摘要
针对智慧仓储场景中多径/非视距无线传输(Non Line of Sight,NLOS)无线传输干扰导致定位精度低、终端续航短、部署成本高三大瓶颈,提出窄带物联网(Narrow Band Internet of Things,NB-IoT)与超宽带(Ultra Wide Band,UWB)融合的定位算法改进方案。首先,构建时延-能量联合约束的加权最小二乘(Weighted Least Squares,WLS)与扩展卡尔曼滤波(Extended Kalman Filter,EKF)联合模型,引入信道状态信息(Channel State Information,CSI)能量熵权重与动态遮挡因子抑制干扰,提升复杂环境下的定位稳定性;其次,设计加权信号质量评估+自适应同步周期的动态功耗管理策略,有效减少模式切换振荡与无效能耗;最后,搭建射频(Radio Frequency,RF)+压电+光伏多源能量回收架构,结合动态电压调整(Dynamic Voltage Scaling,DVS)优化功率分配,延长终端续航。仿真验证结果表明:在金属货架区、NLOS货物堆放区、自动导向车(Automated Guided Vehicle,AGV)动态通道区,改进方案(粒子滤波优化版)的平均定位误差分别降至0.30、0.40、0.28 m,较传统UWB-飞行时间(Time Of Flight,TOF)方案降低75%~81%;终端平均功耗降低42%,启用多源能量回收架构后续航延长至60个月;以100 000 m2仓储场景测算,部署成本较NB-IoT+UWB基础融合方案降低30%。该方案适配常规及冷链、化工等极端仓储场景,为智慧仓储定位的工程化落地提供了技术支撑。
In the context of smart warehousing,the interference caused by multi-path/Non-Line of Sight(NLOS)wireless transmission poses three bottlenecks:low positioning accuracy,short terminal battery life,and high deployment costs.This paper proposes an improved positioning algorithm based on the integration of Narrow Band Internet of Things(NB-IoT)and Ultra Wide Band(UWB).Firstly,a joint model of Weighted Least Squares(WLS)and Extended Kalman Filter(EKF)under joint latency-energy constraints is constructed.Channel State Information(CSI)energy entropy weight and dynamic occlusion factor are introduced to suppress interference and enhance positioning stability in complex environments.Secondly,a dynamic power management strategy combining weighted signal quality evaluation and adaptive synchronization period is designed to effectively reduce mode switching oscillation and ineffective energy consumption.Finally,a multi-source energy recovery architecture consisting of Radio Frequency(RF),piezoelectric,and photovoltaic components is established.Dynamic Voltage Scaling(DVS)is incorporated to optimize power allocation and extend terminal battery life.Simulation results show that in metal shelf areas,NLOS cargo stacking areas,and automated guided vehicle(AGV)dynamic channel areas,the average positioning error of the improved scheme(particle filter optimized version)is reduced to 0.30,0.40,0.28 m,respectively,which is 75%~81%lower than the traditional UWB-Time Of Flight(TOF)scheme.The average terminal power consumption is reduced by 42%,and the battery life is extended to 60 months with the multi-source energy recovery architecture enabled.Based on a 100000 m²warehouse scenario,the deployment cost is reduced by 30%compared to the basic integration of NB-IoT and UWB.This scheme is suitable for conventional warehousing as well as extreme warehousing scenarios such as cold chain and chemical warehousing,providing technical support for the engineering implementation of smart warehousing positioning.
作者
崔运辉
CUI Yunhui(Renmin University of China,Beijing 102208,China)
出处
《智能物联技术》
2026年第2期119-124,共6页
Technology of Io T& AI
