摘要
针对当前室内无线定位信号强度易受干扰、设备部署维护成本高等缺点,以及手机在室内航位推算过程中定位误差随时间累积的问题,本文提出了基于粒子滤波磁场匹配的室内定位方法。相比于传统的航位推算方法,通过改进步态判断方式,并提出了动态步长估计算法和卡尔曼滤波航向估计算法,有效减少步态误判和定位误差。同时通过结合航位推算位置选择粒子滤波算法中的重采样区域,加快粒子收敛速度。最后,通过仿真分析和实际室内环境测试结果表明,本文提出的定位方法能够有效地减小定位误差,并实现2米的定位精度。
Due to in the current wireless based indoor positioning method the received signal strength are suscepti-ble to interference,the cost of equipment deployment and maintenance is high,and the question of in PedestrianDead Reckoning（PDR）systems localization error accumulated by time,this paper presents an indoor positioning sys-tem on smartphone,which uses magnetic matching positioning methods built on particle filter to correct localizationerror in the PDR approach. Compared to the traditional PDR method,the proposed method improves the step detec-tion method and applies a dynamic step length estimation algorithm and heading estimation according to Kalman fil-ter to enhance the robustness and minimize errors. In addition,an adaptive region selection resampling algorithm isintroduced to accelerate the rate of convergence. Finally,through conducting comprehensive experiments and tests,and the results show that the proposed technique can reliably achieve 2 meters precision in a large building.
出处
《传感技术学报》
CAS
CSCD
北大核心
2016年第9期1441-1448,共8页
Chinese Journal of Sensors and Actuators
基金
国家自然科学基金项目(51377187)
重庆市研究生科研创新项目(CYS16033)
关键词
地磁匹配
航位推算
室内定位
卡尔曼滤波
粒子滤波
magnetic matching
pedestrian dead reckoning
indoor localization
kalman filter
particle filter
