Cooperative Approaches to Design of Nonlinear Filters

非线性滤波器设计的协作方法

基本信息

批准号：
283072193
负责人：
Professor Dr.-Ing. Uwe D. Hanebeck
金额：
--
依托单位：
Department of Cybernetics
依托单位国家：
德国
项目类别：
Research Grants
财政年份：
2016
资助国家：
德国
起止时间：
2015-12-31 至 2019-12-31
项目状态：
已结题

来源：
https://gepris.dfg.de/gepris/projekt/283072193?language=en
关键词：
Cooperative Approaches Design Nonlinear Filters

项目摘要

This project is devoted to the state estimation of (nonlinear) discrete-time stochastic dynamic systems based on noisy measurements. State estimation plays a key role in many applications where the knowledge of a system state is required for, e.g., (multistep) prediction, control, fault detection, or generally for a decision making. Important applications such as navigation, tracking, localization, and optimal control can be found in the areas of robotics and automation.In the past decades, the design of nonlinear filters has attracted a significant attention in literature and many (approximate) filtering approaches differing in assumptions, estimation quality, efficiency, and purpose have been proposed. The vast majority of the proposed filters are not optimal; and hence, tailored to specific settings. As a consequence, it is a challenging task to select an appropriate filter for an application. Typically, extensive simulations have to be performed in which different nonlinear filters compete against each other.The objective of this project is to shift from a competitive use of nonlinear filters to a cooperative approach. In particular, the stress is laid on the design of a general framework for a conceptually new cooperative approach to nonlinear filter design. This approach takes an advantage of a combination of, in some sense, complementary properties of various nonlinear - usually approximate - filters. The project analyzes four types of possible cooperative behavior of local filters (integration, monitoring, combination, and feedback) and develops respective algorithms. Using several cooperation types in filter design simultaneously leads to a cooperative global filter. Compared to the traditional filter design, which is rather competitive, the cooperative global filter will provide estimates with generally higher estimation quality in terms of accuracy, credibility, and integrity.

该项目致力于基于噪声测量的（非线性）离散时间随机动态系统的状态估计。状态估计在许多需要了解系统状态的应用中发挥着关键作用，例如（多步）预测、控制、故障检测或一般决策。导航、跟踪、定位和最优控制等重要应用可以在机器人和自动化领域找到。在过去的几十年中，非线性滤波器的设计在文献中引起了极大的关注，许多（近似）滤波方法在提出了假设、估计质量、效率和目的。绝大多数提出的滤波器都不是最优的；因此，根据特定的设置进行定制。因此，为应用选择合适的滤波器是一项具有挑战性的任务。通常，必须进行广泛的模拟，其中不同的非线性滤波器相互竞争。该项目的目标是从非线性滤波器的竞争使用转向合作方法。特别是，重点放在非线性滤波器设计概念上新的协作方法的总体框架的设计上。在某种意义上，这种方法利用了各种非线性（通常是近似的）滤波器的互补特性的组合。该项目分析了本地滤波器四种可能的协作行为（集成、监控、组合和反馈）并开发了各自的算法。在滤波器设计中同时使用多种协作类型会产生协作全局滤波器。与具有相当竞争力的传统滤波器设计相比，协作全局滤波器将提供在准确性、可信度和完整性方面普遍更高的估计质量的估计。

项目成果

期刊论文数量（4）

专著数量（0）

科研奖励数量（0）

会议论文数量（0）

专利数量（0）

Comparative Study of Track-to-Track Fusion Methods for Cooperative Tracking with Bearings-only Measurements

仅方位测量协同跟踪的轨对轨融合方法的比较研究

DOI：
10.1109/icphys.2019.8780330
发表时间：
2019
期刊：
2019 IEEE International Conference on Industrial Cyber Physical Systems (ICPS)
影响因子：
0
作者：
Radtke;Susanne;Kailai Li;Benjamin Noack;Uwe D. Hanebeck
通讯作者：
Uwe D. Hanebeck

Reconstruction of Cross-Correlations with Constant Number of Deterministic Samples

确定性样本数量恒定的互相关重建