Optimal Detection in the K-Distributed Clutter Environment -- Non-Coherent Radar Processing

Abstract

Non-coherent detection of Gaussian targets (Swerling II targets) in the K-distributed clutter environment is investigated. The optimal detector is derived based on the Neyman-Pearson principle. It is shown to be the well-known square-law detector. Amplitude detector, log detector, and the like are not optimal, and result in some detection loss. Temporally correlated clutter provides a target gain, and improves detection. The higher the temporal correlation, the higher the target gain. Spatially correlated non-Gaussian clutter can also provide a CFAR gain. The autoregressive technique is used to optimally estimate the texture of the clutter. That in turn significanly improves the detection compared to the traditional cell-averaging processing.

Open PDF

Document Details

Document Type
Technical Report
Publication Date
Dec 01, 2012
Accession Number
ADA584850

Entities

People

  • Yuhan Dong

Organizations

  • Defence Science and Technology Group

Tags

Communities of Interest

  • Electronic Warfare
  • Materials and Manufacturing Processes

DTIC Thesaurus Topics

  • Amplitude
  • Clutter
  • Coherent Radar
  • Data Processing
  • Detection
  • Detectors
  • Electrical Engineering
  • Electronic Warfare
  • False Alarms
  • Information Science
  • Mathematical Analysis
  • Probability
  • Radar
  • Radar Signals
  • Sea Clutter
  • Signal Processing
  • Warning Systems

Fields of Study

  • Engineering

Readers

  • Adaptive Control and Estimation with Uncertainty in Dynamic Systems.
  • Radar Systems Engineering.