Estimation with Applications to Tracking and Navigation
Estimation with Applications to Tracking and Navigation
Joint Particle Filter and UKF Position Tracking Under Strong NLOS Situation
SSP '07 Proceedings of the 2007 IEEE/SP 14th Workshop on Statistical Signal Processing
A tutorial on particle filters for online nonlinear/non-GaussianBayesian tracking
IEEE Transactions on Signal Processing
Indoor geolocation in the absence of direct path
IEEE Wireless Communications
Super-resolution TOA estimation with diversity for indoor geolocation
IEEE Transactions on Wireless Communications
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In complex propagation environments with multipath reflections determining the time-of-arrival (TOA) of the line-of-sight (LoS) signal, which is required for localization, is challenging. As a result the localization accuracy of TOA-based systems degrade in such environments. We are pursuing a novel approach where the TOA algorithm returns not one but multiple candidate TOA values as this list is more likely to contain the LoS TOA value and the localization algorithm uses all of these to form a more reliable estimate of the node location. In this paper we present a new algorithm for localization and tracking based on multiple candidate TOA values from each anchor. We show that this is similar to the well-known data association problem in target tracking and exploit this similarity to propose a particle filter based algorithm that has linear computational complexity in the number of anchors. The performance of the algorithm is validated using simulated data.