A Kalman Filter-Based Approach to Target Detection and Target- Background Separation in Ground Penetrating Radar Data

Abstract

The returns from shallowly buried targets measured using Ground Penetrating Radar (GPR) are typically obscured by a strong background signal comprised of the reflections from the air-soil interface. A Kalman filter-based approach is proposed to estimate this background signal and to separate it from the target return. In the absence of the target the filter operates using a "quiescent state model" in which it computes the background estimate. A statistic based on measurement innovation is applied to detect the target position. Upon detection the state is augmented by a new component which allows for the change of the signal corresponding to the presence of the target return. The augmented state model is used until it is reverted to the quiescent model by another decision.

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Document Details

Document Type
Technical Report
Publication Date
Aug 01, 1999
Accession Number
ADA370784

Entities

People

  • Dragana Carevic

Tags

Communities of Interest

  • Counter IED
  • Human Systems
  • Space

DTIC Thesaurus Topics

  • Abstracts
  • Algorithms
  • Australia
  • Department Of Defense
  • Detection
  • Electrical Engineering
  • Engineering
  • Engineers
  • Ground Penetrating Radar
  • Information Processing
  • Information Science
  • Signal Processing
  • Standards
  • Surveillance
  • Target Detection
  • Two Dimensional
  • Universities

Readers

  • Radar Systems Engineering.
  • Sensor Fusion and Tracking Systems.