Single frequency network based mobile tracking in NLOS environments

In single frequency network (SFN) positioning, base station (BS) identification is inevitable and non-line-of-sight (NLOS) propagation is usually dominant especially for indoor scenarios. BS identification and NLOS mitigation are two challenging problems which have significant impact on the SFN positioning performance. In this paper, a mobile tracking scheme is proposed to deal with these challenging issues. Specifically, BS identification is first formulated as a data validation problem. Each time-of-arrival (TOA) measurement is tentatively associated with a specific BS so that a number of TOA–BS relationship sets are produced. The gate technique is adapted to evaluate all the TOA–BS relationship sets and the set with the smallest gate parameter value is selected. This identification technique is suited for both line-of-sight (LOS) and NLOS propagation scenarios. The interacting multiple model (IMM) smoother is then utilized to smooth the identified TOA measurements at each BS to reduce the NLOS errors. In addition, the position determination and BS identification are jointly considered to enhance position estimation accuracy. Simulation results demonstrate that the proposed SFN positioning approach can perform satisfactorily in different propagation scenarios and has better performance than other SFN positioning algorithms.