2-D DOA Estimation Based on Sparse Bayesian Learning for L-Shaped Nested Array
Author:
Affiliation:
1. National University of Defense Technology
Publisher
Institute of Electronics, Information and Communications Engineers (IEICE)
Subject
Electrical and Electronic Engineering,Computer Networks and Communications,Software
Link
https://www.jstage.jst.go.jp/article/transcom/E102.B/5/E102.B_2018EBP3232/_pdf
Reference22 articles.
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3. [3] S. Pillai, Y. Bar-Ness, and F. Haber, “A new approach to array geometry for improved spatial spectrum estimation,” Proc. IEEE, vol.73, no.10, pp.1522-1524, 1985. 10.1109/proc.1985.13324
4. [4] S. Pillai and F. Haber, “Statistical analysis of a high resolution spatial spectrum estimator utilizing an augmented covariance matrix,” IEEE Trans. Acoust., Speech, Signal Process., vol.35, no.11, pp.1517-1523, 1987. 10.1109/tassp.1987.1165068
5. [5] P. Pal and P.P. Vaidyanathan, “Nested arrays: A novel approach to array processing with enhanced degrees of freedom,” IEEE Trans. Signal Process., vol.58, no.8, pp.4167-4181, 2010. 10.1109/tsp.2010.2049264
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