Co-frequency interference suppression of airborne VDB receiver based on blind signal separation
-
摘要: 针对民航飞机利用陆基增强系统(GBAS)进行精密进近着陆过程中,GBAS机载甚高频数据广播(VDB)接收机所受到的同频干扰问题,提出采用盲信号分离算法,对VDB接收机所接收到的期望信号与同频干扰信号进行分离,并通过识别解码数据中的机场标识(ID),得到所需期望信号,从而抑制同频干扰信号. 分析并仿真了基于快速固定点(Fast ICA)算法、自然梯度算法和等变自适应分离(EASI)算法,对VDB接收机接收到的混合信号进行分离的机理和同频干扰抑制的实现. 仿真结果表明,这三种算法均能有效分离期望信号与同频干扰信号,进而进行同频干扰抑制,并通过比较三种算法的收敛速度、串音误差和误码率,得出 Fast ICA算法更适合用于VDB信号的同频干扰抑制.Abstract: Aiming at the problem of co-frequency interference of ground-based augmentation systems (GBAS) airborne VHF Data Broadcasting (VDB) receiver in the process of precise approach and landing for civil aviation aircraft using GBAS, a blind signal separation algorithm is proposed to separate the desired signal from the same frequency interference signal received by VDB receiver. The desired signal is obtained by identifying the airport ID in the decoded data, so as to suppress the same frequency interference signal. Based on fast independent component analysis (Fast ICA) algorithm, natural gradient algorithm and equivariant adaptive separation via independence (EASI) algorithm, the mechanism of separating mixed signals received by VDB receivers and the realization of co-channel interference suppression are analyzed and simulated. The simulation results show that the three algorithms can effectively separate the desired signal from the same frequency interference signal, and then suppress the same frequency interference. It is concluded that fast ICA algorithm is more suitable for the same-frequency interference suppression of VDB signals by comparing the convergence speed, crosstalk error and bit error rate of the three algorithms.
-
Key words:
- VDB /
- GBAS /
- co-frequency interference suppression /
- crosstalk error /
- bit error rate
-
[1] KOSTANIC I, MIKHAEL W. Rejection of the co-channel interference using non-coherent independent component analysis based receiver［C］／／Symposium on Circuits and Systems.2002.DOI: 10.1109／MWSCAS.2002.1186938. [2] KOSTANIC I, MIKHAEL W. Blind source separation technique for reduction of co-channel interference［J］. Electronics Letters, 2002, 38(20):1210-1211.DOI: 10.1049／el:20020817. [3] 张光宇, 陈红, 蔡晓霞. 基于Robust ICA的数字调制混合信号盲分离算法［J］. 计算机应用, 2015,35(8):2129-2132. [4] 柴晓冬, 尧辉明, 柴靓. 采用基于独立分量分析的盲信号分离方法分离出FSK信号中的干扰信号［J］. 中国铁道科学, 2009, 30(4):96-101. [5] WU R B, SHI Q Y, HUANG J Y, et al. A novel method of interference suppression for civil aviation air-ground communication based on blind signal extraction［C］// 2007 AsiaPacific Conference on Communications,2007. DOI: 10.1109／APCC.2007. 4433508. [6] TU S L, CHEN S H, ZHENG H, et al. Particle filtering based single-channel blind separation of co-frequency MPSK signals［C］／／2007 International Symposium on Intelligent Signal Processing and Communication Systems, 2008.DOI: 10.1109／ISPACS.2007.4445954. [7] RTCA. RTCA DO-253C Minimum operational performance standards for GPS local area augmentation system airborne equipment ［S］. 2008. [8] RTCA. RTCA DO-246D GNSS-based precision approach Local Area Augmentation System (LAAS) signal-in-space Interface Control Document (ICD) ［S］. 2008. [9] 颜可壹, 吕泽均, 时宏伟. 一种改进的Fast ICA ADS-B 1090ES信号分离技术［J］. 计算机与现代化, 2014(11):31-34,39. [10] 孙守宇, 郑君里, 吴德伟. 基于自然梯度算法的盲信源分离研究［J］. 空军工程大学学报(自然科学版), 2003, 4(3):50-54. [11] AMARI S HUN-ICHI. Natural gradient learning for over-and under-complete bases in ICA［J］. Neural Computation,1999,11(8):1875-1883.DOI: 10.1162／089976699300015990. [12] 余华, 吴文全. 盲源信号分离EASI算法研究与改进［J］. 计算技术与自动化, 2009, 28(4):76-79. [13] 李宗, 冯志鹏, 褚福磊. 基于改进的串音误差的盲分离评价指标［J］. 振动与冲击, 2012,31(18):83-88. -
点击查看大图
计量
- 文章访问数: 393
- HTML全文浏览量: 54
- PDF下载量: 76
- 被引次数: 0
下载:
