Enhanced capon beamformer using regularized covariance matching
2013 (English)In: 2013 5th IEEE International Workshop on Computational Advances in Multi-Sensor Adaptive Processing (CAMSAP), IEEE conference proceedings, 2013, 97-100 p.Conference paper (Refereed)
The Capon method is a powerful nonparametric approach in array processing based on the sample covariance matrix. For small sample sets, however, its performance is degraded. In this paper we formulate a regularized covariance matching framework based on the nuclear norm for enhancing the Capon method. An approximate iterative solution is developed and tested using simulated data. Appropriate regularization parameter values are also inferred from the data, drawing upon the cross-validation approach. The results show significantly improved spatial spectral and signal waveform estimates.
Place, publisher, year, edition, pages
IEEE conference proceedings, 2013. 97-100 p.
IdentifiersURN: urn:nbn:se:kth:diva-138852DOI: 10.1109/CAMSAP.2013.6714016ISI: 000349915100025ScopusID: 2-s2.0-84894181961ISBN: 978-1-4673-3146-3OAI: oai:DiVA.org:kth-138852DiVA: diva2:681856
2013 5th IEEE International Workshop on Computational Advances in Multi-Sensor Adaptive Processing (CAMSAP), 15-18 December 2013 in Saint Martin, French West Indies, France
FunderSwedish Research Council, 621-2011-5847EU, European Research Council, 228044
QC 201401272013-12-202013-12-202015-12-07Bibliographically approved