DocumentCode
1790776
Title
A stochastic geometric approach to sensor array processing
Author
Ba Ngu Vo ; Ba Tuong Vo
Author_Institution
Dept. of Electr. & Comput. Eng., Curtin Univ., Bentley, WA, Australia
fYear
2014
fDate
June 29 2014-July 2 2014
Firstpage
236
Lastpage
239
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.
Keywords
array signal processing; geometry; stochastic processes; Bayesian estimation; array parameters; common signal setting; nonstationary sources; prior information; sensor array processing; stochastic geometric approach; stochastically time-varying number; system model; unified mathematical framework; Arrays; Bayes methods; Geometry; Kernel; Signal processing; Stochastic processes; Uncertainty; Bayesian estimation; random sets; sensor array processing;
fLanguage
English
Publisher
ieee
Conference_Titel
Statistical Signal Processing (SSP), 2014 IEEE Workshop on
Conference_Location
Gold Coast, VIC
Type
conf
DOI
10.1109/SSP.2014.6884619
Filename
6884619
Link To Document