应急环境下实时定位与无线网络资源优化协同设计

Emergencies often lead to drastic changes in the physical environment. Compared to outdoor environments, indoor rescue such as fires in buildings and mine safety accidents would face more complex spatial structures and worse field conditions. The accident may also cause damage to communications facilities in a short period of time, making it more difficult for rescue work. This project intends to conduct research on the key technologies of real-time positioning in the emergency environment and solve the problem of real-time data fusion and transmission under resource constraints. First, based on the optimal observation of distributed sensors, we quantitatively analyze the influence of the weight ratio of key features on positioning accuracy, and then construct a positioning model of multi-source sensing data. Secondly, in order to provide reliable and timely decision information for building efficient resource scheduling strategy, we would explore the impact of nodes’ logical location on the spectrum resource perception and scheduling decisions to present a data transmission optimization scheme for the clustering networks. Finally, to improve the flexibility and reliability of positioning method, a network resource allocation strategy for emergency environment is designed, which can be dynamically adaptable to kinds of complex network environment. The research results of this project can provide theoretical basis and technical support for real-time location networks in emergency environments.

突发事件常常引发物理环境剧变，相较于室外环境，室内救援如建筑内火灾、矿井安全事故救援将面临更为复杂的空间结构和更恶劣的现场环境。事故还可能短时间内造成通讯设施的损毁，阻断现场信息获取和传输渠道，给救援工作增加难度。本项目拟针对应急环境下的实时定位关键技术开展研究，解决资源受限下实时数据融合与传输的难题。首先，利用分布式传感器的优选观测量，定量分析关键数据特征的权重配比对定位精度的影响，构建融合多源传感数据的定位模型。其次，探索网内节点所处位置对资源分配与调度决策的影响，提出通信时延约束下分簇网络时-空关联的数据传输优化方案，提高定位策略的实时性。最后，设计适用于应急环境下的网络资源分配策略，保障网络动态适应各种复杂的空间环境、网络环境、业务环境的变化，实现有限带宽的有序、高效利用，提高定位策略的灵活性和可靠性。本课题的研究成果有望为应急环境下实时定位与组网技术提供理论依据和技术支持。

突发事件常常引发物理环境剧变，相较于室外环境，室内救援如建筑内火灾、矿井安全事故救援将面临更为复杂的空间结构和更恶劣的现场环境。事故还可能短时间内造成通讯设施的损毁，阻断现场信息获取和传输渠道，给救援工作增加难度。本项目主要针对应急环境下的实时定位关键技术开展研究，解决资源受限下实时数据融合与传输的难题。首先，基于分布式传感器的多维观测量，构建了融合多源异构传感数据的定位模型，并给出基于优选数据共享的动态定位模式切换策略。其次，为了保证网络的可靠连通，项目研究了关键数据QoS关联的无线网络实时传输与资源管理的科学方法，在满足目标决策模型精度的前提下，最大限度的提高网络资源的利用率。最后，本项目分析了如何利用现有无线节点可测的物理特性排除检测中的干扰因素影响，给出网络系统状态在线估计方法，提高网络节点对各种参数状态监测的灵敏度和评估的准确性，并建立了基于分布式多特征参量、多维判据的无线网络链路状态自评估诊断和参数动态调整模型，为网络系统的全局控制策略提供可靠、及时的决策信息。本项目执行期内在 IEEE Transactions on Vehicular Technology、 IEEE Transactions on Smart Grid、 Computer Networks、控制理论与应用等刊物发表论文 17篇，发表会议论文 4 篇，申请国家发明专利 9 项，其中已授权 2 项。

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