کد مقاله کد نشریه سال انتشار مقاله انگلیسی نسخه تمام متن
5002354 1368452 2016 8 صفحه PDF دانلود رایگان
عنوان انگلیسی مقاله ISI
Numerical Investigation of Gaussian Filters with a Combined Type Bayesian Filter for Nonlinear State Estimation
ترجمه فارسی عنوان
بررسی عددی فیلترهای گاوسی با فیلتر بیزی ترکیبی برای ارزیابی وضعیت غیرخطی
موضوعات مرتبط
مهندسی و علوم پایه سایر رشته های مهندسی مکانیک محاسباتی
چکیده انگلیسی
This study presents a numerical comparison of three filtering techniques for a nonlinear state estimation problem. We consider an Extended Kalman Filter (EKF), an Unscented Kalman Filter (UKF) and a combined type of Particle Filter, so-called Extended Particle Filter (EPF), for the state estimation for a re-entry vehicle system. The challenge in state estimation for this system is presence of significant nonlinearities in the process and measurement models. The performance aspects for the comparison include computation time, simulation time step, and effect of the choice of the initial conditions for the state estimate and covariance. Also, an investigation of the effect of the number of particles for EPF is performed. Simulation results illustrate that although EPF is computationally more expensive than EKF and UKF, it is less affected by the choice of initial conditions and simulation time step size.
ناشر
Database: Elsevier - ScienceDirect (ساینس دایرکت)
Journal: IFAC-PapersOnLine - Volume 49, Issue 18, 2016, Pages 446-453
نویسندگان
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