移动目标在最小暴露路径(MEP)上的暴露度值反应了无线传感网检测移动目标穿越覆盖区域时的能力，是衡量感知服务质量的一个重要指标。现有基于带权图模型求解最小暴露路径方法(如网格法和维诺图法)存在如下两个缺陷：1. 精度不好控制、偏差大,感应模式单一不够通用；2.缺乏考虑实际约束条件限制、过于依赖起点终点位置.针对这些缺点，本项目首先考虑基于泛函极值理论将起点终点固定的MEP问题抽象成连续优化新模型；其次考虑结合实际限制条件将固定起点和终点的MEP问题推广成带约束条件限制的MEP问题，并抽象成混合优化新模型.最后针对这些新模型高维非线性的特点，结合问题实际背景，研究集成各种高维优化、局部加速、平滑等全局寻优技术的进化求解算法，可以有效减小偏差，以解决异构传感器节点覆盖能力评估、适合多种感应模式等场合的要求，而推广的MEP问题的讨论可以作为更为灵活的评价覆盖质量的方式。

The exposure value of the Minimum Exposure Path (MEP) for mobile target detection shows the sensing and monitoring abilities that a given WSN can offer when a mobile target through the sensing field, and is one of the important indicators to measure the quality of coverage. The shortcomings of the existing methods (such as grid-based and the Voronoi-diagram-based methods) to MEP include: first, the solving algorithms are either hard to control precision, big deviation or are limit in one single sensing way and not general enough; second, MEP relies too much on the locations of starting point and finishing point, lacks of considering the limits of actual situation. In this project, first, a new continuous optimization model is built up based on the funcitonal extreme theory for MEP; second, MEP with fixed original piont finish point is protmoted as one with some path constraint conditions, and a new hybrid optimization model is abstracted to the protmoed one; finally, as it is difficult to solve these models with high-dimensional and nonlinear characteristics, some evolutionay algorithms are adopted, incorporating with the background characteristics and some global opimal technology such as high-dimensional optimizaiton technology, local searching technology ,smooth scheme.The design of these models and their solving algorithms would effectively reduce the deviation, solve the heterogeneous sensor node coverage capability assessment, and would be suitable for a variety of sensing patterns and other occasions, and the promoted MEP could be used as a general way to evaluate the quality of the cover.