Rigid Body Based Location Technology for Ad Hoc Sensor Networks

As an optimization problem, precision location requires sufficient constraints to warrant unique location estimation. The algorithm to determine the constraint sufficiency is the locatability algorithm. For the classic triangulation in two dimensions, locatability algorithm examines if a sensor node...

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Hauptverfasser: Feng Niu, Kyperountas, S., Qicai Shi, Jian Huang
Format: Tagungsbericht
Sprache:eng
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Zusammenfassung:As an optimization problem, precision location requires sufficient constraints to warrant unique location estimation. The algorithm to determine the constraint sufficiency is the locatability algorithm. For the classic triangulation in two dimensions, locatability algorithm examines if a sensor node has at least 3 non-collinear reference node (RN) neighbors. This condition is often not met in most ad hoc sensor networks due to the low RN density. Progressive location was developed to turn a located sensor node into an induced RN which in turn is used to locate other sensor nodes. But even after applying progressive location, a lot of sensor nodes are still left un-locatable. A holistic approach, the rigid body (RB) based location technology, is proposed to group together sensors and RNs in a sensor network to form globally rigid bodies (GRBs) and cooperatively estimate sensor locations. The key differentiator of the technology is its locatability algorithm, a bottom-up procedure to identify GRBs in an anchor-free network and to determine the locatabilities of GRBs by grounding the network. The algorithm consists of four processes (node categorization, bilateration extension, trilateration extension, and tri-connectivity test) and locatability rules. It is shown that a bilateratively rigid sub-network is a strongly rigid graph and requires only the tri-connectivity to become globally rigid. Rules are provided for the locatability determination of rigid bodies and their associated sensor nodes. Simulation results show that the RB-based location algorithm locates drastically more sensor nodes than triangulation and progressive location algorithms especially when RNs are sparse
DOI:10.1109/ICNSC.2006.1673272