NDLI: Performance analysis of direction-of-arrival estimation using the decentralized root-MUSIC

Content Provider	IEEE Xplore Digital Library
Author	Suleiman, W. Pesavento, M. Zoubir, A.
Copyright Year	2015
Description	Author affiliation: Tech. Univ. Darmstadt, Darmstadt, Germany (Pesavento, M.) \|\| Inst. fur Nachrichtentechnik, Tech. Univ. Darmstadt, Darmstadt, Germany (Suleiman, W.) \|\| Darmstadt Univ. of Technol., Darmstadt, Germany (Zoubir, A.)
Abstract	In this paper, we propose a decentralized implementation of the root-MUSIC algorithm over a network of nodes based on averaging consensus (AC) protocol. In our implementation, the nodes compute a sufficient statistic of their measurements, namely the signal subspace, in a decentralized fashion and sent it to a fusion center (FC), which performs the direction-of-arrival (DOA) estimation using the root-MUSIC algorithm. The proposed decentralized implementation reduces the required communication with the FC and the computational cost at the FC. Moreover, we derive an analytical expression for the asymptotic behaviour of the mean square error (MSE) for DOA estimation using our proposed algorithm, which we refer to as the decentralized root-MUSIC algorithm. Based on our performance analysis we show that the decentralized root-MUSIC algorithm is not a consistent estimator of the DOAs. Nevertheless, we demonstrate by simulations that the decentralized root-MUSIC algorithm achieves the Cramér Rao bound (CRB) for small number of snapshots and low SNRs.
Starting Page	329
Ending Page	332
File Size	433366
Page Count	4
File Format	PDF
e-ISBN	9781479919635
DOI	10.1109/CAMSAP.2015.7383803
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2015-12-13
Publisher Place	Mexico
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Algorithm design and analysis Direction-of-arrival estimation Protocols Estimation mean square error Sensors Performance analysis Covariance matrices decentralized root-MUSIC
Content Type	Text
Resource Type	Article

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