Joint Weak Signal Detection and Carrier Frequency Offset Estimation for Communication in Multistatic Collaborative Passive Radar

Abstract

Communication among stations of a multitstatic collaborative passive radar (MCPR) is the prerequisite for networking detection. To tackle the problems of high missed detection probability and poor carrier frequency synchronization in inter-station communication of an MCPR under a low signal-to-noise ratio (SNR), we propose a virtual array-based method to jointly detect communication signals and estimate their starting position and carrier frequency offset (CFO) at the receiving end. It takes advantage of the a priori information of the training sequence to construct SNR-improved virtual sampled signals. On this basis, a large quantity of virtual array snapshots is constructed from the short training sequence by using the method of combinatorics, which benefits us to use the array signal processing theory in communications and reduces the signal processing cost by sharing the same hardware module with the radar signal processing unit. Moreover, to reduce the computational burden, we introduce the root multiple signal classification (root-MUSIC) algorithm to handle the virtual array snapshots. Numerical analyses conducted on the minimum shift keying (MSK) signals validate the feasibility and effectiveness of the proposed method under low SNR.