面向复杂系统估计的采样型非线性滤波方法研究

项目名称： 面向复杂系统估计的采样型非线性滤波方法研究

项目编号： No.61300214

项目类型： 青年科学基金项目

立项/批准年度： 2014

项目学科： 自动化技术、计算机技术

项目作者： 胡振涛

作者单位： 河南大学

项目金额： 23万元

中文摘要： 伴随着感知手段日趋丰富、感知能力日益增强，以及对感知对象认识的不断深入和感知要求的日益提高，人们在复杂系统估计中越来越难以回避非线性、非高斯、噪声相关、分布式和不确定等问题。本项目结合采样型非线性滤波器的自身优势，针对复杂系统呈现出的噪声相关、分布式以及不确定等特征开展滤波器设计和优化工作。主要内容包括：第一，拟从随机采样型滤波器实现原理入手，结合系统状态模型重构技术，研究多传感器量测噪声和过程噪声相关的采样型非线性滤波器；第二，拟结合被估计系统的结构特点以及确定性和随机性采样的优点，研究基于确定-随机采样综合的分布式采样型非线性滤波器；第三，拟在量测跳变马尔可夫模型构建基础上，结合马尔科可夫蒙特卡罗采样、重采样和加权融合技术，研究多传感器量测不确定下基于粒子权重优化的采样型非线性滤波器；最后，以多传感器机动多目标跟踪为应用场景，进一步分析系统所呈现的具体特征，优化算法设计。

中文关键词： 非线性滤波；多源信息融合；目标跟踪；随机性采样；确定性采样

英文摘要： With the means of perception increasingly richer, perception ability enhanced and the deeped understanding of perception object as well as the gradually increasing of perception requirements, it is difficult to avoid the problems such as nonlinear, non-Gaussian, noise correlated, distributed and uncertain problems in the estimation of complex system. Combining with the advantages of sampling nonlinear filter, the design and optimization of filters are studied for noise correlated, distributed and uncertain features appeared in complex system. Some important research work will be included in this project as following: First, based on the realization principle of stochastic sampling filters, meanwhile, by virtue of the reconstruction of system state model, a sampling nonlinear filter with correlated multisensor measurement noise and process noise is to be studied. Second, according to the structural features of estimated system and the advantages of deterministic and stochastic sampling, a distributed sampling nonlinear filter based on comprehensive deterministic-stochastic sampling is to be studied. Third, based on the construction of measurement Jump/Switch Markov model, meanwhile, combining with Markov Chain Monte Carlo sampling, re-sampling technique and weight fusion, a sampling nonlinear filter with partic

英文关键词： Nonlinear filter；Multi-source information fusion；Target tracking；Random sampling；Deterministic sampling