基于极化敏感阵列的ADS-B交叠信号分离方法研究

洪 云海1, 吴 梦节1, 胡 焱1, 樊 荣2
1、中国民用航空飞行学院航空电子电气学院
2、中国民用航空飞行学院航空电子电气学院;西藏成丰源科技有限公司

摘要


随着低空经济快速发展,无人机、电动垂直起降飞行器等低空飞行器的数量与种类持续增多,航空应答信号所处的电磁环境日趋复杂。这也导致集中在1090±1MHz频段内的ADS-B信号交叠现象愈发频繁,进一步加大了信号分离难度。鉴于此,本文基于极化敏感阵列,提出一种新的ADS-B交叠信号分离方法。该方法首先借助极化敏感阵列参数估计算法,完成交叠信号的极化参数估计。然后,基于估计得到的极化参数设计极化滤波器,依托不同信号源的极化状态差异提取有效信号分量,最终实现ADS-B交叠信号的有效分离。数值仿真实验果验证了所提方法的有效性,证实了所提方法具备在信号源时间、频率、空间三维度同时交叠的分离能力,具备较强的工程实用价值。

关键词


阵列信号处理;极化敏感阵列;ADS-B;极化滤波器;交叠信号分离

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参考


[1]M. Zhou and A. -J. van der Veen. Improved blind separation algorithm for overlapping secondary surveillance radar replies, 2011 4th IEEE International Workshop on Computational Advances in Multi-Sensor Adaptive Processing (CAMSAP), San Juan, PR, USA, 2011, pp. 181-184.

[2]G. Galati, N. Petrochilos, E G. Piracci. Degarbling Mode S replies received in single channel stations with a digital incremental improvement[J]. IET Radar, Sonar & Navigation, vol. 9, no.6, pp. 681-691, 2015.

[3]Y. Sunquan, C. Lihu, L. Songting and L. Lanmin. Separation of Space-based ADS-B Signals with Single Channel for Small Satellite, 2018 IEEE 3rd International Conference on Signal and Image Processing (ICSIP), Shenzhen, China, 2018, pp. 315-321.

[4]李丞,张玉,唐波.基于曼彻斯特编码算法的单通道二次雷达信号重构方法[J].探测与控制学报,第40卷,第3期,pp.66-69,2018.

[5]王文益,邵宇识.基于改进单天线投影算法的广播式自动相关监视信号分离[J].电子与信息学报,第42卷,第11期,pp.2720-2726,2020.

[6]K. Li, J. Kang, H. Ren and Q. Wu. A Reliable Separation Algorithm of ADS-B Signal Based on Time Domain, IEEE Access, vol. 9, pp. 88019-88026, 2021.

[7]N. Petrochilos and A. J. van der Veen. Algorithms to separate overlapping secondary surveillance radar replies, 2004 IEEE International Conference on Acoustics, Speech, and Signal Processing, Montreal, QC, Canada, 2004, pp. 44-49.

[8]M. Galati and E. G. Piracci. Decoding techniques for SSR Mode S signals in high traffic environment, European Radar Conference, Paris, France, 2005, pp. 383-386.

[9]N. Petrochilos, G. Galati, L. Mene and E. Piracci. Separation of multiple secondary surveillance radar sources in a real environment by a novel projection algorithm, Proceedings of the Fifth IEEE International Symposium on Signal Processing and Information Technology, Athens, Greece, 2005, pp. 125-130.

[10]N. Petrochilos, G. Galati and E. Piracci. Projection Techniques for Separation of Multiple Secondary Surveillance Radar Sources in a Real Environment, Fourth IEEE Workshop on Sensor Array and Multichannel Processing, 2006., Waltham, MA, USA, 2006, pp. 344-348.

[11]Petrochilos, G. Galati and E. Piracci. Secondary Surveillance Radar: Sparsity-based sources separation in a real environment, 2008 Tyrrhenian International Workshop on Digital Communications-Enhanced Surveillance of Aircraft and Vehicles, Capri, Italy, 2008, pp. 1-5.

[12]唐波,程水英,张浩.基于多通道阵列处理的二次雷达混扰信号分选[J].电讯技术,第54卷,第5期,pp.534-540,2014.

[13]W. Wang, R. Wu and J. Liang. ADS-B Signal Separation Based On Blind Adaptive Beamforming, IEEE Transactions on Vehicular Technology, vol. 68, no. 7, pp. 6547-6556, July 2019.

[14]张海,陈小龙,张涛等人.基于MUSIC算法的二次雷达应答信号分离方法[J].电子与信息学报,第42卷,第12期,pp.2984-2991,2020.

[15]H. Ma, H. Tao and J. Xie, Mixed Far-Field and Near-Field Source Localization Using a Linear Tripole Array, IEEE Wireless Communications Letters, vol. 9, no. 6, pp. 889-892, June 2020


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