随着传感器分辨率的提高，一个目标在每个时刻可产生多个量测，点目标假设不再成立，扩展目标跟踪成为军事领域亟需研究的课题。本项目拟对扩展目标跟踪算法及性能评估进行深入研究，主要内容有：研究非线性系统、不规则扩展目标的多传感器跟踪算法，并研究量测分布与传感器参数、目标-传感器的几何位置之间的关系；采用联合估计目标状态和数据关联的策略，解决杂波环境下非线性系统的多扩展目标跟踪问题；研究不规则形状估计的性能评价指标，及目标运动状态和形状估计的综合性能评价体系；研究目标估计误差下界，为滤波算法评估、扩展目标模型的合理性评价和优化提供依据；研究目标跟踪和类型识别模块间的信息交换方案，提出扩展目标联合跟踪和类型识别算法，提高目标跟踪精度和类型识别的准确率；最后，通过仿真和实验对算法性能进行测试和验证。本项目研究将提高军事或民用领域的目标跟踪和类型识别能力，对提高我国军事防御和攻击能力具有重要的现实意义。

With the increasing of the sensor resolution capability, a target gives rise to several measurements from different measurement sources, and thus the assumption which a target is considered as the point target in the most tracking application, is no longer valid. The extended target tracking has become an urgent research subject in the military field. In this project, tracking algorithms and its performance evaluation of the irregular shape extended target will be deeply researched. The research mainly includes the following aspects: Firstly, the multiple sensor tracking algorithm for the irregular extended target tracking of nonlinear system will be researched, and the relationship between the measurement distribution and the sensor parameters and the relative geometric position of the target-sensor will also be studied on; Secondly, to track multiple extended targets for the nonlinear system in the presence of clutter measurements, the target state and data association will be jointly estimated; Thirdly, the performance evaluation for the irregular shape, and the comprehensive performance evaluation for the kinematic state and the shape, will be discussed; And then, the target state estimation lower bound, which could provide a basis for the performance evaluation of the filtering algorithm and for the extended target model optimization, will be researched; Fourthly, to enhance the tracking accuracy and the class recognition accuracy, the scheme of the information exchange between the tracking module and the class recognition module will be researched, and the joint target tracking and class recognition algorithm will be proposed; Finally, the performance of algorithms will be tested and verified through simulations and experiments. This project will improve the ability of the target tracking and the class recognition in military or civil filed, and has important practical significance to enhance the defense and attack abilities for our military system.