Optimal Array Signal Processing in the Presence of Coherent Wavefronts

Stoica, PetreDepartment of Systems and Control, Uppsala University, Uppsala, Sweden (författare)

NR 20140805
The problem of estimating the parameters of several wavefronts from the measurements of multiple sensors is often referred to as array signal processing. The maximum likelihood (ML) estimator in array signal processing forthe case of non-coherent signals has been studied extensively. The focus here is on the ML estimator for thecase of stochastic coherent signals which arises due to, for example, specular multipath propagation. We showthe very surprising fact that the ML estimates of the signal parameters obtained by ignoring the information thatthe sources are coherent, coincide in large samples with the ML estimates obtained by exploiting the coherentsource information. Thus, the ML signal parameter estimator derived for the non-coherent case (or its large-sample realizations such as MODE os WSF) asymptotically achieves the lowest possible estimation error variance (corresponding to the coherent Cramer-Rao bound)

TEKNIK OCH TEKNOLOGIER Elektroteknik och elektronik Signalbehandling hsv//swe
ENGINEERING AND TECHNOLOGY Electrical Engineering, Electronic Engineering, Information Engineering Signal Processing hsv//eng
Array signal processing
Covariance matrix
Estimation error
Maximum likelihood detection
Maximum likelihood estimation
Parameter estimation
Process control
Sensor arrays
Stochastic processes
Stochastic resonance

Ottersten, Björn,1961-KTH,Signaler, sensorer och system(Swepub:kth)u120hb53 (författare)
Viberg, MatsDepartment of Applied Electronics, Chalmers University of Technology, Gothenburg, Sweden (författare)
Department of Systems and Control, Uppsala University, Uppsala, SwedenSignaler, sensorer och system (creator_code:org_t)

Ingår i:Proceedings IEEE International Conference on Acoustics, Speech, and Signal Processing. ICASSP-96: IEEE, s. 2904-2907

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