Mobile position location using factor graphs

Making use of the time-of-arrival measurements and their stochastic properties, we propose a low-complexity high-accuracy algorithm to estimate the location of a target mobile station (MS). Under a factor graph framework, in the proposed algorithm, soft-information is efficiently exchanged among local processing units to iteratively purify the estimate of the MS location. Numerical results show that the proposed algorithm not only enjoys advantages of low complexity, suitable for integrated-circuit implementation, but it is also able to achieve performance very close to the optimum achievable bound, the maximum-likelihood bound.