Estimation with Applications to Tracking and Navigation
Estimation with Applications to Tracking and Navigation
Target tracking by time difference of arrival using recursive smoothing
Signal Processing
UWB Location and tracking for wireless embedded networks
Signal Processing - Signal processing in UWB communications
Range-only tracking in multipath environments: an algorithm based on particle filtering
GLOBECOM'09 Proceedings of the 28th IEEE conference on Global telecommunications
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
WASP: A System and Algorithms for Accurate Radio Localization Using Low-Cost Hardware
IEEE Transactions on Systems, Man, and Cybernetics, Part C: Applications and Reviews
Indoor geolocation science and technology
IEEE Communications Magazine
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Tracking systems based on the measurement of time of arrival (TOA) assume that the measured signal travels directly between transmitter and receiver. In complex radio propagation environments this direct path signal is often weak compared to multipath signals and there is a tradeoff in the TOA algorithm between sensitivity to the weak direct path and false detection due to noise, sidelobes, and other artifacts. Conventional TOA algorithms return a single TOA, which can be early due to false detection or late due to an undetected direct path, and these errors degrade tracking performance. In this paper a novel approach to this problem is proposed in which tracking performance is improved using multiple candidate TOA values. In particular a set of TOAs are extracted from the channel impulse response for each received signal and converted to a set of range values. A decision as to which among the set of range values is due to the direct path is deferred to the tracking algorithm, which uses a probabilistic soft-decision approach. Experimental studies conducted using a wireless network demonstrate that the 90% percentile absolute position error is reduced from 3.3m to 1.3m and the relative position error is reduced from 1.3m to 0.5m.