Analog Neural Network Approach for Source Localization Using Time-of-Arrival Measurements

被引：0

作者：

Leung, Chi-Sing ^{[1
]}

So, H. C. ^{[1
]}

Chan, Frankie K. W. ^{[1
]}

Constantinides, A. G. ^{[2
]}

机构：

[1] City Univ Hong Kong, Dept Elect Engn, Hong Kong, Hong Kong, Peoples R China

[2] Imperial Coll, London, England

来源：

NEURAL INFORMATION PROCESSING, ICONIP 2012, PT II | 2012年 / 7664卷

关键词：

Analog network; source localization; time-of-arrival;

D O I：

暂无

中图分类号：

TP18 [人工智能理论];

学科分类号：

081104 ; 0812 ; 0835 ; 1405 ;

摘要：

Source localization can be achieved by making use of the time-of-arrival (TOA) measurements, but it is not a trivial task because the TOAs have nonlinear relationships with the source coordinates. This paper exploits a neural network technique, namely, Lagrange programming neural networks, for TOA-based localization. We also investigate the local stability of our formulation. Simulation results demonstrate that the performance of the proposed location estimator approaches the optimality benchmark of Cramer-Rao lower bound.

引用

页码：234 / 241

页数：8

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