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Automatic surface targets detection in forward scatter radar

The purpose of this thesis is to apply automatic detection techniques on forward scatter radar for ground targets detection against vegetation clutter background and thermal noise. This thesis presents the FSR automatic detection performance analysis of three signal processing algorithms: coherent, non-coherent and cross-correlation. The concept of a CFAR forward scatter radar detection is presented and includes pre-fixed threshold detection and adaptive threshold detection. The developments of a set of simulation methods for target detection and performance analysis are described in details. In the results, we will compare the probability of detection for both human and vehicle target against a variety of clutter backgrounds - WGN, stationary narrow band clutter, non-stationary narrow band clutter, and real recorded vegetation clutter at a low (VHF and UHF) frequency bands. Finally, the advantages and limitations of detection performance for each signal processing algorithms are described.

Identiferoai:union.ndltd.org:bl.uk/oai:ethos.bl.uk:731942
Date January 2018
CreatorsWei, Wei
PublisherUniversity of Birmingham
Source SetsEthos UK
Detected LanguageEnglish
TypeElectronic Thesis or Dissertation
Sourcehttp://etheses.bham.ac.uk//id/eprint/7965/

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