Receiver Design with Reduced DOF in Frequency Domain for Target Detection under Gaussian Clutter

Yang Li, Qian He, Rick S. Blum, Alexander M. Haimovich

Research output: Contribution to journalArticlepeer-review

Abstract

This paper addresses the problem of target detection against a background of Gaussian clutter by using frequency snapshots with reduced degrees of freedom (DOF). We derive the optimal detector and detection performance under the Neyman-Pearson criterion for general frequency snapshot selection with arbitrary DOF. When the clutter statistics are unknown, we use a uniformly random frequency snapshot selection method and show how the DOF employed affects the detection performance. When the clutter return follows a stationary Gaussian distribution with slowly varying power spectral density, the optimal selection is derived. When the clutter is composed of reflected versions of the transmitted waveforms, a greedy-based method for selecting the frequency snapshots is presented. Numerical experiments show that a receiver with reduced DOF can lead to detection performance which is very close to that of the receiver with full DOF.

Original languageEnglish (US)
Article number9437819
Pages (from-to)3315-3324
Number of pages10
JournalIEEE Transactions on Signal Processing
Volume69
DOIs
StatePublished - 2021
Externally publishedYes

All Science Journal Classification (ASJC) codes

  • Signal Processing
  • Electrical and Electronic Engineering

Keywords

  • Neyman-Pearson
  • Reduced DOF
  • clutter
  • target detection

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