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Maximum Likelihood and Signal-Selective TDOA Estimation for Noncircular Signals
Fei Wen and Qun Wan,Qun Wan 한국통신학회 2013 Journal of communications and networks Vol.15 No.3
This paper addresses the issue of time-difference-ofarrival (TDOA) estimation for complex noncircular signals. First,under the wide-sense stationary assumption, we derive the maximum likelihood (ML) estimator and the Cramer-Rao lower bound for Gaussian noncircular signals in Gaussian circular noise. The ML estimator uses the second-order statistics information of a noncircular signal more comprehensively when compared with the cross-correlation (CC) and the conjugate CC estimators. Further,we present a scheme to modify the traditional signal-selective TDOA methods for noncircular signals on the basis of the cyclostationarity of man-made signals. This scheme simultaneously exploits the information contained in both the cyclic cross-correlation (CCC) and the conjugate CCC of a noncircular signal.
Maximum Likelihood and Signal-Selective TDOA Estimation for Noncircular Signals
Wen, Fei,Wan, Qun The Korea Institute of Information and Commucation 2013 Journal of communications and networks Vol.15 No.3
This paper addresses the issue of time-difference-of-arrival (TDOA) estimation for complex noncircular signals. First, under the wide-sense stationary assumption, we derive the maximum likelihood (ML) estimator and the Cramer-Rao lower bound for Gaussian noncircular signals in Gaussian circular noise. The ML estimator uses the second-order statistics information of a noncircular signal more comprehensively when compared with the cross-correlation (CC) and the conjugate CC estimators. Further, we present a scheme to modify the traditional signal-selective TDOA methods for noncircular signals on the basis of the cyclostationarity of man-made signals. This scheme simultaneously exploits the information contained in both the cyclic cross-correlation (CCC) and the conjugate CCC of a noncircular signal.