Relaxed Biquadratic Optimization for Joint Filter-Signal Design in Signal-Dependent STAP
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Relaxed Biquadratic Optimization for Joint Filter-Signal Design in Signal-Dependent STAP

  • Author(s): O'Rourke, Sean M
  • Setlur, Pawan
  • Rangaswamy, Muralidhar
  • Swindlehurst, A Lee
  • et al.
Abstract

We investigate an alternative solution method to the joint signal-beamformer optimization problem considered by Setlur and Rangaswamy[1]. First, we directly demonstrate that the problem, which minimizes the received noise, interference, and clutter power under a minimum variance distortionless response (MVDR) constraint, is generally non-convex and provide concrete insight into the nature of the nonconvexity. Second, we employ the theory of biquadratic optimization and semidefinite relaxations to produce a relaxed version of the problem, which we show to be convex. The optimality conditions of this relaxed problem are examined and a variety of potential solutions are found, both analytically and numerically.

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