A blind signal separation method for single-channel electromagnetic surveillance system
A blind signal separation method for single-channel electromagnetic surveillance system
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DOI：
10.1080/00207217.2014.984643
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发表时间：
2014-11
影响因子：
1.3
通讯作者：
Lihui Pang;Zhilong Qi;Shuai Li;B. Tang
中科院分区：
文献类型：
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作者：
Lihui Pang;Zhilong Qi;Shuai Li;B. Tang
在动态嵌入(DE)框架下，利用快速独立分量分析(FastICA)对单通道电磁监视系统中同时接收的多系统频率重叠信号提出了一种盲信号分离方法。首先，从SC记录的一系列延迟向量中构造合适的DE矩阵。详细介绍了嵌入矩阵的滞后时间和嵌入矩阵的维度设置原则。然后，通过FastICA算法对嵌入矩阵进行分解，计算出多个独立分量(ICs)，并将其作为原始信号的一个方便的扩展基础。然后，这些IC被投射回测量空间。之后，根据它们的独立性和功率密度谱对这些投影IC进行分类，并用于恢复感兴趣的源。对该方法的性能进行了数值仿真，验证了该算法的有效性。
In this paper, a blind signal separation (BSS) methodology for simultaneously received multisystem frequency-overlapped signals in a single-channel (SC) electromagnetic surveillance system is proposed using fast independent component analysis (FastICA) in a dynamical embedding (DE) framework. Firstly, an appropriate DE matrix is constructed out of a series of delay vectors from the SC recording. The lag-time and the dimensional of embedding matrix setting principal are introduced in details. Next, multiple independent components (ICs) are calculated by decomposing the embedding matrix through FastICA algorithm, and ICs can be regarded as a convenient expansion basis of the original signals. Then, these ICs are projected back into the measurement space. After that, these projected ICs are classified and used for recovering the sources of interest based on their independent nature and their power density spectrum. Numerical simulation results obtained in evaluating the proposed methodology’s performance confirmed the effectiveness of the proposed algorithm.