Real-time passive source localization: A practical linear-correction least-squares approach
Real-time passive source localization: A practical linear-correction least-squares approach
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DOI：
10.1109/89.966097
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发表时间：
2001-11-01
期刊：
影响因子：
--
通讯作者：
Mersereau, RM
中科院分区：
文献类型：
--
作者：
Huang, YT;Benesty, J;Mersereau, RM
针对加性测量误差模型下的源定位问题，提出了一种线性校正最小二乘估计方法。该方法，这可以很容易地实现在一个实时系统中具有中等的计算复杂度，产生一个有效的源位置估计，而无需假设噪声分布的先验知识。替代现有的估计，包括似然为基础的，球面相交，球面插值，二次校正最小二乘估计，审查和比较其复杂性，估计的一致性和效率对Cramer-Rao下界。数值研究表明，所提出的估计在许多实际情况下表现得更好。
A linear-correction least-squares estimation procedure is proposed for the source localization problem under an additive measurement error model. The method, which can be easily implemented in a real-time system with moderate computational complexity, yields an efficient source location estimator without assuming a priori knowledge of noise distribution. Alternative existing estimators, including likelihood-based, spherical intersection, spherical interpolation, and quadratic-correction least-squares estimators, are reviewed and comparisons of their complexity, estimation consistency and efficiency against the Cramer-Rao lower bound are made. Numerical studies demonstrate that the proposed estimator performs better under many practical situations.