Loading...

A robust CFAR detection with ML estimation

Pourmottaghi, A ; Sharif University of Technology | 2008

786 Viewed
  1. Type of Document: Article
  2. DOI: 10.1109/RADAR.2008.4720885
  3. Publisher: 2008
  4. Abstract:
  5. Any clutter edge in the reference window of a radar CFAR detection, produces an error in the clutter power estimation which reduces the detectability of the cell under test (CUT). In processors such as OS-CFAR, the designers have attempted to improve the detection performance, nevertheless, none of these processors applies an intelligent method of clutter edge recognition and destroyer data elimination. Therefore any of these processors are effective in some especial cases of nonhomogeneous environment, but are deficient in other cases. In this paper an intelligent method is proposed for clutter edge recognition. This method determines the borders in which the clutter statistics are changing and then sets the decision threshold according to the appropriate clutter statistics. It is shown that the new processor improves the radar detection intensively in non-homogeneous environment. © 2008 IEEE
  6. Keywords:
  7. Clutter (information theory) ; Edge detection ; Error detection ; Estimation ; Signal noise measurement ; Cell under tests ; Constant false alarm rate (CFAR) ; CFAR detections ; Clutter edge ; Clutter statistics ; Decision thresholds ; Detectability ; Detection performance ; Intelligent methods ; ML estimation ; Non-homogeneous ; OS-CFAR ; Power estimations ; Radar detections ; Tracking radar
  8. Source: 2008 IEEE Radar Conference, RADAR 2008, Rome, 26 May 2008 through 30 May 2008 ; December , 2008 ; 9781424415397 (ISBN)
  9. URL: https://ieeexplore.ieee.org/document/4720885