Artículos

 

An Adaptive Beamformer Algorithm–Based BMEVA Method for Enhanced Radar Imaging

 

Método BMEVA para formación mejorada de imágenes de radar basado en el algoritmo formador de haz adaptivo

 

René F. Vázquez Bautista¹, Luis J. Morales Mendoza¹, Andrés Blanco Ortega², and Francisco Beltrán Carbajal³

 

¹ Universidad Veracruzana, FIEC, Poza Rica, Veracruz, Mexico. E–mail: favazquez@uv.mx, javmorales@uv.mx

² CENIDET Ingeniería Mecatrónica, Cuernavaca, Morelos, Mexico. E–mail: andres.blanco@cenidet.edu.mx

³ Universidad Politécnica de la Zona Metropolitana de Guadalajara, Tlajomulco de Zúñiga, Jalisco, Mexico. E–mail: francisco.beltran@upjal.edu.mx

 

Article received on 11/19/2010.
Accepted 05/05/2011.

 

Abstract

In this paper, an adaptive beamformer algorithm LMS is presented and showed to improve the Bayesian Maximum Entropy–Variational Analysis (BMEVA) performance for high resolution radar imaging and denoising. A formalism to fuse the BMEVA and its integration inside the LMS structure is also presented. Finally, the image enhancement and denoising produced by the proposed Adaptive BMEVA method is analyzed, and the filter computational performance is demonstrated via SAR images scenarios.

Keywords: Data fusion, adaptive filter, LMS, SAR images, Bayesian maximum entropy.

 

Resumen

En este artículo se presenta la aplicación del algoritmo formador de haz adaptivo: Mínimos Cuadrados Medios (LMS), para mejorar el desempeño del método fusionado Máxima Entropía Bayesiana con Análisis Variacional (BMEVA) para formación de imágenes de radar de alta resolución y reducción del ruido. Además, el formalismo para integrar el método BMEVA fusionado, así como la inclusión bajo la estructura del LMS, es presentado. Finalmente, el mejoramiento de la imagen y la reducción del ruido producido por el método Adaptivo BMEVA es analizado, así como el desempeño computacional del filtro en función del IOSNR a través de diferentes escenarios con imágenes de Radar de Apertura Sintética.

Palabras clave: Fusión de datos, filtrado adaptivo, LMS, imágenes SAR, máxima entropía bayesiana.

 

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