Likelihood method for BPSK and unbalanced QPSK modulation classification
K. C. Ho, Liang Hong · Proceedings of SPIE, the International Society for Optical Engineering/Proceedings of SPIE · 2001
Automatic classification of the digital modulation type of a signal is a branch of non-cooperative communication techniques, which has found many applications in electronics warfare, surveillance and threat analysis. We propose in this paper a classifier based on the likelihood method to distinguish BPSK signal and unbalanced QPSK signal embedded in additive white Gaussian noise (AWGN). Unbalanced QPSK signal occurs when the in-phase and quadrature components of a QPSK signal have different power. The proposed classifier first calculates the log-likelihood functions of BPSK and UQPSK signals using AWGN model and IID data sequence. The ratio of the two log-likelihood functions is dependent on the unbalanced factor. When the unbalanced factor is not known to a receiver, it will be replaced by the maximum likelihood estimation, yielding the generalized likelihood ratio test to classify the two modulation types. The proposed classifier performs better than the classifier without taking into account the unbalanced factor when the SNR and the unbalanced factor are high. At low SNR, the performance of the proposed classifier is comparable to the one without considering the unbalanced factor.