Robust UKF algorithm with motion constraint in BDS navigation

doi:10.11947/j.AGCS.2020.20200149

Abstract

Abstract: In a complex urban environment,navigation based on single BeiDou navigation satellite system (BDS) will be interfered by multipath (MP) and non-line-of-sight (NLOS) signals, which degrades the accuracy of positioning. In order to solve this problem, a robust unscented Kalman filter (UKF) with motion constraint is proposed. The algorithm constructs an equivalent weight function based on the innovation vector, which will overcome the problem of performance degradation of conventional robust method caused by inaccurate initial values of the position and receiver clock offset. In addition, the approximate moving direction and elevation of the carrier are used to further enhance the filtering solution. The actual on-board experiment results show that this method can effectively suppress the interference of MP and NLOS signals, and improve the accuracy of BDS navigation in urban environments.

Key words: BDS navigation, robust estimation, UKF filter, multipath, NLOS, motion constraint

CLC Number:

P228

YIN Xiao, CHAI Hongzhou, XIANG Minzhi, DU Zhenqiang. Robust UKF algorithm with motion constraint in BDS navigation[J]. Acta Geodaetica et Cartographica Sinica, 2020, 49(11): 1399-1406.

References

[1] JIANG Ziyi, GROVES P. GNSS NLOS and multipath error mitigation using advanced multi-constellation consistency checking with height aiding[C]//Proceedings of the 25th International Technical Meeting of the Satellite Division of the Institute of Navigation (ION GNSS 2012). Nashville, TN:ION, 2012:79-88.
[2] TOMINAGA T, KUBO N. Adaptive estimation of measurement noise to improve the performance of GNSS single point positioning in dense urban environment[J]. Journal of the Institute of Positioning Navigation and Timing of Japan, 2017, 8(1):1-8.
[3] 杨元喜. 自适应动态导航定位[M]. 北京:测绘出版社, 2006. YANG Yuanxi. Adaptive navigation and kinematic positioning[M]. Beijing:Surveying and Mapping Press, 2006.
[4] 杨玲, 沈云中, 楼立志. 基于中位参数初值的等价权抗差估计方法[J]. 测绘学报, 2011, 40(1):28-32. YANG Ling, SHEN Yunzhong, LOU Lizhi. Equivalent weight robust estimation method based on median parameter estimates[J]. Acta Geodaetica et Cartographica Sinica, 2011, 40(1):28-32.
[5] 刘韬, 徐爱功, 隋心, 等. 新息向量的抗差Kalman滤波方法及其在UWB室内导航中的应用[J]. 武汉大学学报(信息科学版), 2019, 44(2):233-239. LIU Tao, XU Aigong, SUI Xin, et al. An improved robust Kalman filtering method based on innovation and its application in UWB indoor navigation[J]. Geomatics and Information Science of Wuhan University, 2019, 44(2):233-239.
[6] 胡高歌, 高社生, 赵岩. 一种新的自适应UKF算法及其在组合导航中的应用[J]. 中国惯性技术学报, 2014, 22(3):357-361, 367. HU Gaoge, GAO Shesheng, ZHAO Yan. Novel adaptive UKF and its application in integrated navigation[J]. Journal of Chinese Inertial Technology, 2014, 22(3):357-361, 367.
[7] 刘光明, 徐帆江. 抗差自适应UKF算法在地基光学跟踪空间目标中的应用[J]. 系统工程与电子技术, 2018, 40(3):623-629. LIU Guangming, XU Fanjiang. Application of robustly adaptive UKF algorithm in ground-based bearings-only tracking for space targets[J]. Systems Engineering and Electronics, 2018, 40(3):623-629.
[8] SUZUKI T, KUBO N. N-LOS GNSS signal detection using fish-eye camera for vehicle navigation in urban environments[C]//Proceedings of the 27th International Technical Meetings of the Satellite Division of the Institute of Navigation. Tampa:Institute of Navigation, 2014:1897-1906.
[9] KBAYER N, SAHMOUDI M, CHAUMETTE E. Robust GNSS navigation in urban environments by bounding NLOS bias of GNSS pseudoranges using a 3D city model[C]//Proceedings of the 28th International Technical Meeting of the Satellite Division of the Institute of Navigation. Tampa:Institute of Navigation, 2015:2410-2420.
