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

机译:基于匹配滤波器的ADS-B信号的新型纠错算法

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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. (C) 2019 Elsevier B.V. All rights reserved.
机译:本文致力于解决如何在低信噪比(SNR)下提高自动相关监视广播(ADS-B)信号的接收性能的问题,这是卫星的主要挑战之一基于ADS-B的应用程序。由于SNR不足,常规解码算法可能无法正常运行,而基于匹配滤波器的解码方案是一种很有前途的解决方案。但是,在低SNR的情况下,可能会错误地声明位和置信度值。为此,我们提出了一种N个置信度错误校正算法,如果整个消息中的低置信度位总数不超过N,则将激活该算法。通过对置信度标签应用最佳阈值,我们可以实现最大性能改进。此外,本文还提出了一种简化的方法,称为降错纠错算法,具有良好的接收性能和较低的复杂度。进行了蒙特卡洛仿真,以验证理论结果以及不同纠错算法之间的比较。 (C)2019 Elsevier B.V.保留所有权利。

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