Novel error correction algorithms for ADS-B signals with matched filter based decoding

Abstract

Abstract In this paper, we are committed to solving the problem of how to improve the reception performance of automatic dependent surveillance broadcast (ADS-B) signals at the low signal to noise ratio (SNR), which is one of the principal challenges in the satellite-based ADS-B application. Conventional decoding algorithms may not function properly due to the insufficient SNR, whereas the matched filter based decoding scheme is a promising solution. However, in the case of low SNRs, the bit and confidence values could be declared incorrectly. To this end, we propose an N -confidence error correction algorithm that is activated if the total number of low confidence bits over the entire message is no more than N . By applying the optimal threshold for the confidence level labeling, we can achieve the maximum performance improvement. In addition, a simplified method termed the descending error correction algorithm is also presented in this paper, which has an excellent reception performance and a relatively low complexity. Monte Carlo simulations are carried out to validate the theoretical results, as well as the comparison between different error correction algorithms.