SQR: Successive QCQP refinement for MIMO radar waveform design under practical constraints

• Published in: Conference record - Asilomar Conference on Signals, Systems, & Computers pp. 85 - 89
• Main Authors: Aldayel, Omar, Monga, Vishal, Rangaswamy, Muralidhar
• Format: Conference Proceeding Journal Article
• Language: English
• Published: IEEE 01.11.2015
• Subjects: Algorithm design and analysis; Conferences; constant modulus; Constants; Design engineering; Interference; Mathematical analysis; Maximization; MIMO; MIMO radar; Optimization; phase coding; Signal to noise ratio; Similarity; similarity constraint; SQR; successive algorithm; waveform design; Waveforms
• ISSN: 1058-6393
• DOI: 10.1109/ACSSC.2015.7421087

We address the problem of designing a waveform for Multiple-Input Multiple-Output (MIMO) radar under important practical constraints, namely the constant modulus and the waveform similarity constraints. Incorporating these constraints in an analytically tractable manner continues to be longstanding open challenge. This is because the optimization problem that results from Signal to Interference plus Noise Ratio (SINR) maximization subject to these constraints is a hard non-convex problem. We develop a new analytical approach that involves solving a sequence of convex Quadratic Constrained Quadratic Programming (QCQP) problems, which we prove converges to a sub-optimal solution. We call the method Successive QCQP Refinement (SQR). We evaluate SQR against state of the art in its SINR performance for a practical scenario and show that it outperforms existing methods without incurring a significant computational burden.