Adaptive waveform design and sequential hypothesis testing for target recognition with active sensors

Nathan A. Goodman, Phaneendra R. Venkata, Mark A. Neifeld

Research output: Contribution to journalArticle

206 Scopus citations

Abstract

Cognitive radar is a recently proposed approach in which a radar system may adaptively and intelligently interrogate a propagation channel using all available knowledge including previous measurements, task priorities, and external databases. A distinguishing characteristic of cognitive radar is that it operates in a closed loop, which enables constant optimization in response to its changing understanding of the channel. In this paper, we compare two different waveform design techniques for use with active sensors operating in a target recognition application. We also propose the integration of waveform design with a sequential-hypothesis-testing framework that controls when hard decisions may be made with adequate confidence. The result is a system that updates multiple target hypotheses/classes based on measured data, customizes waveforms as the class probabilities change, and draws conclusions when sufficient understanding of the propagation channel is achieved.

Original languageEnglish (US)
Pages (from-to)105-113
Number of pages9
JournalIEEE Journal on Selected Topics in Signal Processing
Volume1
Issue number1
DOIs
StatePublished - Jun 1 2007

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Keywords

  • Cognitive radar
  • Matched illumination
  • Sequential detection

ASJC Scopus subject areas

  • Signal Processing
  • Electrical and Electronic Engineering

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