NDLI: Sensor fusion for swarms of small unmanned aerial vehicles

Content Provider	IEEE Xplore Digital Library
Author	Denting, R.W. Perlovsky, L.I.
Copyright Year	2005
Description	Author affiliation: Air Force Res. Lab., Hanscom AFB, MA, USA (Denting, R.W.; Perlovsky, L.I.)
Abstract	We consider the problem of automatically developing a 3-dimensional model of the environment based on multiples-dimensional images acquired from differing positions and aspect angles. The problem is complicated by the fact that the sensors are moving, we don't know their precise positions and velocities, and the image fields-of-view may overlap one another in an irregular fashion. This type of problem would be encountered, for example, when attempting to combine information from a swarm of unmanned aerial vehicles to perform automatic target detection, classification, and surveillance. To solve this problem we propose a method whereby a probabilistic model of the preprocessed image data is computed, in which parameters of the model include object locations and classification feature statistics, as well as velocities and positions of the sensors. The parameters are then estimated by maximizing a log-likelihood function which quantitatively measures how well the model fits the data. The crux of the problem is data association, i.e. determining which data samples correspond to which physical objects in the environment. Our approach makes use of a convergent, iterative, system of equations in which data association is performed concurrently with parameter estimation during maximization of the log-likelihood. An advantage of our method is that the computational complexity increases only linearly with the size of the model, and thus the approach is more efficient than the standard approaches.
Starting Page	302
Ending Page	308
File Size	408700
Page Count	7
File Format	PDF
ISBN	0780389166
DOI	10.1109/SIS.2005.1501636
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2005-06-08
Publisher Place	USA
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Image sensors Parameter estimation Surveillance Object detection Sensor fusion Unmanned aerial vehicles Iterative methods Statistics Computational complexity Equations
Content Type	Text
Resource Type	Article

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