AIS多小区同频信号实时盲分离的FPGA设计
发布时间：2019-06-26 14:25
【摘要】：针对船舶自动识别系统(Automatic Identification System,AIS)中相邻多个小区的同频信号相互干扰、无法解调的问题,该文采用多天线接收混合信号,通过在FPGA上设计独立成分分析(Independent Component Analysis,ICA)算法来对混合信号进行实时盲分离.为满足实时性,文中用符号函数代替双曲正切函数对样点数据作非线性映射,简化迭代运算;并将样点数据分块存储,用于并行计算.同时实现了高精度特征分解(Eigen Value Decomposition,EVD),用于对混合数据进行白化.最后将设计的FPGA系统在Xilinx Isim中仿真,结果表明,主频20MHz时,系统在850μs内完成了从4路512点AIS混合信号中分离出了三路源信号.本文的设计也可应用于雷达、声纳等可能存在同频干扰的实时信号处理系统.
[Abstract]:In order to solve the problem that the same frequency signals of adjacent cells in ship automatic recognition system (Automatic Identification System,AIS) interfere with each other and can not be Demodulated, this paper adopts multi-antenna to receive mixed signals, and designs an independent component analysis (Independent Component Analysis,ICA algorithm on FPGA to carry out real-time blind separation of mixed signals. In order to meet the real-time performance, the symbolic function is used instead of the hyperbolic tangent function to make nonlinear mapping of the sample point data to simplify the iterative operation, and the sample point data are stored in blocks for parallel computing. At the same time, the high precision feature decomposition (Eigen Value Decomposition,EVD is realized, which is used to whiten the mixed data. Finally, the designed FPGA system is simulated in Xilinx Isim. The results show that the system separates three source signals from 4 512point AIS mixed signals in 850 渭 s when the main frequency 20MHz is used. The design of this paper can also be applied to real-time signal processing systems with radar, Sonar and other possible co-frequency interference.
【作者单位】： 南开大学电子信息与光学工程学院;天津市光电传感器与传感网络技术重点实验室;
【基金】：国家自然科学基金(No.61571244,No.61501262) 天津市科技计划项目(No.16YFZCSF00540)
【分类号】：TN791;U675.7
本文编号：2506255
[Abstract]:In order to solve the problem that the same frequency signals of adjacent cells in ship automatic recognition system (Automatic Identification System,AIS) interfere with each other and can not be Demodulated, this paper adopts multi-antenna to receive mixed signals, and designs an independent component analysis (Independent Component Analysis,ICA algorithm on FPGA to carry out real-time blind separation of mixed signals. In order to meet the real-time performance, the symbolic function is used instead of the hyperbolic tangent function to make nonlinear mapping of the sample point data to simplify the iterative operation, and the sample point data are stored in blocks for parallel computing. At the same time, the high precision feature decomposition (Eigen Value Decomposition,EVD is realized, which is used to whiten the mixed data. Finally, the designed FPGA system is simulated in Xilinx Isim. The results show that the system separates three source signals from 4 512point AIS mixed signals in 850 渭 s when the main frequency 20MHz is used. The design of this paper can also be applied to real-time signal processing systems with radar, Sonar and other possible co-frequency interference.
【作者单位】： 南开大学电子信息与光学工程学院;天津市光电传感器与传感网络技术重点实验室;
【基金】：国家自然科学基金(No.61571244,No.61501262) 天津市科技计划项目(No.16YFZCSF00540)
【分类号】：TN791;U675.7
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