TY - JOUR
T1 - A novel method for the detection of the number of signals at low signal-to-noise ratios
AU - Hou, Yun Shan
AU - Huang, Jian Guo
AU - Shi, Wen Tao
PY - 2011/6
Y1 - 2011/6
N2 - The detection of the number of space signals is one of the key issues in array signal processing. In view of the poor performance of traditional detection methods at low signal-to-noise ratios, a new method called Detection Technique based on Approximate Eigenvectors (DTAE) is proposed to improve the detection performance of sensor arrays at low signal-to-noise ratios. In the proposed method the direction of the centroid of the cluster of signals is first estimated by some kind of beamform scanning in the space, next the approximate eigenvectors of the data covariance matrix is calculated according to the centroid estimate, then the array output data are weighted by the approximate eigenvectors, finally the estimate of the number of signals is acquired by some kind of manipulating of the peak-to-average power ratio of the weighted data in frequency domain. Simulations show the proposed method DTAE demonstrates much better performance than Akaike Information Criterion (AIC) and other methods at low signal-to-noise ratios, which is valuable in engineering practice.
AB - The detection of the number of space signals is one of the key issues in array signal processing. In view of the poor performance of traditional detection methods at low signal-to-noise ratios, a new method called Detection Technique based on Approximate Eigenvectors (DTAE) is proposed to improve the detection performance of sensor arrays at low signal-to-noise ratios. In the proposed method the direction of the centroid of the cluster of signals is first estimated by some kind of beamform scanning in the space, next the approximate eigenvectors of the data covariance matrix is calculated according to the centroid estimate, then the array output data are weighted by the approximate eigenvectors, finally the estimate of the number of signals is acquired by some kind of manipulating of the peak-to-average power ratio of the weighted data in frequency domain. Simulations show the proposed method DTAE demonstrates much better performance than Akaike Information Criterion (AIC) and other methods at low signal-to-noise ratios, which is valuable in engineering practice.
KW - Akaike Information Criterion (AIC)
KW - Approximate eigenvectors
KW - Cluster of signals
KW - Detection the number of signals
KW - Peak-to-average power ratio
UR - http://www.scopus.com/inward/record.url?scp=79959874207&partnerID=8YFLogxK
U2 - 10.3724/SP.J.1146.2010.01077
DO - 10.3724/SP.J.1146.2010.01077
M3 - 文章
AN - SCOPUS:79959874207
SN - 1009-5896
VL - 33
SP - 1390
EP - 1394
JO - Dianzi Yu Xinxi Xuebao/Journal of Electronics and Information Technology
JF - Dianzi Yu Xinxi Xuebao/Journal of Electronics and Information Technology
IS - 6
ER -