A Novel Multi-Criteria Preamble Detection Algorithm for ADS-B Signals

Satellite-based automatic dependent surveillance broadcast (ADS-B) is of great importance in the next generation air traffic management system. However, there are two major challenges: interference and low signal to noise ratio (SNR). The interference can be mitigated by various separation algorithms. In this paper, we are committed to improving the detection performance for the ADS-B signals with downlink format field equal to 17 at low SNRs. At the moment, commercial receivers work well with sufficient SNRs but may not function properly in the case of the low SNRs. To this end, based on the characteristics of the ADS-B signal frame format, we propose a novel multi-criteria preamble detection algorithm. The proposed algorithm is a constant false alarm rate (CFAR) detection algorithm, and the determination of threshold is independent of noise power. We make a detailed theoretical analysis of each criterion, and develop the analytic expression of the detection probability. All the theoretical results are validated by the Monte Carlo simulations. The simulation shows that the proposed algorithm has an excellent probability of detection when the SNR is low, which is suitable for the satellite-based ADS-B application.