一种基于粒子滤波的多源融合室内定位方法

室内定位技术作为社会各行业迫切需求的科技服务，尚无公认完善的解决方法。由于单一技术的定位方法不可消除其固有缺点，多种定位技术融合提升的方法是实现高精度室内定位的重要研究方向。本文面向日益复杂的室内环境，提出一种多源融合室内定位方法，将深度置信网络与 RSSI 指纹定位方法相结合实现粗略定位，同时使用行人航位测算技术完成行人航迹预测。然后运用粒子滤波器将粗略定位结果与预测的行人航迹信息相融合，提升了传统 RSSI 室内指纹定位技术的精确度与实时性。

Multi-Source Indoor Positioning Method Based on Particle Filter

Indoor positioning technology as the urgent demand of various industries of science and technology services, there is no recognized perfect solution. Because every positioning technology can not eliminate its inherent shortcomings, the integration of multiple positioning technologies is an important research direction to achieve high precision indoor positioning. Facing increasingly complex indoor environment, a multi-source indoor positioning method is proposed in the paper, which combines deep confidence network and RSSI fingerprint positioning method to achieve rough positioning. At the same time, pedestrian position measurement technology is used to complete pedestrian track prediction. Then, the particle filter is used to fuse the rough positioning results with the predicted pedestrian track information, which improves the accuracy and real-time performance of the traditional RSSI indoor fingerprint positioning technology.