中圖分類號：TN92 文獻(xiàn)標(biāo)志碼：A DOI：10.16157/j.issn.0258-7998.233797 中文引用格式： 劉倩蕓,，林敏,，劉灝，等. 基于超寬帶系統(tǒng)的雙卡爾曼濾波定位算法[J]. 電子技術(shù)應(yīng)用,，2023,，49(6)：58-62. 英文引用格式： Liu Qianyun，Lin Min,，Liu Hao,，et al. A double-layer Kalman filter positioning algorithm based on ultra-wide band system[J]. Application of Electronic Technique，2023,，49(6)：58-62.
A double-layer Kalman filter positioning algorithm based on ultra-wide band system
Liu Qianyun,，Lin Min，Liu Hao,，Yu Ze,，Zheng Liyin
(School of Communication and Information Engineering， Shanghai University,， Shanghai 200444,， China)
Abstract： In order to track and locate the moving target in complex indoor environment, a double-layer Kalman filter (DKF) with weakening NLOS noises is designed, which cascades the classical Kalman filter (KF) and the Extended-Kalman filter (EKF). A method for distinguishing the noises is introduced into KF by adjusting the covariance according to the residual between the prediction and measurement. Through this method, the filter gain of KF is able to adjust adaptively, so that the distances measured by ultra-wide band (UWB) sensors can be smoothed and then input into the next EKF. Finally, the real-time positioning is achieved by outputting the position information of the moving target after EKF at each iteration. The algorithm is simulated on MATLAB, and the tracking accuracy is compared with several existing algorithms under the constant velocity (CV) model. The proposed DKF can achieve high accuracy within 3 cm in LOS environment and 10 cm in NLOS environment.
Key words : UWB；Kalman filter,；indoor positioning,；NLOS noises
