A stochastic geometric approach to sensor array processing

dc.contributor.author	Vo, Ba-Ngu
dc.contributor.author	Vo, Ba Tuong
dc.date.accessioned	2017-01-30T13:17:09Z
dc.date.available	2017-01-30T13:17:09Z
dc.date.created	2015-10-29T04:09:47Z
dc.date.issued	2014
dc.identifier.citation	Vo, B. and Vo, B. 2014. A stochastic geometric approach to sensor array processing, in Proceedings of the 2014 IEEE Workshop on Statistical Signal Processing (SSP), Jun 29-Jul 2 2014, pp. 236-239. Gold Coast, Qld, IEEE.
dc.identifier.uri	http://hdl.handle.net/20.500.11937/30044
dc.identifier.doi	10.1109/SSP.2014.6884619
dc.description.abstract	A new unified mathematical framework for sensor array processing is proposed. The proposed framework combines Bayesian estimation with stochastic geometry to accommodate prior information, uncertainty in array parameters, and unknown and stochastically time-varying number of nonstationary sources. A system model for a common signal setting is constructed to demonstrate the proposed framework.
dc.publisher	IEEE Computer Society
dc.title	A stochastic geometric approach to sensor array processing
dc.type	Conference Paper
dcterms.source.startPage	236
dcterms.source.endPage	239
dcterms.source.title	IEEE Workshop on Statistical Signal Processing Proceedings
dcterms.source.series	IEEE Workshop on Statistical Signal Processing Proceedings
dcterms.source.isbn	9781479949755
curtin.department	Department of Electrical and Computer Engineering
curtin.accessStatus	Fulltext not available