CramÉr-rao Bound for DOA Estimators under the Partial Relaxation Framework
2019 (English)In: 2019 IEEE INTERNATIONAL CONFERENCE ON ACOUSTICS, SPEECH AND SIGNAL PROCESSING (ICASSP), IEEE , 2019, p. 4469-4473Conference paper, Published paper (Refereed)
Abstract [en]
In this paper, the Cramer-Rao Bound for the Direction-of-Arrival parameter under the partial relaxation framework is derived. We introduce a non-redundant parameterization of the signal model corresponding to the partial relaxation framework, in which the array structure in part of the steering matrix is neglected while the rank of the relaxed steering matrix is maintained. We prove that the stochastic Cramer-Rao Bound for the Direction-of-Arrival parameter under the partial relaxation signal model is lower-bounded by that of the conventional stochastic Cramer-Rao Bound. Furthermore, we prove that the partial relaxation estimator for the Weighted Subspace Fitting criterion asymptotically achieves the conventional Cramer-Rao Bound in the case of uncorrelated source signals.
Place, publisher, year, edition, pages
IEEE , 2019. p. 4469-4473
Series
International Conference on Acoustics Speech and Signal Processing ICASSP, ISSN 1520-6149
Keywords [en]
DOA Estimation, Cramer-Rao Bound, Partial Relaxation, Non-redundant Parameterization, Mean-squared Error
National Category
Signal Processing
Identifiers
URN: urn:nbn:se:bth-18735DOI: 10.1109/ICASSP.2019.8682980ISI: 000482554004141ISBN: 978-1-4799-8131-1 (print)OAI: oai:DiVA.org:bth-18735DiVA, id: diva2:1358166
Conference
44th IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP), MAY 12-17, 2019, Brighton, ENGLAND
2019-10-072019-10-072019-10-17Bibliographically approved