三维水下移动传感网多目标有向路径覆盖增强机制研究  

Research on Directional Path Coverage Enhancement Algorithm of Multiple Objects in 3D Underwater Mobile Sensor Networks

作　　者：张美燕[1] 蔡文郁[2] 周丽萍[1] 

机构地区：[1]浙江水利水电学院电气工程系,杭州310018 [2]杭州电子科技大学电子信息学院,杭州310018

出　　处：《传感技术学报》2014年第1期100-106,共7页Chinese Journal of Sensors and Actuators

基　　金：国家自然科学基金项目(61102067);浙江省自然科学基金项目(LQ12F03006);水声通信与海洋信息技术教育部重点实验室(厦门大学)开放课题项目;浙江省重中之重学科"海洋机电装备技术"开放基金项目

摘　　要：水下传感网中实现多个移动目标的协同追踪任是一个技术难题,针对这个问题论文提出了一种分布式的多目标有向路径覆盖增强算法。在实际的三维水下传感网中,水下传感器节点会随着水流运动而移动,被追踪的目标具有自主行动能力。假设移动规律遵从Meandering Current Mobility模型,多个运动目标沿着基于概率的Random Walk移动模型轨迹运动。在论文提出的算法中,覆盖运动路径的传感器节点通过两跳邻居节点范围内的水下传感器节点协同决策来实现最大化路径覆盖,通过调整水下传感器节点自身的有向覆盖方向达到多目标轨迹路径有向覆盖率平均值最大,并使多目标轨迹路径有向覆盖率标准方差尽量小。最后论文通过MATLAB软件仿真来验证分布式覆盖增强算法的有效性,能够显著提高多个移动目标的路径覆盖率。Collaborative tracking of multiple moving targets in mobile 3D underwater sensor networks remains to be a conundrum;therefore, this paper presents a distributed multi-target path coverage enhancement algorithm to be directed against above problem. Underwater sensor nodes are assumed to be mobile due to ocean current and the detective targets have the ability of autonomous mobility in practical mobile 3D underwater sensor networks. The movement law of underwater sensor nodes and multiple moving targets comply with Meandering Current Mobility models and Random Walk mobility model based on probability respectively. In our algorithm, the maximal path coverage ratio of multi-target trajectory paths is achieved by the collaborative decision-making within the two-hop neighbor nodes. The directional coverage orientations is decided with the objective to maximize path coverage ratio, moreover,the coverage ratio standard deviation of different target trajectory paths remains to be as small as possible. Finally,the effectiveness of distributed coverage enhancement algorithm is verified by MATLAB simulation and the results proved significantly improvement of multi-target path coverage ratio.

关 键 词：水下传感网 移动传感网 三维传感网 有向覆盖 目标追踪 

分 类 号：TP393[自动化与计算机技术—计算机应用技术]