Memorias de investigación
Research Publications in journals:
Generalisation of inverse synthetic aperture radar autofocusing methods based on the minimisation of the Rényi entropy
Year:2010

Research Areas
  • Electronic technology and of the communications

Information
Abstract
In order to obtain focused inverse synthetic aperture radar (ISAR) images, an accurate translational motion compensation is required. The phase adjustment step corresponds to fine compensation and must be properly designed. The authors introduce the Re¿nyi entropy for autofocusing ISAR images. The Re¿ nyi entropy of order a is a generalisation of the standard Shannon entropy. When a tends to be the unity, the Re¿nyi entropy tends to be the Shannon entropy. Here, we demonstrate that minimising the Re¿nyi entropy for a ¿ 2 is equivalent to maximising the contrast for ISAR autofocusing. Furthermore, it is also shown that maximising the peak value is equivalent to minimising the Re¿nyi entropy for a tending to infinity. On the other hand, the authors propose to minimise the Re¿nyi entropy with a ¿ 0.5 to reconstruct an accurate ISAR image. Simulated data have been used to verify that, in terms of mean squared error, the proposed method with a ¿ 0.5 outperforms other autofocusing algorithms such as the method based on contrast maximisation or the one based on the minimisation of the standard Shannon entropy. The method has also been applied to real data.
International
Si
JCR
Si
Title
IET Radar Sonar and Navigation
ISBN
1751-8784
Impact factor JCR
0,981
Impact info
Volume
4
10.1049/iet-rsn.2009.0027
Journal number
4
From page
586
To page
594
Month
AGOSTO
Ranking
Participants
  • Autor: M Datcu Remote Sensign Technology Institute
  • Autor: José María Muñoz Ferreras Universidad de Alcalá de Henares
  • Autor: Felix Perez Martinez UPM

Research Group, Departaments and Institutes related
  • Creador: Grupo de Investigación: Microondas y Radar
  • Departamento: Señales, Sistemas y Radiocomunicaciones