Cooperative Localization Using Efficient Kalman Filtering for Mobile Wireless Sensor Networks

The authors consider the problem of cooperative localization in mobile Wireless Sensor Networks (WSNs). To be able to continuously localize the mobile network, they propose to exploit the knowledge of the location of the anchor nodes to linearize the nonlinear distance measurements with respect to the location of the unknown nodes. Based on this linearized measurement model, they estimate the location of the unknown nodes using a Kalman Filter (KF) instead of a suboptimal Extended KF (EKF) and try to estimate the corresponding unknown measurement noise covariance matrix using an iterative process.