基于惯性测量的主动室内定位系统研究

发布时间：2018-07-05 19:27

本文选题：主动室内定位 + 惯性测量　；参考：《江南大学》2014年硕士论文

【摘要】：随着微电子与通信技术的迅猛发展，实时定位导航技术得到了快速发展，应用日益普及。然而，在日常生活与工作最重要的室内环境中，当前主流的定位手段（如全球卫星定位系统）常因建筑物遮挡和多径衰落等效应，，造成定位困难或精度不足等问题。针对室内定位需求已出现了多种系统，它们采用不同的技术手段，性能与适用范围也存在差异，但部署难度与覆盖范围依然是当前阻碍室内定位技术应用的常见问题。惯性定位技术作为一种不依赖外界辅助的独立定位方式，在适用范围与部署难度上具有得天独厚的优势。另一方面，得益于智能移动终端及传感器技术的不断进步，智能手持设备不但运算能力越来越强，而且普遍内置了较完备的惯性测量传感器。因此，在手持平台上实现惯性室内定位已具有很高的可行性。在这样的背景下，本论文以广泛使用的智能手持设备为平台，设计并实现了一种主动惯性室内定位系统，可实现室内环境中无外界辅助条件下的主动相对定位，具有广泛的适用性。本论文研究的主动惯性室内定位系统主要基于捷联惯性定位方式，其基本思想是通过手持平台内置的加速度计与陀螺仪间的配合，获得设备运动过程中一个固定坐标系内的三维加速度，进而获得三维速度及位移信息。为实现此目标，主要需完成三部分的工作：首先获得加速度、角速度等惯性测量数据；然后进行坐标系转换、积分等数据处理，实现由加速度到位移的转换；最后，抑制采集与处理过程中引入的噪声与累积误差，保证定位顺利进行及定位结果准确可靠。论文的主要研究工作如下。 1、选用基于苹果公司iOS平台的智能移动手持终端，通过CoreMotion框架控制其内置的加速度计与陀螺仪进行数据采集，并使用定时器控制两者数据采集的同步与采样速率，使其组成惯性测量单元；然后，在磁阻传感器与CoreLocation框架的配合下实现惯性测量数据自设备坐标系至地理坐标系的转换。 2、为提高定位成功率与准确性，在定位解算过程中提出了一种主动惯性室内定位算法。该算法采用零速度修正方法的思想，结合角速度模值、加速度模值及其方差检测行人步行过程中的静止状态；然后，针对加速度、角速度、速度和位移的误差量设计了扩展型卡尔曼滤波器(EKF)，并在静止状态中利用速度测量值作为速度误差的观测值，对EKF进行更新；再通过更新后的速度及位移误差的最优估计来修正速度和位移。 3、为验证算法的有效性，以智能移动手持终端实测数据为基础，利用MATLAB平台对算法进行仿真验证；然后，对验证过的算法进行适当调整，将其应用于智能移动手持终端，并对系统进行测试。测试结果表明，实现的主动惯性室内定位系统在中近距离正常或低速步行等典型情况下，能有效地实现相对定位，单次定位过程中的位移误差可控制在步行距离的15%以内，且定位误差随时间变化较小。
[Abstract]:With the rapid development of micro - electronics and communication technology , real - time positioning and navigation technology has been rapidly developed , and its application is becoming more popular . However , in the most important indoor environment of daily life and work , there are many problems such as positioning difficulty or insufficient precision .

In this paper , the active inertia indoor positioning system is mainly based on strap - down inertial positioning method . The basic idea is to get the three - dimensional acceleration in a fixed coordinate system in the motion process of the equipment through the coordination between the accelerometer and the gyroscope built in the handheld platform . In order to achieve this goal , three parts of work are mainly completed : firstly , the inertial measurement data such as acceleration and angular velocity are obtained ;
then carrying out data processing such as coordinate system conversion , integration and the like to realize conversion from acceleration to displacement ;
Finally , the noise and accumulated errors introduced in the process of acquisition and processing are suppressed to ensure the smooth positioning and accurate and reliable positioning results . The main work of the thesis is as follows .

1 , selecting an intelligent mobile handheld terminal based on the Apple iOS platform , controlling the built - in accelerometer and the gyroscope to carry out data acquisition through the CoreMotion frame , and using a timer to control the synchronous and sampling rate of the data acquisition of the two data so as to form an inertial measurement unit ;
Then , the conversion of the inertial measurement data from the device coordinate system to the geographic coordinate system is realized under the cooperation of the magnetoresistive sensor and the CoreLocation frame .

2 . In order to improve the positioning success rate and accuracy , an active inertia indoor positioning algorithm is proposed in the process of positioning and solving . The algorithm adopts the idea of zero speed correction method , and combines the angular velocity model value , the acceleration mode value and the variance to detect the static state in the pedestrian walking process ;
Then , the extended Kalman filter ( EKF ) is designed for the error amount of acceleration , angular velocity , velocity and displacement , and the velocity measurement is used as the observation value of velocity error in the stationary state , and the EKF is updated ;
and then the speed and the displacement are corrected through the updated speed and the optimal estimation of the displacement error .

3 . To verify the validity of the algorithm , based on the measured data of the intelligent mobile handheld terminal , the algorithm is verified by MATLAB platform .
Then , the validated algorithm is properly adjusted , it is applied to intelligent mobile handheld terminal , and the system is tested . The test results show that the active inertia indoor positioning system can effectively realize relative positioning in the typical case of middle - distance normal or low - speed walking , and the displacement error can be controlled within 15 % of walking distance , and the positioning error changes with time .
【学位授予单位】：江南大学
【学位级别】：硕士
【学位授予年份】：2014
【分类号】：TN96

【共引文献】