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|Title:||Multi-sensor tracking of a vehicle on a grid|
|Citation:||Conference record of the Thirty-Eighth Asilomar Conference on Signals, Systems & Computers : November 7-10, 2004, Pacific Grove, California / Michael B. Matthews (ed.), vol. 2, pp. 1402- 1406|
|Publisher:||IEEE Computer Society Press|
|Publisher Place:||Piscataway, NJ USA|
|Conference Name:||Asilomar Conference on Signals, Systems & Computers (38th : 2004 : Pacific Grove, California)|
|Sworder, D.D. ; Boyd, J.E. ; Hutchins, R.G. ; Elliott, R.J.|
|Abstract:||Considerable work has been done on model-based, multi-sensor signal processing algorithms for estimating the location and the motion mode of a mobile vehicle. Hybrid models provide the best framework for fusion of disparate sensor measurements. But abrupt sensor nonlinearities and rigid motion constraints require more detailed analysis. This paper presents a multiple-model estimator that provides high quality location and uncertainty estimates for a vehicle following a mapped road grid. An example illustrates the power of the estimator.|
|Description:||© Copyright 2004 IEEE|
|Appears in Collections:||Mathematical Sciences publications|
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