[10] 谭兴龙, 王坚, 李增科. 基于SVD的改进抗差UKF算法及在组合导航中的应用[J]. 控制与决策, 2014, 29(10):1744-1750. TAN Xinglong, WANG Jian, LI Zengke. SVD aided improved robust UKF algorithm and its application for integration navigation[J]. Control and Decision, 2014, 29(10):1744-1750.
[11] 李彦杰, 杨元喜, 何海波. 附加约束条件对GNSS/INS组合导航结果的影响分析[J]. 武汉大学学报(信息科学版), 2017, 42(9):1249-1255. LI Yanjie, YANG Yuanxi, HE Haibo. Effects analysis of constraints on GNSS/INS integrated navigation[J]. Geomatics and Information Science of Wuhan University, 2017, 42(9):1249-1255.
[12] 胡杰, 严勇杰, 王子卉. 基于速度约束与模糊自适应滤波的车载组合导航[J]. 兵工学报, 2020, 41(2):231-238. HU Jie, YAN Yongjie, WANG Zihui. Vehicle integrated navigation based on velocity constraint and fuzzy adaptive filtering[J]. Acta Armamentarii, 2020, 41(2):231-238.
[13] YANG Cheng, SHI Wenzhong, CHEN Wu. Robust M-M unscented Kalman filtering for GPS/IMU navigation[J]. Journal of Geodesy, 2019, 93(8):1093-1104.
[14] JIANG Chen, ZHANG Shubi, CAO Yizhi, et al. A robust fault detection algorithm for the GNSS/INS integrated navigation systems[J]. Journal of Geodesy and Geoinformation Science, 2020, 3(1):12-24.
[15] DISSANAYAKE G, SUKKARIEH S, NEBOT E, et al. The aiding of a low-cost strapdown inertial measurement unit using vehicle model constraints for land vehicle applications[J]. IEEE Transactions on Robotics and Automation, 2001, 17(5):731-747.
[16] 柴艳菊, 阳仁贵, 王海涛, 等. 附加运动约束提高GPS/INS导航参数估计精度[J]. 中国惯性技术学报, 2011, 19(1):28-32. CHAI Yanju, YANG Rengui, WANG Haitao, et al. Improving the navigation accuracy of GPS/INS by adding motion information constraints[J]. Journal of Chinese Inertial Technology, 2011, 19(1):28-32.
[17] YANG Jun, MA Jinfeng, LIU Xinning, et al. A height constrained adaptive Kalman filtering based on climbing motion model for GNSS positioning[J]. IEEE Sensors Journal, 2017, 17(21):7105-7113.
[18] GUO Fei, ZHANG Xiaohong, WANG Jinling. Timing group delay and differential code bias corrections for BeiDou positioning[J]. Journal of Geodesy, 2015, 89(5):427-445.
[19] JULIER S J, UHLMANN J K, DURRANT-WHYTE H F. A new approach for filtering nonlinear systems[C]//Proceedings of 1995 American Control Conference-ACC'95. Seattle, WA:IEEE, 1995:1628-1632
[20] JULIER S J, UHLMANN J K, DURRANT-WHYTE H F. A new method for the nonlinear transformation of means and covariances in filters and estimators[J]. IEEE Transactions on Automatic Control, 2000, 45(3):477-482.
[21] JULIER S J. The scaled unscented transformation[C]//Proceedings of 2002 American Control Conference. Anchorage, AK:IEEE, 2002:4555-4559.
[22] GROSS J, GU Yu, GURURAJAN S, et al. A comparison of extended Kalman filter, sigma-point Kalman filter, and particle filter in GPS/INS sensor fusion[C]//Proceedings of AIAA Guidance, Navigation, and Control Conference. Toronto:AIAA, 2010.
[23] CRASSIDIS J L, JUNKINS J L. Optimal estimation of dynamic systems[M]. 2nd ed. Boca Raton:Chapman & Hall/CRC, 2012.
[24] 胡丛玮, 刘大杰, 姚连璧. 带约束条件的自适应滤波及其在GPS定位中的应用[J]. 测绘学报, 2002, 31(S1):39-44. DOI:10.3321/j.issn:1001-1595.2002.z1.009. HU Congwei, LIU Dajie, YAO Lianbi. Adaptive filtering with constraint for GPS positioning[J]. Acta Geodaetica et Cartographica Sinica, 2002, 31(S1):39-44. DOI:10.3321/j.issn:1001-1595.2002.z1.009.
[25] YANG Yuanxi, GAO W, ZHANG X. Robust Kalman filtering with constraints:a case study for integrated navigation[J]. Journal of Geodesy, 2010, 84(6):373-381.
[26] SIMON D, CHIA T L. Kalman filtering with state equality constraints[J]. IEEE Transactions on Aerospace and Electronic Systems, 2002, 38(1):128-136.
[27] DING Weidong, WANG Jinling. Precise velocity estimation with a stand-alone GPS receiver[J]. The Journal of Navigation, 2011, 64(2):311-325.
[28] HONDA J, KAKUBARI Y, KOGA T. DOP simulation considering LOS/NLOS for aircraft positioning on airport surface[C]//Proceedings of 2015 IEEE Asia-Pacific Conference on Synthetic Aperture Radar (APSAR). Singapore:IEEE, 2015:773-776.