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Low-Observable Nonlinear Trajectory Generation for Unmanned Air Vehicles
Abstract This paper explores low observability flig
This paper explores low observability flight path planning of unmanned air vehicles (UAV’s) in the presence of radar detection systems. The probability of detection model of an aircraft near an enemy radar depends on aircraft attitude, range, and configuration. A detection model is coupled with a simplified aircraft dynamics model. The Nonlinear Trajectory Generation (NTG) software package developed at Caltech is used. The NTG algorithm is a gradient descent optimization method that combines three technologies: B–splines, output space collocation and nonlinear optimization tools. Implementations are formulated with temporal constraints that allow periods of high observability interspersed with periods of low observability. Illustrative examples of optimized routes for low observability are presented.
outes for low observability are presented.  +
Authors Kathy Misovec, Tamer Inanc, Jerry Wohletz, Richard Murray  +
ID 2003b  +
Source 2003 Conference on Decision and Control (CDC)  +
Tag miwm03-cdc  +
Title Low-Observable Nonlinear Trajectory Generation for Unmanned Air Vehicles +
Type Conference Paper  +
Categories Papers
Modification date
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15 May 2016 06:18:46  +
URL
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http://www.cds.caltech.edu/~murray/preprints/miwm03-cdc.pdf  +
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Low-Observable Nonlinear Trajectory Generation for Unmanned Air Vehicles + Title
 

 

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