Direct Position Estimation Utilizing Non-Line-of-Sight (NLOS) GPS Signals

Yuting Ng, Grace Xingxin Gao

Abstract:	We propose Direct Position Estimation (DPE) utilizing non-line-of-sight (NLOS) GPS signals for urban navigation. In urban environments, buildings reflect GPS signals, leading to reception of NLOS GPS signals. In addition, buildings obstruct GPS signals, resulting in reduced GPS signal availability. We treat NLOS GPS signals as additional line-of-sight (LOS) GPS signals to virtual satellites at mirror-image positions. We calculate these satellite mirror-image positions and velocities using knowledge of building reflection surfaces estimated from available three-dimensional (3D) maps. We then create expected signal receptions to include NLOS GPS signal information at multiple potential navigation candidates. Following that, we use Direct Position Estimation (DPE) to obtain the Maximum Likelihood Estimate (MLE) navigation solution. The MLE navigation solution is the navigation candidate with the expected signal reception that produced the highest overall correlation against the actual received signal. We implemented DPE utilizing NLOS GPS signals on our software platform - PyGNSS. We conducted experiments in front of the 53 m by 40 m wind tunnel located at NASA Ames Research Center in Mountain View, California. The surface of the wind tunnel’s air intake valve is a dense metal mesh of grid size 1.8 cm, a reflector of GPS signals. We demonstrated through our experiment, an improvement in horizontal positioning accuracy by 40 m in comparison to conventional GPS positioning using scalar tracking.
Published in:	Proceedings of the 29th International Technical Meeting of the Satellite Division of The Institute of Navigation (ION GNSS+ 2016) September 12 - 16, 2016 Oregon Convention Center Portland, Oregon
Pages:	1279 - 1284
Cite this article:	Ng, Yuting, Gao, Grace Xingxin, "Direct Position Estimation Utilizing Non-Line-of-Sight (NLOS) GPS Signals," Proceedings of the 29th International Technical Meeting of the Satellite Division of The Institute of Navigation (ION GNSS+ 2016), Portland, Oregon, September 2016, pp. 1279-1284. https://doi.org/10.33012/2016.14855
Full Paper:	ION Members/Non-Members: 1 Download Credit Sign In