CAJ | 학술논문

针对低成本IMU自主个人导航系统方位漂移的问题,提出了一种融合鞋式IMU、楼层平面图的个人导航解决方案,为实现精度较高的室内相对定位设计了一种新的辅助粒子滤波算法.引入卡尔曼滤波+粒子滤波的级联框架,底层卡尔曼滤波器在捷联解算的基础上,利用零速修正技术估计 IMU 的位置和姿态;上层粒子滤波器提取步行中每一步的步长和方位变化作为量测,建立相应的步行运动模型融入非线性地图匹配技术.考虑室内应用情境,通过对传递粒子的多步推演预测和选择性剔除,推导了一种新的粒子滤波算法.采集低精度IMU的室内行走数据验证了算法的有效性:约300 m行程的室内导航最终位置误差不超过0.3 m.表明提出的级联滤波算法框架能有效解决建筑平面信息辅助情形下的个人导航问题,新设计的粒子滤波算法有助于提高个人导航系统连续位置测定的精度和可靠性.
침대저성본IMU자주개인도항계통방위표이적문제,제출료일충융합혜식IMU、루층평면도적개인도항해결방안,위실현정도교고적실내상대정위설계료일충신적보조입자려파산법.인입잡이만려파+입자려파적급련광가,저층잡이만려파기재첩련해산적기출상,이용령속수정기술고계 IMU 적위치화자태;상층입자려파기제취보행중매일보적보장화방위변화작위량측,건립상응적보행운동모형융입비선성지도필배기술.고필실내응용정경,통과대전체입자적다보추연예측화선택성척제,추도료일충신적입자려파산법.채집저정도IMU적실내행주수거험증료산법적유효성:약300 m행정적실내도항최종위치오차불초과0.3 m.표명제출적급련려파산법광가능유효해결건축평면신식보조정형하적개인도항문제,신설계적입자려파산법유조우제고개인도항계통련속위치측정적정도화가고성.
As heading drift error remains a problem in a standalone pedestrian navigation system(PNS) that uses low-cost inertial measurement unit(IMU), an algorithm for integrating shoe-mounted IMU with building plane was proposed, and a novel auxiliary particle filter which is more applicable in indoor navigation scenario was devised. A double-deck framework comprises Kalman filter(KF) and particle filter(PF) was introduced, in which the lower KF applies zero-updating measurement for drift correction. The upper PF computes the step-wise changes of IMU position and heading to use them as measurements, and a corresponding pedestrian movement model was constructed for fusing nonlinear map-matching technique. The proposed algorithm is verified through experimental data collected from a low-performance IMU mounted on foot:the final positioning error of 300 m travel distance is less than 0.3 m. It is also shown that the consistent positioning accuracy and reliability of a PNS could be improved effectively with the modified auxiliary particle filter.