Adaptive detection of multiple point-like targets with conic acceptance
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Adaptive detection of multiple point-like targets with conic acceptance. / Hao, Chengpeng; Bandiera, Francesco; Yang, Jun; Hou, Chaohuan.
2011 IEEE International Conference on Acoustics, Speech, and Signal Processing, ICASSP 2011 - Proceedings. 2011. s. 2684-2687 5947038 (ICASSP, IEEE International Conference on Acoustics, Speech and Signal Processing - Proceedings).Publikation: Bidrag til bog/antologi/rapport › Konferencebidrag i proceedings › Forskning › fagfællebedømt
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TY - GEN
T1 - Adaptive detection of multiple point-like targets with conic acceptance
AU - Hao, Chengpeng
AU - Bandiera, Francesco
AU - Yang, Jun
AU - Hou, Chaohuan
PY - 2011
Y1 - 2011
N2 - In this paper we consider the problem of detecting multiple point-like targets in the presence of steering vector mismatches and Gaussian disturbance with unknown covariance matrix. To this end, we first model the actual useful signal as a vector belonging to a proper cone whose axis coincides with the whitened direction of the nominal array response. Then we develop two new robust adaptive detectors resorting to the two-step generalized-likelihood ratio test (GLRT) design procedure without assignment of a distinct set of secondary data. Finally, a performance assessment, conducted by Monte Carlo simulation, show that the proposed detectors achieve a visible performance improvement over their natural counterparts.
AB - In this paper we consider the problem of detecting multiple point-like targets in the presence of steering vector mismatches and Gaussian disturbance with unknown covariance matrix. To this end, we first model the actual useful signal as a vector belonging to a proper cone whose axis coincides with the whitened direction of the nominal array response. Then we develop two new robust adaptive detectors resorting to the two-step generalized-likelihood ratio test (GLRT) design procedure without assignment of a distinct set of secondary data. Finally, a performance assessment, conducted by Monte Carlo simulation, show that the proposed detectors achieve a visible performance improvement over their natural counterparts.
KW - Adaptive detection
KW - constant false alarm rate (CFAR)
KW - generalized likelihood ratio test (GLRT)
UR - http://www.scopus.com/inward/record.url?scp=80051647846&partnerID=8YFLogxK
U2 - 10.1109/ICASSP.2011.5947038
DO - 10.1109/ICASSP.2011.5947038
M3 - Article in proceedings
AN - SCOPUS:80051647846
SN - 9781457705397
T3 - ICASSP, IEEE International Conference on Acoustics, Speech and Signal Processing - Proceedings
SP - 2684
EP - 2687
BT - 2011 IEEE International Conference on Acoustics, Speech, and Signal Processing, ICASSP 2011 - Proceedings
T2 - 36th IEEE International Conference on Acoustics, Speech, and Signal Processing, ICASSP 2011
Y2 - 22 May 2011 through 27 May 2011
ER -
ID: 362748291