Reflection plane parameters estimation with GNSS multipath signal
-
摘要: 全球卫星导航系统（GNSS）多径信号广泛存在于城市峡谷等复杂导航定位场景中. 多径信号在干扰GNSS接收机并造成系统定位精度下降的同时，也为接收机提供了周边反射面环境信息. 在码相位延迟幅度联合跟踪算法（CADLL）实现GNSS多径信号感知和特征参数提取的基础上，设计实现了基于粒子滤波的反射面参数估计算法. 该算法可以在GNSS多径环境中增强接收机的环境感知能力，相关环境信息可应用于场景感知、避障、路径规划和定位增强等领域. 静态环境下进行GNSS多径信号采集和算法测试，实验结果表明该算法能够有效估计反射面位置参数，反射面方位角均方根误差（RMSE）小于10°，反射面俯仰角RMSE小于5°，反射面距离RMSE小于10 m.
-
关键词:
- 环境感知 /
- 全球卫星导航系统（GNSS） /
- 粒子滤波 /
- 多径信号处理 /
- 反射面定位
Abstract: GNSS multipath signals widely exist in complex navigation and positioning scenarios such as urban canyons. Although the multipath signal interferes GNSS receiver and reduces positioning accuracy, it provides environment information around the receiver. Based on the coupled amplitude delay locked loops algorithm (CADLL) which senses GNSS multipath signals and extracts feature parameters, a particle filter-based reflection plane parameters estimation algorithm is designed and implemented. The algorithm can enhance the receiver's environment perception in the GNSS multipath environment, the corresponding information can be applied to the fields of scene perception, collision avoidance, path planning and positioning augmentation. GNSS multipath signal recording and algorithm testing are carried out in a static environment. The experimental results show that the algorithm can effectively estimate the position parameters of the reflecting plane. The root mean square error (RMSE) of the azimuth angle of the reflection plane is less than 10 degrees, the RMSE of the elevation angle is less than 5 degrees, and the RMSE of the distance is less than 10 meters. -
表 1 天台标定实验GNSS信号及接收机参数
项目 参数 信号频点 BDS B1I PRN 20 卫星轨道 MEO 卫星方位角 61.1° 卫星俯仰角 16.8° 接收机经度坐标 31.0250337°E 接收机纬度坐标 121.4397454°N 接收机速度 0 m/s 
下载: 导出CSV
表 3 陆家嘴市区环境GNSS信号及接收机参数
项目 参数 信号频点 BDS B1I PRN 06 卫星轨道 IGSO 卫星方位角 173.9° 卫星俯仰角 41.8° 接收机经度坐标 31.2354768°E 接收机纬度坐标 121.4978325°N 接收机速度 0 m/s
下载: 导出CSV
-
[1] 李治泽. 基于激光雷达的四旋翼飞行器SPLAM研究与实现[D]. 长沙: 国防科技大学, 2017. [2] 蔡雄风. 城市综合环境无人驾驶车辆导航方法研究[D].上海: 上海交通大学, 2017. [3] 万玮, 李黄, 洪阳, 等. GNSS-R遥感观测模式及陆面应用[J]. 遥感学报, 2015, 19(6): 882-893. [4] 陈锐志, 王磊, 李德仁, 等. 导航与遥感技术融合综述[J]. 测绘学报, 2019, 48(12): 1507-1522. [5] GROVES P, JIANG Z Y, RUDI M, et al. A portfolio approach to NLOS and multipath mitigation in dense urban areas[C/OL]//Proceedings of the 26th International Technical Meeting of the Satellite Division of The Institute of Navigation, 2013: 3231-3247. https://www.ion.org/publications/abstract.cfm?articleID=11264. [6] YEDYKONDALU K, SARMA ACHANTA D, SATYA V. Estimation and mitigation of GPS multipath interference using adaotive filtering[J]. Progress in electromagnetics research m, 2011(21): 133-148. DOI: 10.2528/PIERM11080811. [7] VAN NEE R, TOWNSEND B, FENTON P, et al. L1 carrier phase multipath error reduction using MEDLL technology[C/OL]//Proceedings of the 8th International Technical Meeting of the Satellite Division of The Institute of Navigation (ION GPS), 1995: 1539-1544. https://www.ion.org/publications/abstract.cfm?articleID=2407. [8] CHEN X, DOVIS F, PINI M. An innovative multipath mitigation method using coupled amplitude delay locked loops in GNSS receivers[C]//Proceedings of IEEE/ION PLANS 2010, Indian, 2010: 1118-1126. DOI: 10.1109/PLANS.2010.5507230. [9] ARULAMPALAM M S, MASKELL S, GORDON N, et al. A tutorial on particle filters for online nonlinear/non-Gaussian Bayesian tracking[J]. IEEE transactions on signal processing, 2002, 50(2): 174-188. DOI: 10.1109/78.978374. [10] CHEN Z S. Bayesian filtering: from Kalman filters to particle filters, and beyond[J]. Statistics, 2003, 182(1): 1-69. DOI: 10.1080/02331880309257. [11] 秦永元. 惯性导航[M]. 北京: 科学出版社, 2014. -
点击查看大图
图(7) / 表(3)
计量
- 文章访问数: 591
- HTML全文浏览量: 360
- PDF下载量: 53
- 被引次数: 0
