TY - JOUR
T1 - Robust Direction-Finding Method for Sensor Gain and Phase Uncertainties in Non-uniform Environment
AU - Yang, Long
AU - Yang, Yixin
AU - Liao, Guisheng
AU - Wang, Yong
N1 - Publisher Copyright:
© 2019, Springer Science+Business Media, LLC, part of Springer Nature.
PY - 2020/4/1
Y1 - 2020/4/1
N2 - A direction-of-arrival (DOA) estimation algorithm, which is robust to sensor gain and phase uncertainties for completely uncalibrated arrays in a non-uniform noise environment, is proposed in this study. As a result of the sensor gain uncertainties or the shielding effects for some baffled arrays, the noise power may vary with sensors. Therefore, a non-uniform noise model is considered. A cost function established by the orthogonality of subspaces is accumulated along several rough space intervals surrounding the real angles of sources. After analyzing the influences of rough space intervals, an iterative refinement operation is carried out to improve the estimation performance of the DOA and sensor gain and phase responses. The Cramér–Rao bounds of the DOA and sensor gain and phase in the non-uniform noise model are derived. Simulations and experimental results show the superiority of the proposed method.
AB - A direction-of-arrival (DOA) estimation algorithm, which is robust to sensor gain and phase uncertainties for completely uncalibrated arrays in a non-uniform noise environment, is proposed in this study. As a result of the sensor gain uncertainties or the shielding effects for some baffled arrays, the noise power may vary with sensors. Therefore, a non-uniform noise model is considered. A cost function established by the orthogonality of subspaces is accumulated along several rough space intervals surrounding the real angles of sources. After analyzing the influences of rough space intervals, an iterative refinement operation is carried out to improve the estimation performance of the DOA and sensor gain and phase responses. The Cramér–Rao bounds of the DOA and sensor gain and phase in the non-uniform noise model are derived. Simulations and experimental results show the superiority of the proposed method.
KW - Robust DOA estimation
KW - Self-calibration
KW - Sensor gain and phase uncertainties
KW - Uncalibrated arrays
UR - http://www.scopus.com/inward/record.url?scp=85070958421&partnerID=8YFLogxK
U2 - 10.1007/s00034-019-01237-4
DO - 10.1007/s00034-019-01237-4
M3 - 文章
AN - SCOPUS:85070958421
SN - 0278-081X
VL - 39
SP - 1943
EP - 1964
JO - Circuits, Systems, and Signal Processing
JF - Circuits, Systems, and Signal Processing
IS - 4
ER -