Possible improvements of synthetic aperture radar (SAR) using fuzzy logic

Remote sensing and especially synthetic aperture radar (SAR) are efficient tools for environmental protection. This paper gives first a brief overview about applications and basic principles of SAR. The second part of the paper describes uncertainties and ambiguities inherent in the SAR system. Concepts using fuzzy logic that are able to handle this vagueness are proposed. In image analysis the greatest advantage appears within multisensor applications. The fuzzy system considers not only the information of the various remotely sensed data but also takes their uncertainties into account. Besides their usefulness in image analysis, fuzzy systems are suitable to create a user friendly interface and an adaptive control for future remote sensing systems. The last part of the paper presents a new approach to adaptively classify SAR images. It consist of a fuzzy comparison of distributions (FCOD) and the fuzzy learning vector quantizer (FLVQ). This system performs a first step towards an improved SAR system.

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