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Efficient direction of arrival estimation based on sparse covariance fitting criterion with modeling mismatch

Cai, S; Wang, G; Zhang, J; Wong, K-K; Zhu, H; (2017) Efficient direction of arrival estimation based on sparse covariance fitting criterion with modeling mismatch. Signal Processing , 137 pp. 264-273. 10.1016/j.sigpro.2017.02.011. Green open access

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Abstract

This paper studies direction of arrival (DoA) estimation with an antenna array using sparse signal reconstruction (SSR). Among the existing SSR methods, the sparse covariance fitting based algorithms, which can estimate source power and noise variance naturally, are most promising. Nevertheless, they are either on-grid model based methods whose performance are sensitive to off-grid DoAs or gridless methods which are computationally demanding. In this paper, we propose an off-grid DoA estimation algorithm based on the sparse covariance fitting criterion. We first consider a scenario in which the number of snapshots is larger than the array size. An algorithm is proposed by applying an off-grid model, which takes into account the deviations between the discretized sampling grid and the true DoAs, to the sparse covariance fitting criterion. It estimates the on-grid parameters and the deviations of off-grid DoAs separately and thus is computationally efficient to implement. Then in the case where the number of snapshots is smaller than the array size, we propose to execute the DoA estimation algorithm iteratively under the stochastic maximum likelihood (SML) criterion. The estimation accuracy and computational efficiency of the proposed algorithms are demonstrated by computer simulations.

Type: Article
Title: Efficient direction of arrival estimation based on sparse covariance fitting criterion with modeling mismatch
Open access status: An open access version is available from UCL Discovery
DOI: 10.1016/j.sigpro.2017.02.011
Publisher version: http://doi.org/10.1016/j.sigpro.2017.02.011
Language: English
Additional information: This version is the author accepted manuscript. For information on re-use, please refer to the publisher’s terms and conditions.
Keywords: DoA estimationSparse parameter estimationOff-grid modelSparse covariance fitting
UCL classification: UCL > Provost and Vice Provost Offices
UCL > Provost and Vice Provost Offices > UCL BEAMS
UCL > Provost and Vice Provost Offices > UCL BEAMS > Faculty of Engineering Science
UCL > Provost and Vice Provost Offices > UCL BEAMS > Faculty of Engineering Science > Dept of Electronic and Electrical Eng
URI: https://discovery.ucl.ac.uk/id/eprint/1549996
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