LocHunt - Angle of Arrival Based Location Estimation in Harsh Multipath Environments.
IEEE Global Communications Conference(2018)
摘要
The next generation of cellular networks promises to be the platform for ubiquitous, precise, and accurate location-awareness. Although positioning using radio-frequency waves has many advantages in terms of cost and performance, propagation phenomena such as multipath propagation and shadowing can immensely deteriorate this performance leading to incorrect estimation of a user's location. This paper introduces LocHunt, an algorithm that addresses such a problem. Concretely, at each time-instance, angle-of-arrivals (AoAs) of multipath waves from several anchors are estimated and all the candidate locations of the user are derived. Repeating this operation for a span of time, the algorithm exploits the heuristics that those candidate locations obtained from non-line-of-sight (NLoS) paths exhibit large spatial variations, whereas the true location of the user is manifested as a denser cluster. Subsequently, the peak of the underlying empirical probability density function corresponds to an estimate of the user's location, which can be found by the mean-shift algorithm followed by the connected-components algorithm. The proposed data-driven approach is compared to the state-of-the-art, showing improved localization accuracy with up to one order of magnitude reduction in computational complexity. Channel state information (CSI), similar to that exposed by 802.11n MIMO-OFDM systems, is used for testing the algorithms and is generated by a modified Winner 2 (WIM2) channel simulator.
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关键词
arrival based location estimation,harsh multipath environments,cellular networks,radio-frequency waves,propagation phenomena,multipath propagation,LocHunt,time-instance,angle-of-arrivals,multipath waves,nonline-of-sight paths,mean-shift algorithm,connected-components algorithm,probability density function,location-awareness,MIMO-OFDM systems
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