DocumentCode :
2742338
Title :
Detection with target-incurring orthogonal subspace interference
Author :
Wang, Pu ; Fang, Jun ; Li, Hongbin
Author_Institution :
ECE Dept., Stevens Inst. of Technol., Hoboken, NJ, USA
fYear :
2012
fDate :
17-20 June 2012
Firstpage :
405
Lastpage :
408
Abstract :
In this paper, we consider the detection of a deterministic signal with an unknown scaling amplitude in the presence of a colored noise, when there is a covariance mismatch between the null and alternative hypotheses. Specifically, we consider a scenario where the target incurs an additional subspace interference that is orthogonal to the target steering vector and only present under the alternative hypothesis. To address this problem, we apply the generalized likelihood ratio test (GLRT) principle which results in a detector involving the following steps: the observation is first projected into the interference subspace. Then, the energy of the projected signal (residue) is computed. If the residual energy is small, the GLRT reduces to the standard matched filter (MF) which ignores the subspace interference; otherwise, a modified test statistic is employed for additional interference cancellation. Simulation results are presented to demonstrate the effectiveness of the proposed detector.
Keywords :
matched filters; object detection; radiofrequency interference; signal detection; GLRT principle; colored noise; covariance mismatch; deterministic signal detection; generalized likelihood ratio test; matched filter; orthogonal subspace interference; projected signal energy computation; scaling amplitude; target steering vector; test statistic; Cost function; Covariance matrix; Detectors; Interference; Maximum likelihood estimation; Noise; Vectors; Hypothesis test; adaptive detection; generalized likelihood ratio test; subspace interference;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Sensor Array and Multichannel Signal Processing Workshop (SAM), 2012 IEEE 7th
Conference_Location :
Hoboken, NJ
ISSN :
1551-2282
Print_ISBN :
978-1-4673-1070-3
Type :
conf
DOI :
10.1109/SAM.2012.6250523
Filename :
6250523
Link To Document :
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