TY - GEN
T1 - Computationally efficient method for estimation of the number of signals in multipath environment
AU - Xin, Jingmin
AU - Ohashi, Yoji
AU - Sano, Akira
PY - 2005
Y1 - 2005
N2 - This paper proposes a nonparametric detection method for the coherent narrowband signals impinging on a uniform linear array (ULA). By exploiting the array geometry and its shift invariance property, the coherency of incident signal is decorrelated through subarray averaging, and the number of incident signals is equal to the rank of a matrix formed from the cross-correlations between some sensor data, where the effect of additive noise is also eliminated. Then a new criterion is formulated in the terms of the row elements of the QR upper-triangular factor of the cross product of formed correlation matrix, and the number of signals is determined as the value for which this QR-based criterion is maximized. The proposed method has remarkable insensitivity to the correlation of incident signals and flexibility to the spatially correlated noise. Simulation results show that the proposed method is superior in detecting closely-spaced signals with small number of snapshots and at low signal-to-noise ratio (SNR).
AB - This paper proposes a nonparametric detection method for the coherent narrowband signals impinging on a uniform linear array (ULA). By exploiting the array geometry and its shift invariance property, the coherency of incident signal is decorrelated through subarray averaging, and the number of incident signals is equal to the rank of a matrix formed from the cross-correlations between some sensor data, where the effect of additive noise is also eliminated. Then a new criterion is formulated in the terms of the row elements of the QR upper-triangular factor of the cross product of formed correlation matrix, and the number of signals is determined as the value for which this QR-based criterion is maximized. The proposed method has remarkable insensitivity to the correlation of incident signals and flexibility to the spatially correlated noise. Simulation results show that the proposed method is superior in detecting closely-spaced signals with small number of snapshots and at low signal-to-noise ratio (SNR).
UR - https://www.scopus.com/pages/publications/33947187621
M3 - 会议稿件
AN - SCOPUS:33947187621
SN - 0780394046
SN - 9780780394049
T3 - IEEE Workshop on Statistical Signal Processing Proceedings
SP - 609
EP - 614
BT - 2005 IEEE/SP 13th Workshop on Statistical Signal Processing - Book of Abstracts
T2 - 2005 IEEE/SP 13th Workshop on Statistical Signal Processing
Y2 - 17 July 2005 through 20 July 2005
ER -