A New GPS/RFID Integration Algorithm Based on Iterated Reduced Sigma Point Kalman Filter for Vehicle Navigation

被引：0
|
作者：
Peng, Jing [1 ,2 ]
Wu, Falin [3 ]
Zhu, Ming [1 ]
Zhang, Kefei [1 ]
Wang, Feixue [2 ]
机构：
[1] RMIT Univ, Sch Math & Geospatial Sci, Melbourne, Vic, Australia
[2] Natl Univ Def Technol, Sch Elect Sci & Engn, Changsha, Hunan, Peoples R China
[3] Beijing Univ Aeronaut & Astronaut, Sch Instrument & Opto Elect Engn, Beijing, Peoples R China
来源：
PROCEEDINGS OF THE 22ND INTERNATIONAL TECHNICAL MEETING OF THE SATELLITE DIVISION OF THE INSTITUTE OF NAVIGATION (ION GNSS 2009) | 2009年
关键词：
D O I：
暂无
中图分类号：
TP18 [人工智能理论];
学科分类号：
081104 ; 0812 ; 0835 ; 1405 ;
摘要：
To improve the accuracy, reliability and availability of GPS navigation service in urban area, a new GPS/RFID integration method for vehicle navigation is proposed in this paper. In the proposed method, a RFID system is used to aid GPS to achieve a high accuracy positioning via the Received Signal Strength (RSS) measurements and sparse location information of RFID tags. An iterated Reduced Sigma Point Kalman Filter is proposed as a predominant filter for the GPS/RFID integration as well. The results of field experiment show that both accuracy and availability of positioning can be improved by this low-cost GPS/RFID integration method significantly.
引用
收藏
页码：803 / 810
页数：8
相关论文
共 50 条
  • [21] GPS/INS navigation based on adaptive finite impulse response-Kalman filter algorithm
    Jin B.
    Li J.
    Zhu D.
    Guo J.
    Su B.
    Nongye Gongcheng Xuebao/Transactions of the Chinese Society of Agricultural Engineering, 2019, 35 (03): : 75 - 81
  • [22] A computationally efficient Kalman filter-based RAIM algorithm for aircraft navigation with GPS and NavIC
    Bhattacharyya S.
    Measurement Science and Technology, 2023, 34 (12)
  • [23] The INS/GPS integrated navigation based on autonomous underwater vehicle using modified extended Kalman filter
    Hou, Yudong
    Cheng, Liang
    Wang, Qing
    Li, Jiangxiong
    Ke, Yinglin
    TRANSACTIONS OF THE INSTITUTE OF MEASUREMENT AND CONTROL, 2024,
  • [24] Iterated Square Root Unscented Kalman Filter and Its Application in Deep Sea Vehicle Navigation
    Wang, Xiulian
    Liu, Kaizhou
    Lin, Yanping
    Liu, Ben
    Zhao, Yang
    Cui, Shengguo
    Feng, Xisheng
    2015 27TH CHINESE CONTROL AND DECISION CONFERENCE (CCDC), 2015, : 4920 - 4925
  • [25] Research on relative navigation method based on INS/Vision using sigma-point Kalman filter
    Cui, Nai-Gang
    Wang, Xiao-Gang
    Guo, Ji-Feng
    Yuhang Xuebao/Journal of Astronautics, 2009, 30 (06): : 2220 - 2225
  • [26] Ultratight GPS/Reduced-IMU Integration for Land Vehicle Navigation
    Sun, Debo
    Petovello, Mark G.
    Cannon, M. Elizabeth
    IEEE TRANSACTIONS ON AEROSPACE AND ELECTRONIC SYSTEMS, 2013, 49 (03) : 1781 - 1791
  • [27] A Integrated Navigation Algorithm Based on Distributed Kalman Filter
    Zhang, Yonggang
    Dang, Yuanfang
    Li, Ning
    Huang, Yulong
    2015 IEEE INTERNATIONAL CONFERENCE ON INFORMATION AND AUTOMATION, 2015, : 2132 - 2135
  • [28] Predictive Iterated Kalman Filter for INS/GPS Integration and Its Application to SAR Motion Compensation
    Fang, Jiancheng
    Gong, Xiaolin
    IEEE TRANSACTIONS ON INSTRUMENTATION AND MEASUREMENT, 2010, 59 (04) : 909 - 915
  • [29] Initial alignment of Inertial Navigation System based on a predictive iterated Kalman filter
    Cheng, Guanghao
    Cao, Songyin
    Guo, Lei
    Chen, Wenhua
    2018 37TH CHINESE CONTROL CONFERENCE (CCC), 2018, : 4655 - 4660
  • [30] GPS and IMU Integration on an autonomous vehicle using Kalman filter (LabView Tool)
    Dhongade, Amol P.
    Khandekar, M. A.
    PROCEEDINGS OF THE 2019 INTERNATIONAL CONFERENCE ON INTELLIGENT COMPUTING AND CONTROL SYSTEMS (ICCS), 2019, : 1122 - 1125
12345