RFID旋转天线中的椭圆模型室内定位算法
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摘要
传统的基于RSSI测距的RFID室内定位系统需要多台天线同时进行测量,使得定位系统部署成本昂贵。而目前只使用一个天线的RFID旋转天线定位方法由于需要测量最大信号强度的角度,需要长期搜索标签,导致系统无法长期稳定工作。为了解决上述问题,提出在天线旋转过程中,获得不同特定角度的等信号强度轨迹,再通过遍历方法求两个椭圆模型的交点,实现定位。最后将该算法在硬件装置上进行了实验,结果表明平均定位误差达到0.754 m,与传统RSSI定位算法相比可以减少36.19%左右的硬件部署成本,同时解决了读写器容易发热的问题。
The traditional RFID indoor positioning system based on the distance measurement of RSSI needs to use multiple antennas simultaneously, which makes the cost of RFID positioning system expensive. However, the RFID rotating antenna positioning method using only one antenna needs to long-term search for a tag to measure the maximum signal strength, which causes that the system is unable to operate stably for a long period of time. In order to solve the problem,the system obtains the equal signal strength of different angles by rotating RFID antenna. Then the intersection points of two elliptical models are obtained by traversal methods. In this way the positioning function is achieved. At last the performance of the proposed algorithm is tested on the hardware device. The result indicates that the error of position is 0.754 m. Compared with the traditional RSSI positioning algorithm, the cost of proposed RFID indoor positioning system can be reduced about 36.19%. At the same time, the problem of heating easily of the reader is solved.
The traditional RFID indoor positioning system based on the distance measurement of RSSI needs to use multiple antennas simultaneously, which makes the cost of RFID positioning system expensive. However, the RFID rotating antenna positioning method using only one antenna needs to long-term search for a tag to measure the maximum signal strength, which causes that the system is unable to operate stably for a long period of time. In order to solve the problem,the system obtains the equal signal strength of different angles by rotating RFID antenna. Then the intersection points of two elliptical models are obtained by traversal methods. In this way the positioning function is achieved. At last the performance of the proposed algorithm is tested on the hardware device. The result indicates that the error of position is 0.754 m. Compared with the traditional RSSI positioning algorithm, the cost of proposed RFID indoor positioning system can be reduced about 36.19%. At the same time, the problem of heating easily of the reader is solved.
引文
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[14]鲍天翼.基于旋转天线的RFID定位算法和仿真分析[J].电子世界,2016,492(6):68-69.
[15]李珣,刘丽,洪良,等.移动机器人室内无源RFID定位方法及实现[J].计算机工程与应用,2017,53(16):230-236.
[16]陈增强,国峰,张青.基于模糊神经网络建模的RFID室内定位算法[J].系统科学与数学,2014,34(12):1438-1450.
[17]郭国法,卢运栓,张开生.适用于车间巡检定位的改进RFID定位算法[J].实验室研究与探索,2016,35(12):29-33.
[2]Deyle T,Nguyen H,Reynolds M,et al.RF vision:RFIDreceive signal strength indicator(RSSI)images for sensor fusion and mobile manipulation[C]//IEEE/RSJ International Conference on Intelligent Robots and Systems,St.Louis,MO,USA,2009:5553-5560.
[3]李丽娜,马俊,徐攀峰,等.RFID室内定位技术研究综述[J].计算机应用与软件,2015,32(9):1-3.
[4]Liu H,Darabi H,Banerjee P,et.al.Survey of wireless indoor positioning techniques and systems[J].IEEE Transactions on Systems Man and Cybernetics Part C-Applications and Reviews,2007,37(6):1067-1080.
[5]Shao S,Burkholder R J.Item-level RFID tag location sensing utilizing reader antenna spatial diversity[J].IEEESensors Journal,2013,13(10):3767-3774.
[6]Ko C H.RFID 3D location sensing algorithms[J].Automation in Construction,2010,19(5):588-595.
[7]Huang C H,Lee L H,Ho C C,et al.Real-Time RFIDindoor positioning system based on Kalman-filter drift removal and Heron-Bilateration location estimation[J].IEEE Transactions on Instrumentation and Measurement,2015,64(3):728-739.
[8]袁晓峰,陈颀.一种基于RFID的定位方法[J].无线电通信技术,2016,42(6):81-85.
[9]童汇琛.基于多普勒效应的RFID室内定位技术研究与实现[D].上海:上海交通大学,2014.
[10]Liu C,Cheng Z,Zhang Y,et al.An indoor positioning system based on RFID with rotating antenna and passive tags[C]//IEEE International Conference on Robotics and Automation Engineering,Shanghai,China,2017:455-459.
[11]刘禹,关强.RFID系统测试与应用实务[M].北京:电子工业出版社,2010.
[12]陈宇琦.RFID测距的研究与应用[D].广州:广东工业大学,2012.
[13]陈晨.基于RFID的定位算法研究[D].太原:太原科技大学,2014.
[14]鲍天翼.基于旋转天线的RFID定位算法和仿真分析[J].电子世界,2016,492(6):68-69.
[15]李珣,刘丽,洪良,等.移动机器人室内无源RFID定位方法及实现[J].计算机工程与应用,2017,53(16):230-236.
[16]陈增强,国峰,张青.基于模糊神经网络建模的RFID室内定位算法[J].系统科学与数学,2014,34(12):1438-1450.
[17]郭国法,卢运栓,张开生.适用于车间巡检定位的改进RFID定位算法[J].实验室研究与探索,2016,35(12):29-33.
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