On the Satisfaction of Modulus and Ambiguity Function Constraints in Radar Waveform Optimization for Detection

Abstract

We consider the design of radar systems that are capable of using knowledge of their interference environment to dynamically design transmit waveforms that afford optimum signal-to-interference-plus-noise ratio while satisfying modulus and ambiguity function constraints. We begin by establishing the inextricable nature of modulus constraints in the waveform optimization problem. We then extend the state of the art in waveform optimization to accommodate these constraints. This is done by solving a secondary optimization problem using the method of alternating projections. We demonstrate that this approach can be a computationally efficient alternative to dynamic programming methods. We then consider the multiple-target detection problem, which is the basis for introducing ambiguity function constraints into the waveform design process. We formulate the waveform optimization problem for several receiver architectures, and solve these problems using sequential quadratic programming and interior point methods. Finally, we address the need for a more computationally tractable approach by considering a number of suboptimal formulations. This includes a novel formulation based on a parameterization of nonlinear frequency modulation.

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Document Details

Document Type
Technical Report
Publication Date
Jun 01, 2010
Accession Number
ADA531426

Entities

People

  • Lee K. Patton

Organizations

  • Wright State University

Tags

Communities of Interest

  • Energy and Power Technologies
  • Materials and Manufacturing Processes
  • Sensors

DTIC Thesaurus Topics

  • Air Force
  • Algorithms
  • Computer Programming
  • Detection
  • Detectors
  • Doppler Effect
  • Dynamic Programming
  • Frequency
  • Frequency Modulation
  • Frequency Shift
  • Modulation
  • Optimization
  • Radar
  • Scattering
  • Synthetic Aperture Radar
  • Target Detection
  • Waveforms

Fields of Study

  • Engineering

Readers

  • Operations Research
  • Radar Systems Engineering.
  • Radio communications and signal processing.