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Open Access Publications from the University of California

On Convex Relaxations for Joint Transmit-Receive Design in Radar Systems

  • Author(s): O'Rourke, Sean
  • Advisor(s): Swindlehurst, A. Lee
  • et al.

This dissertation investigates joint design of transmit and receive resources in radar systems, given prior knowledge of a signal-dependent clutter environment, based on simultaneous convex relaxation. Motivated by waveform-adaptive space-time adaptive processing

(WA-STAP), we first analyze traditional approaches to joint trans-receive design, which alternate between optimal signal designs for fixed filters and vice versa to maximize signal-to-interference-plus-noise ratio (SINR). First, we demonstrate that SINR & its variants are

non-convex bi-quadratic programs (BQP). Next, we provide perspectives on current alternating methods used to solve BQPs in terms of linear semidefinite (SDP) & quadratically-constrained quadratic (QCQP) programs. We then develop a novel method of performing this

joint design based on quadratic semidefinite programming (QSDP). Our proposed relaxation scheme first analyzes the power-constrained problem, and is accompanied by exploration of operator structures for signal-dependent clutter. This technique is then extended to more

challenging waveform constraints -- in particular, constant modulus and similarity constrained designs. A refinement scheme is devised to improve recovery of vector solutions from therelaxed matrix solution for the constant modulus problem. Finally, we apply the technique

to a system model other than WA-STAP; namely, the reverberant sonar/radar channel. Numerical simulations are provided to show the superior performance of our method for SINR, detection, & resolution across multiple environmental scenarios.

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