【摘要】 随着物联网和体域网的飞速发展,人体运动追踪技术在医疗、安防等领域得到了广泛应用.针对传统惯性人体运动追踪系统存在累积误差和漂移的问题,本文提出了一种基于IMU/TOA融合的人体运动追踪方法.通过对融合系统克拉美罗界(Cramer-Rao Lower Bound,CRLB)的推导,从理论上证明了IMU/TOA融合方法的有效性.实验结果可以看出,本文提出的基于IMU/TOA融合的人体运动追踪方法,在空间性能和时间性能两个方面都有较大的提升.更多还原

【Abstract】 With the rapid development of the Internet of things and the body area network,the human motion tracking technology has been widely used in medical,security and many other fields.A human motion tracking method based on IMU/TOA fusion is proposed to solve the problem of error accumulation and drift in a single IMU human motion tracking system.On this basis,the effectiveness of IMU/TOA fusion method is proved theoretically by deducing the cramer-rao lower bound(CRLB) of fusion system.The experimental results show that the proposed human motion tracking method based on IMU/TOA fusion has great improvement in both spatial and temporal performance.更多还原