Distributed fusion for satellite passive localization using convex combination

In this paper, distributed data fusion for satellite passive localization is examined. The traditional single or multiple satellite passive localization systems usually use a fixed localization mode which commonly has poor fault tolerance capability. We investigate a distributed passive localization scheme using angle only measurements from multiple satellites. However, recursive fusion algorithms are subject to different tradeoffs regarding their speed of convergence and convergence accuracy, and the satellite passive localization applications usually suffer large initial error. The convex combination is recently used to combine different adaptive filters to obtain better filtering performance than the original filters. To improve the fusion performance, data fusion algorithm using convex combination is developed based on sigma point Kalman filter (SPKF). Computer simulation experiments are performed to show the effectiveness of the proposed localization scheme and algorithm.