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Constrained Optimization Paradigms for Adaptive, Cognitive Radar

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Technical Report,15 Sep 2015,14 Sep 2018

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The Pennsylvania State University University Park United States

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Multiple-Input Multiple-Output MIMO radar system allows each antenna element to transmit a different waveform. This waveform diversity can be exploited to enhance the beampattern design, in particular, effective management of radar radiation power in directions of interest. This work addresses the problem of designing a beampattern for MIMO radar, which in turn is determined by the transmit waveform. While unconstrained design is straightforward, a key open challenge is enforcing the constant modulus constraint on the radar waveform. It is well-known that the problem of minimizing deviation of the designed beampattern vs. an idealized one subject to the constant modulus constraint constitutes a hard non-convex problem. Existing methods that address constant modulus invariably lead to a stiff trade-off between analytical tractability achieved by relaxations and approximations and realistic design that exactly achieves constant modulus but is computationally burdensome. A new approach is proposed in this work, which involves solving a sequence of convex Equality Constrained Quadratic Programs, each of which has a closed form solution and such that constant modulus is achieved at convergence.

Subject Categories:

  • Radio Communications
  • Active and Passive Radar Detection and Equipment

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