一种改进的高斯粒子滤波室内定位算法陈波覃锡忠贾振红邓磊王晓兵张家林.pdf

246 2017 ，53（14） Computer Engineering and Applications 计算机工程与应用 一种改进的高斯粒子滤波室内定位算法 1 1 1 2 2 2 陈 波 ，覃锡忠 ，贾振红 ，邓 磊 ，王晓兵 ，张家林 1 1 1 2 2 2 CHEN Bo , QIN Xizhong , JIA Zhenhong , DENG Lei ，WANG Xiaobing , ZHANG Jialin 1.新疆大学 信息科学与工程学院，乌鲁木齐 830046 2. 中国移动通信集团新疆有限公司，乌鲁木齐 830063 1.School of Information Science and Engineering, Xinjiang University, Urumqi 830046, China 2.Subsidiary Company of China Mobile in Xinjiang, Urumqi 830063, China CHEN Bo, QIN Xizhong, JIA Zhenhong, et al. Improved Gaussian particle filter algorithm for indoor positioning. Computer Engineering and Applications, 2017, 53 （14）：246-250. Abstract ：In the wireless indoor positioning research, it proposes using the phone built inertial acceleration sensor data to calculate the user ’s motion path, automatically acquires the fingerprint data when passing through the fingerprint, auto- matically builds fingerprint database to reduce the large amount of data collection in the stage of off-line fingerprint data- base establishment. Due to cellphone ’s built-in acceleration sensors collect data exists non-linear noise and other interfer- ence, it proposes an improved GPF （Gaussian Particle Filter ）algorithm, the improved filtering algorithm acceleration fil- tered samples get a better valuation to calculate the motion path. It results a significant effect on state variables obeys lin- ear variation and observed equation obeys nonlinear changes system model. Experimental results show that the improved algorithm to calculate the path is better than Gaussian particle filter algorithm and Kalman filter algorithm and reduces the computational complexity. After the new method to establish the database, it will save a lot of off-line data collection job, but basically the same accuracy as compared with the traditional method of fingerprint data