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Cooperative localization and tracking technique relies on pairwise measurements to jointly estimate the positions and the velocities of multiple nodes in a mobile ad hoc network. The pairwise measurements include the range and the radial velocity between the transmitting and receiving nodes. For a large-scale network, we formulate the state-space models for the subsystems and develop the distributed extended Kalman filters for cooperative localization and tracking. The decentralized approach takes into account the limited resources of node memory, embedded computation, and communication bandwidth. The algorithm works well in a sparsely connected mobile network and can adapt to changes in network connectivity. Numerical results show that the performances of the decentralized cooperative localization and node velocity estimation are close to the posterior Cramér-Rao lower bounds of the centralized approach.
Date of Publication: July 2012