Clemente, C. and Miller, A.W. and Soraghan, J.J. (2013) Robust principal component analysis for micro-doppler based automatic target recognition. In: 3rd IMA conference on Mathematics in Defence, 2013-10-24.
Clemente_etal_Robust_principle_component_analysis_for_micro_doppler.pdf - Preprint
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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.
|Item type:||Conference or Workshop Item (Paper)|
|Keywords:||micro-doppler, automatic target recognition, target classification, radar detection, Electrical engineering. Electronics Nuclear engineering, Electrical and Electronic Engineering|
|Subjects:||Technology > Electrical engineering. Electronics Nuclear engineering|
|Department:||Faculty of Engineering > Electronic and Electrical Engineering
Technology and Innovation Centre > Sensors and Asset Management
|Depositing user:||Pure Administrator|
|Date Deposited:||24 Feb 2015 09:28|
|Last modified:||19 Jan 2017 20:32|