TY - CHAP
T1 - Approach with nonuniform linear arrays
AU - Benesty, Jacob
AU - Cohen, Israel
AU - Chen, Jingdong
N1 - Publisher Copyright:
© Springer Nature Switzerland AG 2019.
PY - 2019
Y1 - 2019
N2 - Until now, we have dealt with ULAs but another straightforward geometry extension is the nonuniform linear array (NULA), which is the focus of this chapter. First, we show how from two virtual ULAs we can construct a physical NULA whose associated steering vector is the Kronecker product of the steering vectors associated with the virtual arrays. Then, we explain how Kronecker product beamforming is performed. We give the most important performance measures in this context. Finally, we show how to derive some interesting optimal beamformers.
AB - Until now, we have dealt with ULAs but another straightforward geometry extension is the nonuniform linear array (NULA), which is the focus of this chapter. First, we show how from two virtual ULAs we can construct a physical NULA whose associated steering vector is the Kronecker product of the steering vectors associated with the virtual arrays. Then, we explain how Kronecker product beamforming is performed. We give the most important performance measures in this context. Finally, we show how to derive some interesting optimal beamformers.
UR - http://www.scopus.com/inward/record.url?scp=85101066301&partnerID=8YFLogxK
U2 - 10.1007/978-3-030-15600-8_5
DO - 10.1007/978-3-030-15600-8_5
M3 - 章节
AN - SCOPUS:85101066301
T3 - Springer Topics in Signal Processing
SP - 113
EP - 145
BT - Springer Topics in Signal Processing
PB - Springer Science and Business Media B.V.
ER -