基于MEMS的消防单兵室内定位研究与设计

发布时间：2018-03-31 02:32

本文选题：消防员　切入点：室内定位　出处：《山东大学》2017年硕士论文

【摘要】：社会的快速发展与火灾频发的状况对消防救援提出越来越高的要求。针对火灾现场的特殊情况,开发高效可靠的消防员室内定位设备,确保后方指挥系统能够实时了解火场中消防人员的位置和运动状态,高效快速的部署救援决策,有效的完成救援任务,保障消防员及人民群众的生命财产安全有着重要意义。本文首先简述了室内定位相关技术和惯性导航研究现状。由于传统的室内定位技术无法直接应用于火场环境,本文基于前期消防员单兵作战侦查系统研究基础和特殊的应用场景,提出了不依赖于外部信息的消防员上下双惯导定位方案。然后,对该方案各个模块的硬件电路进行了设计,包括电源电路、FPGA最小控制系统、双惯导模块以及蓝牙模块等;之后,探讨了人员运动状态判断的神经网络建立过程、行走位移的估计以及室内航向角的推算算法;最后,利用FPGA按照Top-Down(自上而下)模块化设计思想和流程对系统功能进行了实现,并完成了对各单元模块的仿真测试。本文提出的室内定位方案摒弃了惯用的零速检测(ZUPT)算法,通过对惯导数据的研究和分析,建立了用于人体运动状态判断和行走步长估计的BP神经网络模型,结合自相关函数对步频的计算,求解出行走路程,使室内位移值计算更加准确;利用扩展卡尔曼滤波(EKF)对惯导数据进行融合,可精确推算出行人运动方位角;定位装置选用具有并行数据处理能力的现场可编程门阵列FPGA作为主控制器,可将两惯导模块的采集数据同时处理,提高了实时性、降低了设计成本。大量实验测试表明,本方案硬件设计合理、算法高效、系统性能稳定可靠,达到了消防员室内定位的需要,具有较强的使用价值和广阔的应用前景。
[Abstract]:The rapid development of the society and the frequent fire situation put forward higher and higher requirements for fire fighting rescue. In view of the special situation of the fire scene, the development of efficient and reliable fireman indoor positioning equipment, To ensure that the rear command system can understand the position and movement of fire fighting personnel in real time, deploy rescue decisions efficiently and quickly, and effectively complete the rescue mission. It is of great significance to ensure the life and property safety of firefighters and people. Firstly, this paper briefly introduces the research status of indoor positioning technology and inertial navigation. Because the traditional indoor positioning technology can not be directly applied to the fire site environment, In this paper, based on the research foundation and special application scene of firemen's single combat investigation system, a new scheme of fireman's upper and lower inertial navigation is proposed, which does not depend on external information. Then, the hardware circuit of each module of the scheme is designed. Including the power circuit FPGA minimum control system, dual inertial navigation module and Bluetooth module, etc. After that, the establishment process of neural network, the estimation of walking displacement and the calculation algorithm of indoor heading angle are discussed. The function of the system is realized by using FPGA according to Top-Downmodularization design idea and flow chart, and the simulation test of each unit module is completed. The indoor positioning scheme proposed in this paper abandons the usual zero-speed detection algorithm. Based on the research and analysis of inertial navigation data, a BP neural network model for the estimation of human motion state and walking step size is established. Combining with the calculation of the step frequency of autocorrelation function, the walking distance is solved. The calculation of indoor displacement value is more accurate, the extended Kalman filter (EKF) is used to fuse the inertial navigation data, and the moving azimuth angle of the traveller can be calculated accurately. The locator adopts field programmable gate array (FPGA) with parallel data processing ability as main controller, which can process the data collected by the two inertial navigation modules at the same time, which improves the real-time performance and reduces the design cost. A large number of experiments show that, The hardware design of this scheme is reasonable, the algorithm is efficient, the system performance is stable and reliable, which meets the need of fireman's indoor positioning, and has strong application value and broad application prospect.
【学位授予单位】：山东大学
【学位级别】：硕士
【学位授予年份】：2017
【分类号】：TN96

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