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A Factor-Graph-Based TOA Location Estimator
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DOI：10.1109/TWC.2012.040412.110520.png)
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Abstract
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A high-accuracy and low-complexity TOA-based algorithm is proposed to estimate mobile station (MS) location. First, a factor-graph-based distributive approach is used, which can work in a multi-state system as well. By effectively exchanging the available soft-information or stochastic property of the variables, this distributive approach can perform almost as well as conventional algorithm while requiring much less computational workload. Second, data screening method was applied to reduce complexity and data discrimination to improve accuracy. Simulation results demonstrate that this approach can maintain good accuracy while achieving low complexity. Since this approach is accurate and easy to implement, it will better satisfy the demands of real applications.
Keywords:
TOA
location tracking
Kalman filter
extended Kalman filter
factor graph
soft-information
sum-product algorithm
data screening
data discrimination
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