Robust principal component analysis for micro-doppler based automatic target recognition

C. Clemente, A.W. Miller, J.J. Soraghan

Research output: Contribution to conferencePaperpeer-review

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Dealing with real data it is likely that it will exhibit the presence of unexpected observations within the data which can affect the correct reduction of the representative features of a target signature. For the speciffc case of micro-Doppler based classiffcation this problem can appear in the feature selection stage. To address this problem the Robust PCA based on the Minimum Covariance Determinant (MCD) estimator is introduced. The proposed technique showed to improve the overall classiffcation accuracy.
Original languageEnglish
Number of pages6
Publication statusPublished - Oct 2013
Event3rd IMA conference on Mathematics in Defence - Malvern, United Kingdom
Duration: 24 Oct 2013 → …


Conference3rd IMA conference on Mathematics in Defence
Country/TerritoryUnited Kingdom
Period24/10/13 → …


  • micro-doppler
  • automatic target recognition
  • target classification
  • radar detection

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