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Article Dans Une Revue Radio Science Année : 2008

A duct mapping method using least squares support vector machines

Résumé

This paper introduces a “refractivity from clutter” (RFC) approach with an inversion method based on a pregenerated database. The RFC method exploits the information contained in the radar sea clutter return to estimate the refractive index profile. Whereas initial efforts are based on algorithms giving a good accuracy involving high computational needs, the present method is based on a learning machine algorithm in order to obtain a real-time system. This paper shows the feasibility of a RFC technique based on the least squares support vector machine inversion method by comparing it to a genetic algorithm on simulated and noise-free data, at 1 and 5 GHz. These data are simulated in the presence of ideal trilinear surface-based ducts. The learning machine is based on a pregenerated database computed using Latin hypercube sampling to improve the efficiency of the learning. The results show that little accuracy is lost compared to a genetic algorithm approach. The computational time of a genetic algorithm is very high, whereas the learning machine approach is real time. The advantage of a real-time RFC system is that it could work on several azimuths in near real time.
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Dates et versions

hal-01174769 , version 1 (19-10-2015)

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Rémi Douvenot, Vincent Fabbro, Peter Gerstoft, Christophe Bourlier, Joseph Saillard. A duct mapping method using least squares support vector machines. Radio Science, 2008, 43, pp.RS6005. ⟨10.1029/2008RS003842⟩. ⟨hal-01174769⟩
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