基于LoRa的地下停车场车辆定位系统设计

Design of LoRa-based Vehicle Positioning System Applied to Underground Parking Lots

利用LoRa在抗干扰、低功耗、低成本方面的优势,设计了一种基于LoRa的地下停车场车辆定位系统;针对地下停车场特殊通信环境,对非视距(Not Line of Sight,NLOS)时延模型进行分析;将排序算法与典型均值滤波算法相结合,改善典型均值滤波算法只能将脉冲噪声在滤波窗口内均摊而不能彻底消除的固有缺陷;通过参数拟合的方法,对地下停车场环境下规律性的NLOS时延和节点模块处理误差进行抑制;对三边定位算法进行优化,提高定位精度,避免无解情况的发生;在实际环境中进行测试,验证了系统的可行性。

With the advantages of LoRa in anti-interference,low power consumption and low cost,a vehicle positioning system based on LoRa for underground parking lots is designed.The NLOS delay model is analyzed in the special communication environment of underground parking lots.In this paper we combine the sorting algorithm with the typical mean filtering algorithm to overcome the downside of the typical mean filtering algorithm that the impulse noise can only be shared equally in the filter window and cannot be completely eliminated.Besides,we use the method of parameter fitting to suppress the regular NLOS delay in underground parking environment and processing the error of the label node module.We also optimize the Trilateration Method to improve the accuracy of positioning and avoid the situation of the occurrence of no solution.The system is applied in actual environment and the feasibility of the system is verified.