Geometry and Motion Based Positioning Algorithms for Mobile Tracking in NLOS Environments

This paper presents positioning algorithms for cellular network-based mobile tracking in severe non-line-of-sight (NLOS) propagation scenarios. The aim of the algorithms is to enhance positional accuracy of network-based positioning systems when the GPS receiver does not perform well due to the hostile environment. Two positioning methods with NLOS mitigation are proposed. Constrained optimization is utilized to minimize the cost function which takes account of the NLOS error. Mobile velocity and heading angle information is exploited to greatly enhance position accuracy. It is observed through simulation that the proposed methods significantly outperform other cellular network based positioning algorithms. Further, the exact expressions of the CRLB are derived when the distance measurement error is the sum of an exponential and a Gaussian variable.