Navigation system development of the underwater vehicles using the GPS/INS sensor fusion

被引：2
作者：
机构：
[1] Department of Electrical and Computer Engineering, Pusan National University
[2] Department of Electronic Engineering, Pusan National University
来源：
Choi, Won-Suck | 1600年 / Springer Verlag卷 / 8917期
基金：
新加坡国家研究基金会;
关键词：
GPS/INS; IMU; Kalman Filter; Sensor Fusion;
D O I：
10.1007/978-3-319-13966-1_48
中图分类号：
学科分类号：
摘要：
Sensor fusion of GPS/INS using the Kalman filter design is proposed in this paper. GPS/INS data is utilized for estimating the position of AUV (Autonomous Underwater Vehicle) and Kalman filter simplifies the position estimation. The received GPS signals are stable most of the time, because they determine the position vector of the receiver which can receive microwaves transmitted from satellites (more in practice) with 24 hours’ orbitation in the GPS real-time Otherwise, A low data rate and the impact of the disturbance. These disadvantages the INS data (gyroscope sensor, accelerometer, magnetic compass) compensatation for the inaccuracy of the GPS data. The noise in the acceleration data from INS data is reduced by Kalman filter in this paper. So, the KF localization system applied to the surface of water is proposed in this paper and the system performance is confirmed by experiments. © Springer International Publishing Switzerland 2014.
引用
收藏
页码：491 / 497
页数：6
相关论文
共 7 条
  • [1] Kim K.J., Park C.G., Yu M.J., Park Y.B., A performance comparison of extended and unscented Kalman filters for INS/GPS tightly coupled approach, Journal of Control, Automation, and Systems Engineering, 12, 8, (2007)
  • [2] Eom H.S., Kim J.Y., Baek J.Y., Lee M.C., Reduction of Relative Position Error for DGPS Based Localization of AUV using LSM and Kalman Filter, Journal of the Korean Society for Precision Engineering, 27, 10, pp. 52-60
  • [3] Schmidt G.T., INS/GPS technology trends, NATO Research and Technology Organization, pp. 1-16, (2009)
  • [4] Lee J.H., Kim H.S., A Study of High Precision Position Estimator Using GPS/INS Sensor Fusion, Journal of the Institute of Electronics Engineers of Korea, 49, 11, (2012)
  • [5] Hwang S.Y., Lee J.M., Estimation of attitude and position of moving objects using multifiltered inertial navigation system, The Institute of Electronics Engineers of Korea, 60, 12, pp. 2383-2396, (2011)
  • [6] Kim T.G., Choi H.T., Lee Y.J., Ko N.Y., Localization for pose of an Underwater Robot Using EKF Method, Summer Scholarship Conference of the Institute of Electronics and Information Engineers, (2013)
  • [7] Rigaud V., March L., Michel J.L., Borot P., Sensor fusion for AUV localization, The Institute of Electrical and Electronics Engineers, (1990)
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