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A closed-form distributed source localisation method using TDOA and GROA

机译:使用TDOA和GROA的封闭式分布式源定位方法

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摘要

This paper proposes a closed-form distributed passive source localisation method using time difference of arrival (TDOA) and gain ratios of arrival (GROA) measurements. After removing the unknown parameters in TDOA equations by using GROA measurements, the proposed method applies two-step weighted least-square (LS) minimisations. First, the TDOA and GROA equations are transformed into a set of pseudo-linear equations by introducing additional parameters, and a weighted LS estimation is used to obtain a rough estimate; secondl, this method exploits additional parameters to refine the estimate through another weighted LS estimation. The application of weighting matrix leads to an approximate maximum likelihood estimator and produces a substantial improvement in source localisation accuracy. Both the theoretical analysis and simulation results indicate that the proposed method can achieve the Cramer-Rao Lower Bound at a moderate noise level and outperform the existing methods in terms of localisation accuracy.
机译:本文提出了一种基于到达时间差(TDOA)和到达增益比(GROA)测量的闭式分布式无源源定位方法。在使用GROA测量结果删除TDOA方程中的未知参数之后,该方法应用了两步加权最小二乘(LS)最小化。首先,通过引入附加参数,将TDOA和GROA方程转换为一组伪线性方程,然后使用加权LS估计获得粗略估计。其次,该方法利用其他参数通过另一个加权LS估计来完善估计。加权矩阵的应用导致一个近似的最大似然估计器,并在源定位精度上产生了实质性的改善。理论分析和仿真结果均表明,该方法可以在中等噪声水平下实现Cramer-Rao下界,并且在定位精度方面优于现有方法。

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