caa a22 4500 606205160 CHVBK 20210128101006.0 cr unu---uuuuu 210128e20150901xx s 000 0 eng 10.1007/s00034-015-9987-6 doi (NATIONALLICENCE)springer-10.1007/s00034-015-9987-6 A Novel ESPRIT-Based Algorithm for DOA Estimation with Distributed Subarray Antenna [Elektronische Daten] [Yan Ma, Baixiao Chen, Minglei Yang, Yi Wang] Distributed subarray antennas (DSAs), which are sparse arrays consisting of two or more far separated subarrays, have many advantages over uniform linear array, especially for direction of arrival (DOA) estimation. However, they are subject to manifold ambiguity, which has significant influence on DOA estimation. In order to solve the manifold ambiguity of uncorrelated sources for DSA, a novel method based on estimation of signal parameters via rotational invariance technique by utilizing optimal subarray partition is proposed in this paper. In the proposed method, an optimized reference estimation is obtained by the rotational invariance between the new subarrays with optimal partition of DSA. The high accuracy and unambiguous DOA estimations are then disambiguated easily according to the optimized reference estimation. In this way, the performance of disambiguated DOA estimation can be enhanced in cases of the low signal-to-noise ratio and the large spacing between the subarrays. Moreover, the ambiguity threshold effect of DOA estimation for DSA is analyzed by means of the maximum a posteriori estimator. Computer simulation results show good performance of the proposed method and the effectiveness of the ambiguity threshold for DSA. Springer Science+Business Media New York, 2015 Distributed subarray antenna (DSA) nationallicence Estimation of signal parameters via rotational invariance technique (ESPRIT) nationallicence Optimal subarray partition nationallicence Ambiguity threshold nationallicence Maximum a posteriori (MAP) estimator nationallicence Ma Yan National Laboratory of Radar Signal Processing, Xidian University, 710071, Xi'an, Shaanxi, China aut Chen Baixiao National Laboratory of Radar Signal Processing, Xidian University, 710071, Xi'an, Shaanxi, China aut Yang Minglei National Laboratory of Radar Signal Processing, Xidian University, 710071, Xi'an, Shaanxi, China aut Wang Yi National Laboratory of Radar Signal Processing, Xidian University, 710071, Xi'an, Shaanxi, China aut Circuits, Systems, and Signal Processing Springer US; http://www.springer-ny.com 34/9(2015-09-01), 2951-2972 0278-081X 34:9<2951 2015 34 34 https://doi.org/10.1007/s00034-015-9987-6 text/html Onlinezugriff via DOI BK010053 XK010053 XK010000 Metadata rights reserved Springer special CC-BY-NC licence nationallicence 1 research-article jats NATIONALLICENCE NATIONALLICENCE NL-springer NATIONALLICENCE 856 40 https://doi.org/10.1007/s00034-015-9987-6 text/html Onlinezugriff via DOI NATIONALLICENCE 700 1- Ma Yan National Laboratory of Radar Signal Processing, Xidian University, 710071, Xi'an, Shaanxi, China aut NATIONALLICENCE 700 1- Chen Baixiao National Laboratory of Radar Signal Processing, Xidian University, 710071, Xi'an, Shaanxi, China aut NATIONALLICENCE 700 1- Yang Minglei National Laboratory of Radar Signal Processing, Xidian University, 710071, Xi'an, Shaanxi, China aut NATIONALLICENCE 700 1- Wang Yi National Laboratory of Radar Signal Processing, Xidian University, 710071, Xi'an, Shaanxi, China aut NATIONALLICENCE 773 0- Circuits, Systems, and Signal Processing Springer US; http://www.springer-ny.com 34/9(2015-09-01), 2951-2972 0278-081X 34:9<2951 2015 34 34