TY - GEN
T1 - Source number detection with nested arrays and ULAs using jackknifing
AU - Han, Keyong
AU - Nehorai, Arye
PY - 2013
Y1 - 2013
N2 - We consider the problem of source number detection based on uniform linear arrays (ULAs) and the recently proposed nested arrays. A ULA with N sensors can detect at most N - 1 sources, whereas a nested array provides O(N2) degrees of freedom with O(N) sensors, enabling us to detect K sources with N<K sensors. In order to make full use of the available limited valuable data, we propose a novel strategy, which is inspired by the jackknifing resampling method. Exploiting numerous iterations of subsets of the whole data set, this strategy helps the existing detection methods achieve great improvements. Numerical simulations demonstrate the advantage of our strategy, both for ULAs and nested arrays.
AB - We consider the problem of source number detection based on uniform linear arrays (ULAs) and the recently proposed nested arrays. A ULA with N sensors can detect at most N - 1 sources, whereas a nested array provides O(N2) degrees of freedom with O(N) sensors, enabling us to detect K sources with N<K sensors. In order to make full use of the available limited valuable data, we propose a novel strategy, which is inspired by the jackknifing resampling method. Exploiting numerous iterations of subsets of the whole data set, this strategy helps the existing detection methods achieve great improvements. Numerical simulations demonstrate the advantage of our strategy, both for ULAs and nested arrays.
KW - jackknifing
KW - nested array
KW - Source number detection
KW - uniform linear array
UR - http://www.scopus.com/inward/record.url?scp=84894209362&partnerID=8YFLogxK
U2 - 10.1109/CAMSAP.2013.6714006
DO - 10.1109/CAMSAP.2013.6714006
M3 - Conference contribution
AN - SCOPUS:84894209362
SN - 9781467331463
T3 - 2013 5th IEEE International Workshop on Computational Advances in Multi-Sensor Adaptive Processing, CAMSAP 2013
SP - 57
EP - 60
BT - 2013 5th IEEE International Workshop on Computational Advances in Multi-Sensor Adaptive Processing, CAMSAP 2013
Y2 - 15 December 2013 through 18 December 2013
ER -