Cooperative estimation using multiple mobile sensor nodes communicating over a lossy network is considered. A new method, termed predicted information, is developed from a separable formulation of the extended information filter. Two variations of the predicted information method are presented, which trade between accuracy and computational complexity. The first variation estimates the information matrix updates directly from estimates of the cooperating sensor node states. The second variation uses a piecewise constant approximation to predict the informationmatrixupdates.Thepredictedinformation methodisshowntogivetheexactsolutionforlinearsystems when the measurement dynamics are constant or known by all sensor nodes. The predicted information method is evaluated with a cooperative geolocation problem with two uninhabited aerial vehicles using gimballing camera sensors. Flight-test data and high-fidelity hardware-in-the-loop simulations are used to compare the predicted information method with three benchmark methods from the literature for tracking both stationary and maneuvering targets and for single extended losses and random dropouts.
['William Whitacre', 'Mark E. Campbell']
Cooperative Estimation Using Mobile Sensor Nodes in the Presence of Communication Loss