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

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.

[img]
Preview
 PDF (Clemente-etal-Robust-principle-component-analysis-for-micro-doppler)
Clemente_etal_Robust_principle_component_analysis_for_micro_doppler.pdf
Preprint
Download (181kB)| Preview

    Abstract

    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.

    Creators(s): Clemente, C. ORCID logoORCID: https://orcid.org/0000-0002-6665-693X, Miller, A.W. and Soraghan, J.J. ORCID logoORCID: https://orcid.org/0000-0003-4418-7391;
    Item type:Conference or Workshop Item(Paper)
    ID code:51885
    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:09 Feb 2020 03:30
    Related URLs:
    URI:https://strathprints.strath.ac.uk/id/eprint/51885
    Export data:
    CORE (COnnecting REpositories)