Hybrid Positioning with 3GPP-LTE and GPS employing Particle Filters

Abstract

Global navigation satellite systems (GNSSs) can deliver very good position estimates under optimum conditions. How- ever, especially in urban canyons and indoor scenarios with severe multipath propagation and blocking of satellites by buildings the accuracy loss can be very large. Often, po- sitioning with GNSSs is impossible in these scenarios. On the other hand, cellular wireless communication systems such as the third generation partnership project (3GPP) long-term evolution (LTE) provide excellent coverage in urban and most indoor environments. Thus, this paper researches timing based positioning algorithms, in this case time difference of arrival (TDoA), using 3GPP-LTE and GPS measurements. This paper considers a particle filter for 3GPP-LTE TDoA positioning and the fusion of 3GPP-LTE signals with GPS measurements. To obtain better positioning results, a 3GPP-LTE TDoA error model is derived, which splits the TDoA errors in slow varying and fast varying errors. The slow varying error model is included in the prediction model and the fast varying error model in the likelihood function of the particle filter. The last part of this paper, evaluates the positioning performances of the developed particle filter in an indoor scenario. These evaluations show clearly the possibility of using 3GPP-LTE measurements for indoor positioning. Additionally, it shows the advantage of fusing 3GPP-LTE with GPS measurements.