کد مقاله کد نشریه سال انتشار مقاله انگلیسی نسخه تمام متن
558671 874965 2007 13 صفحه PDF دانلود رایگان
عنوان انگلیسی مقاله ISI
Performance comparison of EKF and particle filtering methods for maneuvering targets
موضوعات مرتبط
مهندسی و علوم پایه مهندسی کامپیوتر پردازش سیگنال
پیش نمایش صفحه اول مقاله
Performance comparison of EKF and particle filtering methods for maneuvering targets
چکیده انگلیسی

Online tracking of maneuvering targets is a highly nonlinear and challenging problem that involves, at every time instant, the estimation not only of the unknown state in the dynamic model describing the evolution of the target, but also the underlying model accounting for the regime of movement. In this paper we review and compare several sequential estimation procedures, that use appropriate strategies for coping with various models that account for the different modes of operation. We focus on the application of the recently proposed cost-reference particle filtering (CRPF) methodology, which aims at the estimation of the system state without using probability distributions. The resulting method has a more robust performance when compared to standard particle filtering (SPF) algorithms or the interactive multiple model (IMM) algorithm based on the use of the well known extended Kalman filter (EKF). Advantages and disadvantages of the considered algorithms are illustrated and discussed through computer simulations.

ناشر
Database: Elsevier - ScienceDirect (ساینس دایرکت)
Journal: Digital Signal Processing - Volume 17, Issue 4, July 2007, Pages 774-786