Deterministic Sampling for Nonlinear Dynamic State Estimation

• Tác giả: Igor Gilitschenski
• Ngôn ngữ: eng
• ISBN-13: 978-3731504733
• ISBN: KSP/1000051670
• Ký hiệu phân loại: 621.3 Electrical, magnetic, optical, communications, computer engineering; electronics, lighting
• Thông tin xuất bản: Karlsruhe : KIT Scientific Publishing, 2016
• Mô tả vật lý: 1 electronic resource (XVI, 167 p. p.)
• Bộ sưu tập: Tài liệu truy cập mở
• ID: 202170

Tóm tắt

The goal of this work is improving existing and suggesting novel filtering algorithms for nonlinear dynamic state estimation. Nonlinearity is considered in two ways: First, propagation is improved by proposing novel methods for approximating continuous probability distributions by discrete distributions defined on the same continuous domain. Second, nonlinear underlying domains are considered by proposing novel filters that inherently take the underlying geometry of these domains into account.