【摘要】 无线室内定位是物联网技术的重要应用之一,为提高对于运动目标的定位和跟踪的精度,论文设计了基于TOA技术的扩展卡尔曼滤波算法。提出利用双边双向测距算法进行节点间的距离测定,将时钟误差及测距误差视为状态噪声,设计扩展卡尔曼滤波器,获得递推估计算法。在不同运动轨迹和不同噪声参数下的仿真测试结果表明,所设计算法可有效提高定位精度,改善目标跟踪效果。更多还原

【Abstract】 Indoor wireless location is one of the most important applications of internet of things. To improve the precision of location and tracking of mobile object,the extended Kalman filter algorithm is proposed based on Time of Arrival(TOA)method in this paper. The symmetrical double-sided two-way ranging algorithm is used to measure the distance between the nodes. The errors of timer and distance are considered as state noise. The extended Kalman filter is designed and the recursive estimation algorithm is achieved. The simulations under different mobile tracking and noise parameters are done,and the results show that the proposed algorithm can improve the location precision and tracking performance effectively.更多还原