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International Journal of Antennas and Propagation
Volume 2019, Article ID 7419156, 9 pages
https://doi.org/10.1155/2019/7419156
Research Article

DOA Estimation Method in Multipath Environment for Passive Bistatic Radar

1National Key Laboratory of Science and Technology on ATR, National University of Defense Technology, Changsha 410073, China
2College of Information Engineering, Shenzhen University, Shenzhen 518060, China

Correspondence should be addressed to Panhe Hu; moc.361@9002ehnapuh

Received 24 January 2019; Revised 6 May 2019; Accepted 13 May 2019; Published 20 June 2019

Academic Editor: Ana Alejos

Copyright © 2019 Panhe Hu et al. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

Abstract

Direction-of-arrival (DOA) estimation in multipath environment is an important issue for passive bistatic radar (PBR) using frequency agile phased array VHF radar as illuminator of opportunity. Under such scenario, the main focus of this paper is to cope with the closely spaced uncorrelated and coherent signals in low signal-to-noise ratio and limited snapshots. Making full use of the characteristics of moduli of eigenvalues, the DOAs of the uncorrelated signals are firstly estimated. Afterwards, their contributions are eliminated by means of spatial difference technique. Finally, in order to improve resolution and accuracy DOA estimation of remaining coherent signals while avoiding the cross-terms effect, a new beamforming solution based iterative adaptive approach (IAA) is proposed to deal with a reconstructed covariance matrix. The proposed method combines the advantages of both spatial difference method and the IAA algorithm while avoiding their shortcomings. Simulation results validate its effectiveness; meanwhile, the good performances of the proposed method in terms of resolution probability, detection probability, and estimation accuracy are demonstrated by comparison with the existing methods.