tailieunhanh - Báo cáo hóa học: " From Matched Spatial Filtering towards the Fused Statistical Descriptive Regularization Method for Enhanced Radar Imaging"

Tuyển tập báo cáo các nghiên cứu khoa học quốc tế ngành hóa học dành cho các bạn yêu hóa học tham khảo đề tài: From Matched Spatial Filtering towards the Fused Statistical Descriptive Regularization Method for Enhanced Radar Imaging | Hindawi Publishing Corporation EURASIP Journal on Applied Signal Processing Volume 2006 Article ID 39657 Pages 1-9 DOI ASP 2006 39657 From Matched Spatial Filtering towards the Fused Statistical Descriptive Regularization Method for Enhanced Radar Imaging Yuriy Shkvarko Cinvestav Unidad Guadalajara Apartado Postal 31-438 Guadalajara Jalisco 45090 Mexico Received 20 June 2005 Revised 4 November 2005 Accepted 23 November 2005 Recommended for Publication by Douglas Williams We address a new approach to solve the ill-posed nonlinear inverse problem of high-resolution numerical reconstruction of the spatial spectrum pattern SSP of the backscattered wavefield sources distributed over the remotely sensed scene. An array or synthesized array radar SAR that employs digital data signal processing is considered. By exploiting the idea of combining the statistical minimum risk estimation paradigm with numerical descriptive regularization techniques we address a new fused statistical descriptive regularization SDR strategy for enhanced radar imaging. Pursuing such an approach we establish a family of the SDR-related SSP estimators that encompass a manifold of existing beamforming techniques ranging from traditional matched filter to robust and adaptive spatial filtering and minimum variance methods. Copyright 2006 Hindawi Publishing Corporation. All rights reserved. 1. INTRODUCTION In this paper we address a new approach to enhanced array radar or SAR imaging stated and treated as an ill-posed nonlinear inverse problem. The problem at hand is to perform high-resolution reconstruction of the power spatial spectrum pattern SSP of the wavefield sources scattered from the probing surface referred to as a desired image . The reconstruction is to be performed via space-time processing of finite dimensional recordings of the remotely sensed data signals distorted in a stochastic measurement channel. The SSP is defined as a spatial distribution of the power . the .