基于盲源分离算法的脉冲压缩雷达信号分选

Li Jiang, Lin Li, Guoqing Zhao
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引用次数: 3

摘要

随着脉冲密度的增大,现代电子侦察,特别是脉冲压缩雷达信号的分选变得极为困难。盲源分离(BSS)是一种从混合观测数据中分离信号的新技术。本文提出了各种脉冲压缩雷达信号的瞬时混合模型,包括线性调频、多相编码、移相键控和跳频信号。针对雷达信号,提出了快速独立分量分析(FastICA)和联合对角化BSS算法的结合。采用性能指数(PI)和信噪比(SIR)分析了不同信噪比下的分离性能。实验结果证明了该方法的有效性和正确性。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Pulse-compression radar signal sorting using the blind source separation algrithms
With the increase of pulse density, signal sorting becomes extremely difficult for modern electronic reconnaissance, especially for pulse-compression radar signals. Blind source separation (BSS) is a new developed technology for separating signals from mixed observed data. In this paper, we propose various instantaneous mixing models of pulse-compression radar signals, including linear frequency modulation, polyphase code, phase-shift keying and frequency-hopping signals. The combinations of fast independent component analysis (FastICA) and joint diagonalization BSS algorithms are presented for radar signals. The performance index (PI) and signal-to-interference ratio (SIR) are adopted to analyze the separation performance at different signal-to-noise ratios. The experiment results demonstrate the validity and correctness of the proposed method.
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