本项目以复杂非线性非高斯随机系统中的状态估计和滤波需求为基本背景，以增加目标先验信息为切入点，探索精度和实时性相融合的模糊语义粒子滤波理论与方法，使之基本满足非线性非高斯随机系统对非线性滤波理论和应用的需要。基于模糊概率和模糊语义信息处理理论，建立能够有效融合目标特征语义信息的模糊语义概率模型；优化多特征语义模糊集，提出基于K-L散度模糊聚类的语义特征模糊集自适应方法；引入目标特征信息和观测信息，提出融合模糊集合序列条件估计和截断理论的重要性密度函数构建方法，综合改善算法的精度和时间复杂度；开展模糊语义粒子滤波方法的应用研究，以多目标跟踪为例，重点对多目标交互运动模型、高维状态空间的粒子采样以及目标数目时变情况下的数据关联等几个关键问题展开研究。研究成果不仅可以有效解决非线性非高斯随机系统的非线性滤波问题，而且可为其它复杂随机系统的数据分析和处理领域的应用研究提供新的研究方法和研究思路。

To the state estimation and filtering problem in the complex nonlinear non-Gaussian stochastical system, this project will study real-time and high precise the fuzzy semantic particle filtering theory and methods by increasing the target prior information, and make its basically meet the requirement of the nonlinear filtering theory and application for nonlinear non-Gaussian stochastical system. Based on the fuzzy probability and fuzzy semantic information processing theory, this project will propose the fuzzy semantic probability model that can effectively incorporate the semantic information of the target feature. By optimizing the multi-feature semantic fuzzy sets, this project will propose an adaptive feature semantic fuzzy set approach based on Kullback-Leibler (K-L) divergence fuzzy clustering. To incorporate target feature information and latest observation information, this project will propose a new the importance density function based on fuzzy set sequence condition estimation and truncation theory, which can effectively improve the precision and time complexity of this algorithm. Finally, this project will study the application of fuzzy semantic particle filtering method for multi-target tracking, which will mainly focus on multi-target interaction motion model, the particle sampling problem in the high dimensional state space and the data association with time-varying target number. The research results of this project can not only solve the nonlinear filtering problem of nonlinear non-Gaussian stochastic systems, but also provide new methods and ideas for the application of data analysis and processing in other complex stochastic systems.