Efficient feature extraction of cycle spectrum and weak communication signal detection

Cyclic spectrum analysis is often used for weak signal detection, but due to the high computational complexity, the associated methods are often limited in engineering use. Hence, in this work, the characteristics of cyclic spectrum are studied, and an efficient weak communication signal detection method is proposed thereupon. By studying the cyclic spectrum of the communication signal, an analytical scheme determining the cyclic spectrum line of the communication signal, i.e. Binary Phase Shift Keying (BPSK) modulated signal, is proposed. In order to improve the detection efficiency, a sparse vector is used to express the characteristics of the cyclic spectrum line, and a detection mechanism is established accordingly. Monte Carlo simulation results show that the proposed method achieves higher detection accuracy without inducing more computation complexity compared to the peering cyclic spectrum detection techniques.