Detection and Estimation in Sensor Arrays Using
Detection and Estimation in Sensor Arrays Using
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发表时间：
1991
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通讯作者：
M. Viberg;B. Ottersten;T. Kailath
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作者：
M. Viberg;B. Ottersten;T. Kailath
本文解决了影响传感器阵列的窄带发射器信号的信号参数估计问题。提出了一种多维估计程序，适用于任意阵列结构和信号相关性。该方法基于最近引入的加权子空间拟合（WSF）标准，并且包括用于检测源数量和估计信号参数的方案。建议使用高斯-牛顿型算法来最小化 WSF 准则。基于WSF成本函数的渐近分布，还制定了一种新的检测方案。证明了检测算法对于任意信号相关性（包括相干性）的强一致性。将 WSF 检测方法与最近提出的信息论方法进行比较，发现它为高信号相关场景提供了显着的改进。进行了仿真，将所提出的 WSF 技术与确定性最大似然 (ML) 方法进行了比较。发现 WSF 方案仅受到估计精度的限制，而不受初始化或检测的限制。对于 ML 方法来说，情况似乎并非如此。
This paper addresses the problem of signal param- eter estimation of narrow-band emitter signals impinging on an array of sensors. A multidimensional estimation procedure is proposed, which applies to arbitrary array structures and sig- nal correlation. The method is based on the recently introduced weighted subspace fitting (WSF) criterion, and includes schemes for both detecting the number of sources and estimating the signal parameters. A Gauss-Newton type algorithm is sug- gested for minimizing the WSF criterion. A new detection scheme is also formulated based on the asymptotic distribution of the WSF cost function. Strong consistency of the detection algorithm is proved for arbitrary signal correlation, including coherence. The WSF detection method is compared to a re- cently proposed information theoretic approach, and found to provide a significant improvement for high signal correlation scenarios. Simulations are carried out comparing the proposed WSF technique to the deterministic maximum likelihood (ML) method. The WSF scheme is found to be limited only by the estimation accuracy and not by the initialization or detection. This does not appear to be true for the ML method.