Multiple Signal Detection in Correlated Noise Using Cross Correlation

Weak signal detection is widely used in many aspects. However, limited by the signal-to-noise ratio, detection under low signal-to-noise ratio has always been a challenge. The performance of traditional energy detection methods has deteriorated significantly under low signal-to-noise ratio or faced with noise uncertainty. The use of cross correlation methods can effectively improve the detection signal-to-noise ratio but threshold setting is closely related to noise power. To deal with noise uncertainty, in this paper, we propose a new test statistics for cross correlation detection, that is peak-to-average ratio. Firstly through mathematical derivation and simulation peak-to-average is proved to be robust against noise uncertainty. Then we design a detection algorithm for cross-correlation detection in the case of multiple signals, which expands the application scenarios of cross correlation detection. Finally, based on the experimental platform built, the performance of the algorithm is verified by taking the received UAV image transmission signal as an detection target.