摘 要惯性导航技术是利用加速度计和陀螺仪采集载体的加速度和角速度，通过 对加速度和角速度积分得到载体在导航坐标系下的速度和位置，最终实现导航 与定位。在这个过程中不需要与外界进行信号的交换，是完全自主的导航方法， 是解决在森林、城市峡谷、室内环境等 GPS 信号强度较弱的地区导航问题的有 效方法。随着微机电技术的快速发展，捷联惯性导航技术成为当前研究的热点。69943
本文主要研究基于低成本惯性传感器的行人航位推算模型。介绍了关于惯 性导航的基础理论，分析了零速检测辅助惯性导航的算法，利用在足部着地的 瞬间速度为零的特性，检测出该时刻的速度，并将其当做观测值带入卡尔曼滤 波，更新导航参数的协方差，将改正数反馈到导航系统当中，从而减弱误差的 累积，保证导航精确地进行。
通过实验验证，本文所介绍的行人航位推算模型在室内环境中可以实现米 级的导航精度，能够满足人们对于室内导航定位的需求。若经过进一步的修改 与完善，可以推广到一些灾害场景下的应急救援当中。
该论文有图 30 幅，表 2 个，参考文献 40 篇。
毕业论文关键词:室内定位 捷联式惯性导航 零速更新 卡尔曼滤波
Pedestrian Dead Reckoning Model Based Inertial Data
Abstract Inertial navigation technology is the use of acceleration and angular velocity of the accelerometer and gyroscope carrier, through the acceleration and angular velocity integral give the velocity and position of the carrier in navigation coordinate system, and ultimately the navigation and positioning. In this process does not require the exchange of signals with the outside world, is a fully autonomous navigation method is solved in the forest, urban canyons and indoor environment such as the weak GPS signal intensity area navigation problem. With the rapid development of MEMS technology, strapdown inertial navigation technology has become a hot research topic in the current research.
This paper mainly studies the pedestrian dead low cost inertial sensor based on model prediction. Introduced inertial navigation on the basic theory, analysis of the zero speed detection aided inertial navigation algorithm, the characteristic of zero at the foot of the instant speed and detect the speed of the moment and as the observation value into Kalman filter, update navigation parameters of the covariance, will change the positive feedback to the navigation system which, to lessen the error accumulation, to ensure accurate and navigation.
Through experimental verification, the pedestrian dead reckoning model in indoor environment can achieve meter level navigation accuracy can satisfy people's demand for indoor navigation and positioning. If further modification and improvement, which can be extended to a number of disaster scenarios in the emergency rescue.
Key words: indoor positioning strapdown inertial navigation zero velocity update Kalman filter
目 录
摘 要 I
Abstract II
目 录 III
图清单 IV
表清单 V
1 绪论 1
1.1 背景与意义 1
1.2 研究意义 基于惯性数据的行人航位推算模型:http://www.youerw.com/guanli/lunwen_79034.html