A ToA/IMU Indoor Positioning System by Extended Kalman Filter, Particle Filter and MAP Algorithms

作者：Chen Xuechen^*; Song Shupeng; Xing Jihong

来源：27th IEEE Annual International Symposium on Personal, Indoor, and Mobile Radio Communications (PIMRC), 2016-09-04 to 2016-09-08.

This work introduces an indoor positioning system (IPS) which is a combination of wireless sensor network (WSN) and inertial navigation system (INS) for locating a moving object indoor. Here, WSN is adopted to measure the ranges from the unknown node to those anchor nodes by time of arrival (ToA) method. The core of the INS is the inertial measurement unit (IMU), which consists of accelerometers and gyroscopes. The real time inertial measurements from IMU and the range information by ToA method are both transmitted to processing terminal, where we propose to use three kinds of recursive Bayesian algorithms to make use of data to obtain the location estimations. The experimental results show that even with only two anchor nodes, the estimation accuracy of hybrid method by these three algorithms is higher than both standalone ToA method with 3 anchors and pure inertial solution.

• 出版日期2016
• 单位中山大学