Gaussian message-based cooperative localization on factor graph in wireless sensor networks

Location information has become a critical requirement for many applications in wireless sensor networks. Conventional localization requires dense anchors with known positions or high transmit power in sparse networks to reach successful localization, which is not suitable for low-cost and low-power sensors. Cooperative localization is a promising solution for wireless sensors´ localization, in which the agents needing to be located cooperate with neighboring nodes by exchanging messages and perform measurements with them. In this paper, a distributed cooperative localization algorithm on factor graph is proposed to locate the sensors. Resorting to the linearization method to tackle the nonlinearity in range measurement, Gaussian parametric messages are obtained with closed forms using the sum-product algorithm on factor graph, which leads to low computational complexity and low communication overhead. Numerical simulations are performed to evaluate the proposed algorithm, which shows superior performance to the particle-based SPAWN estimator.