Experimental and model investigation on radar classification capability
نویسندگان
چکیده
The capability of multifrequency polarimetric synthetic aperture radar (SAR) to discriminate among nine vegetation classes is shown using both experimental data and model simulations. The experimental data were collected by the multifrequency polarimetric AIRSAR at the Dutch Flevoland site and the Italian Montespertoli site. Simulations are carried out using an electromagnetic model, developed at Tor Vergata University, Rome, Italy, which computes microwave vegetation scattering. The classes have been defined on the basis of geometrical differences among vegetation species, leading to different polarimetric signatures. It is demonstrated that, for each class, there are some combinations of frequencies and polarizations producing a significant separability. On the basis of this background, a simple, hierarchical parallelepiped algorithm is proposed.
منابع مشابه
Palarimetric Synthetic Aperture Radar Image Classification using Bag of Visual Words Algorithm
Land cover is defined as the physical material of the surface of the earth, including different vegetation covers, bare soil, water surface, various urban areas, etc. Land cover and its changes are very important and influential on the Earth and life of living organisms, especially human beings. Land cover change monitoring is important for protecting the ecosystem, forests, farmland, open spac...
متن کاملImproving Radar Absorbing Capability of Polystyrene Nanocomposites: Preparation and Investigation of Microwave Absorbing Properties
Microwave absorbing materials are usually designed to solve protection against electromagnetic interference in wireless communication systems and high frequency circuit mechanisms. In this research polystyrene (PS) nanocomposites containing various nano-fillers were successfully synthesized. The novelty of this work is comparing of three various nanostructures: non-metallic conductive graphene ...
متن کاملGeneral Linear Chirplet Transform and Radar Target Classification
In this paper, we design an attractivealgorithm aiming to classify moving targets includinghuman, animal, vehicle and drone, at groundsurveillance radar systems. The non-stationary reflectedsignal of the targets is represented with a novelmathematical framework based on behavior of thesignal components in reality. We further propose usingthe generalized linear chirp transform for the analysisst...
متن کاملAn Experimental Investigation of the Effects of Canard Position on the Aerodynamic Forces of a Fighter Type Configuration Model
An extensive experimental investigation is conducted to study the effect of canard position relative to the fuselage reference line on the aerodynamic forces of a fighter type configuration model. Aerodynamic forces at different flight conditions are measured in a subsonic wind tunnel. The wing and the canard have triquetrous shapes. Experiments are conducted at Reynolds number of 342209 and at...
متن کاملClassification of polarimetric radar images based on SVM and BGSA
Classification of land cover is one of the most important applications of radar polarimetry images. The purpose of image classification is to classify image pixels into different classes based on vector properties of the extractor. Radar imaging systems provide useful information about ground cover by using a wide range of electromagnetic waves to image the Earthchr('39')s surface. The purpose ...
متن کاملذخیره در منابع من
با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید
برای دانلود متن کامل این مقاله و بیش از 32 میلیون مقاله دیگر ابتدا ثبت نام کنید
ثبت ناماگر عضو سایت هستید لطفا وارد حساب کاربری خود شوید
ورودعنوان ژورنال:
- IEEE Trans. Geoscience and Remote Sensing
دوره 37 شماره
صفحات -
تاریخ انتشار 1999