偏差有界不确定动态系统容偏数据关联和估计融合研究

项目名称： 偏差有界不确定动态系统容偏数据关联和估计融合研究

项目编号： No.61273074

项目类型： 面上项目

立项/批准年度： 2013

项目学科： 自动化技术、计算机技术

项目作者： 朱允民

作者单位： 四川大学

项目金额： 83万元

中文摘要： 近三十年，多传感器信息融合在国防、科技、经济、社会等众多领域发挥着重要的作用。在实际应用中，被探测目标或观测器大都处在各种复杂、变化环境中，再将存在系统错误，包括运动和观测方程模型偏差简化为传统的标准框架已经远不能满足需要。本项目主要研究即使模型纠偏后仍存在未知偏差的容偏稳健数据关联和估计融合理论和方法。我们将借助国际上最新发展的优化理论和方法、特别是近年来国际顶尖优化和信息处理专家新获得的稳健优化和集值滤波技术，加上我们在以往基金项目完成中所获得的成功经验和技巧，研究在当前实际应用中有迫切需求的不确定动态系统容偏数据关联、估计一体化稳健融合，克服长期悬而未决的模型纠偏和数据关联互为前提、相互影响，分别处理效果差的难点。同时，所获得的新方法包括在多项式时间内可实现的高效算法，使成果在基础理论上有显著创新，在工程实际中有广泛应用价值。

中文关键词： 有偏动态系统；极小化欧氏误差；集值滤波；多算法融合；异构信息估计融合

英文摘要： In the past thirty years, multisensor information fusion has been very important powerful in national defence, science and technology, economy and society. In practical applications, the targets under detection and observers are very often in various complecated and changed situation. Hence, it is not satisfied that the process and measurement equations are simplified as a standard and ideal framework. In this project, we will study bias-tolerant data association and estimation fusion theory and mothods even if there is still unknown model biases after people corrected the model biases. We will use newly developed optimization theory and methods, in particular, robust optimization technique and set-membership filtering developed by some top-rate optimization and information processing experts in the world, along with our successful experience and skills summarized in the previous science foundation projects to study the integrated bias-tolerant data association and robust estimation fuison for uncertain dynamic systems which is a emergent research problem in the current applications. In doing so, we first have to overcome a long time unsolved difficulty- - model bias correction and data association are mutually associated and influenced. In the meantime, the new results must contain high efficiency polynom

英文关键词： biased dynamic system；minimizing Euclidean error；set-member-ship filter；multi-algorithm fusion；heterogeneous information estimation fusion