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首页> 外文期刊>IEEE Transactions on Aerospace and Electronic Systems >Source separation and tracking for time-varying systems
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Source separation and tracking for time-varying systems

机译：时变系统的源分离和跟踪

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Many situations arise when it is desired to recover from a noisy mixture of data both an estimate of a propagating source signal as well as its angular position. Accordingly, the problem of source separation and tracking for time-varying systems of moving sources is studied. Using techniques borrowed from independent component analysis (ICA) and numerical linear algebra, a processing solution is formulated. The ULV decomposition (ULVD), a member of the complete orthogonal decompositions (CODs) family is used to normalize and decorrelate the data. Since the ULVD is known to stably update and downdate with time-varying data, this step is named ULVD adaptive whitening. The ICA-based EASI (equivariant adaptive separation based on independence) algorithm is adapted to provide not only separated sources but direction-of-arrival (DOA) estimates. Developed improvements to this technique are an adaptive filter method for estimating the mixing matrix from the newly estimated signals as well as a simple cross-over detection scheme. Finally, the developed solutions are tested in simulation examples using meaningful performance measures.
机译：当需要从嘈杂的数据混合中恢复传播的源信号的估计值及其角度位置时，会出现许多情况。因此，研究了移动源的时变系统的源分离和跟踪问题。使用从独立成分分析（ICA）和数值线性代数中借鉴的技术，制定了处理解决方案。 ULV分解（ULVD）是完全正交分解（COD）族的成员，用于规范化和解相关数据。由于已知ULVD使用时变数据稳定地更新和降级，因此此步骤称为ULVD自适应白化。基于ICA的EASI（基于独立性的等距自适应分离）算法不仅可以提供分离的信号源，还可以提供到达方向（DOA）估计。对这种技术的改进发展是一种自适应滤波器方法，用于根据新估计的信号估计混合矩阵以及一种简单的交叉检测方案。最后，使用有意义的性能指标在模拟示例中测试开发的解决方案。

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