Simultaneous Localization, Calibration and Tracking in an Ad Hoc Sensor Network
What	We introduce Simultaneous Localization and Tracking, called SLAT, the problem of tracking a target in a sensor network while simultaneously localizing and calibrating the nodes of the network. Our proposed solution, LaSLAT, is a Bayesian filter providing on-line probabilistic estimates of sensor locations and target tracks. It does not require globally accessible beacon signals or accurate ranging between the nodes. Real hardware experiments are presented for 2D and 3D, indoor and outdoor, and ultrasound and audible ranging-hardware-based deployments. Results demonstrate rapid convergence and high positioning accuracy.
Which	IPSN-06 paper
Why	Localization is not the goal of sensor networks. Use the hardware you have.
Who	Christopher Taylor, Ali Rahimi, Jonathan Bachrach, Howard Shrobe, Anthony Grue
How	Java and MATlab, MIT Cricket Motes, and XSMs
When	Fall 2004-Summer 2005
Where	MIT CSAIL
And	Coordinate Formation in Sensor Networks