A Correlation Detection Method of Low SNR Based on Multi-Channelization

Abstract

This letter proposes a correlation detection algorithm based on multi-channelization. The existing method has poor performance for detecting a time-varying signal with a low signal-to-noise ratio(SNR). To overcome this problem, we use the method of correlation summation after multi-channelization. According to the difference between the correlation between signals and noise in the received data, the single-channel data is converted into multi-channel data by a multi-channelization method without changing the signals. Then the noise is filtered by correlation calculation of multi-channel data, which can improve the detection probability of signals under low SNR. Based on the theory of multi-channelization, we propose two different methods to detect signals. To better reflect the performance of the algorithm, we compared several classical signal detection methods, such as energy detection (ED), correlation detection (CD), and cyclic spectrum detection (CSD). Simulation analysis and experimental results show that the multi-channelization correlation detection algorithm has better detection performance when the SNR is low.