This paper considers locating a static source on Earth using the time difference of arrival (TDOA) and frequency difference of arrival (FDOA) measurements obtained by a dual-satellite geolocation system. The TDOA and FDOA from the source are subject to unknown time and frequency offsets because the two satellites are imperfectly time-synchronized or frequency-locked. The satellite locations are not known accurately as well. To make the source position identifiable and mitigate the effect of satellite location errors, calibration stations at known positions are used. Achieving the maximum likelihood (ML) geolocation performance usually requires jointly estimating the source position and extra variables (i.e., time and frequency offsets as well as satellite locations), which is computationally intensive. In this paper, a novel closed-form geolocation algorithm is proposed. It first fuses the TDOA and FDOA measurements from the source and calibration stations to produce a single pair of TDOA and FDOA for source geolocation. This measurement fusion step eliminates the time and frequency offsets while taking into account the presence of satellite location errors. The source position is then found via standard TDOA-FDOA geolocation. The developed algorithm has low complexity and performance analysis shows that it attains the Cramér-Rao lower bound (CRLB) under Gaussian noises and mild conditions. Simulations using a challenging scenario with a short-baseline dual-satellite system verify the theoretical developments and demonstrate the good performance of the proposed algorithm.
2017 20th International Conference on Information Fusion (Fusion), July 2017, doi:10.23919/ICIF.2017.8009716