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基于多模差分融合的高速车辆定位算法
引用本文:姚锟,任维政.基于多模差分融合的高速车辆定位算法[J].应用声学,2015,23(7):2464-2466.
作者姓名:姚锟  任维政
作者单位:北京邮电大学
摘    要:针对车辆高速运动下定位延时大、精度低、稳定性差的问题,发挥GPS、RSSI和INS三种定位模式的各自优势,将GPS差分校准算法与RSSI测距相结合求解横坐标,将RSSI测距与INS惯导迭代算法相结合求解纵坐标,提出了一种适合高速运动车辆的多模差分融合精确定位算法。以四车道的高速路为场景进行了仿真实验,当车速为70km/h时,跟踪误差<1m,定位延时<0.2s。实验结果表明,该算法可实现车身级和车道级定位,在精确交通诱导、车辆防撞等智能交通领域具有应用前景和推广价值。

关 键 词:无线传感器网络  高速运动定位  RSSI  GPS  INS

High-speed Vehicle Localization Algorithm Based on Multi-mode Differential Fusion
Abstract:Aim to solve the problems of big delay, low accuracy and poor stability of localization under the high-speed situation of vehicles, play all the advantages of three positioning mode, including GPS, RSSI and INS system. We combine GPS differential algorithm with RSSI ranging together to get abscissa, and fuse RSSI ranging and INS iterative algorithm to get ordinate, propose a multi-mode differential fusion precise localization algorithm for high-speed vehicles. During the simulation experiments based on a four-lane highway scene, the tracking error is less than 1m, localization delay is less than 0.2s when the speed is 70km/h. Experimental results show that the algorithm can achieve lane-level localization accuracy, there are broad promotion prospects in the field of precise intelligent transportation and Vehicle Collision Avoidance System.
Keywords:Rapid localization algorithm  Differential fusion  Internet of Vehicles  WSN network  Real-time guidance
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