The Compressed Nested Array for Underdetermined DOA Estimation by Fourth-order Difference Coarrays
Yan Zhou, Yanyan Li, Lin Wang, Cai Wen, Weike Nie
Abstract
In this paper, a new sparse array structure, which further improves the degrees of freedom (DOFs) and enhanced the DOA estimation performance, for the fourth-order cumulant based direction of arrival (DOA) estimation is proposed. The new-formed array is hole-free and can achieve a large consecutive range in its fourth-order difference coarray. By analyzing its second-order sum coarray and fourth-order difference coarray, the closed form expression for the physical sensor locations and the corresponding virtual sensor configurations are derived. Compared with the existing fourth-order based sparse array structures, such as FLNA and SAFOE-NA, when the number of sensors is less than 23, the proposed sparse array can obtain longer consecutive virtual array, leading to more detected sources with a higher accuracy. Numerical simulations are performed to verify the superiorities of the proposed sparse array for fourth-order cumulant based DOA estimation.
BibTeX
@inproceedings{icassp2020_thecompressednes,
title = {The Compressed Nested Array for Underdetermined DOA Estimation by Fourth-order Difference Coarrays},
author = {Yan Zhou and Yanyan Li and Lin Wang and Cai Wen and Weike Nie},
booktitle = {ICASSP 2020},
year = {2020}
}