]
HULEIHEL W, TABRIKIAN J, and SHAVIT R. Optimal adaptive waveform design for cognitive MIMO radar[J]. IEEE Transactions on Signal Processing, 2013, 61(20): 5075-5089.
[13]
JIU Bo, LIU Hongwei, WANG Xu, et al. Knowledge-based spatial-temporal hierarchical MIMO radar waveform design method for target detection in heterogeneous clutter zone[J]. IEEE Transactions on Signal Processing, 2015, 63(3): 543-554.
[14]
KISIALIOU M, LUO X D, and LUO Z Q. Efficient implementation of quasi-maximum-likelihood detection based on semidefinite relaxation[J]. IEEE Transactions on Signal Processing, 2009, 57(12): 4811-4822.
[15]
WANG Yongchao, WANG Xu, LIU Hongwei, et al. On the design of constant modulus probing signals for MIMO radar[J]. IEEE Transactions on Signal Processing, 2012, 60(8): 4432-4438.