一种信标辅助的北斗伪卫星CPD定位方法

doi:10.19665/j.issn1001-2400.20230409

西安电子科技大学学报 ›› 2024, Vol. 51 ›› Issue (2): 107-115.doi: 10.19665/j.issn1001-2400.20230409

一种信标辅助的北斗伪卫星CPD定位方法

张衡¹^,²^,³(), 蔚保国²^,³(), 潘树国¹()

1.东南大学仪器科学与工程学院,江苏南京 210096
2.中国电子科技集团公司第五十四研究所,河北石家庄 050081
3.卫星导航系统与装备技术国家重点实验室,河北石家庄 050081

收稿日期:2023-02-04 出版日期:2024-04-20 发布日期:2024-01-12
通讯作者: 潘树国(1981—),男,教授,E-mail:psg@seu.edu.cn
作者简介:张衡(1988—),男,工程师,E-mail:13582161539@163.com;
蔚保国(1966—),男,研究员,E-mail:yubg@sina.cn
基金资助:
国家重点研发计划(2021YFB3900800);国家重点研发计划(2021YFB3900801);国家重点研发计划(2021YFB3900802);河北省重点研发计划(20310901D)

Beacon-aided CPD indoor positioning method for the BeiDou pseudo-satellite

ZHANG Heng¹^,²^,³(), YU Baoguo²^,³(), PAN Shuguo¹()

1. School of Instrument Science and Engineering,Southeast University,Nanjing 210096,China
2. The 54th Research Institute of China Electronics Technology Group Corporation,Shijiazhang 050081,China
3. State Key Laboratory of Satellite Navigation System and Equipment Technology,Shijiazhang 050081,China

Received:2023-02-04 Online:2024-04-20 Published:2024-01-12

摘要/Abstract

摘要：

针对北斗伪卫星信号引入室内并在小尺度空间下提供高精度定位的难题,如何在顾及网络建设成本的基础上提升小尺度空间的定位时效性和定位精度是未来室内定位技术中需要解决的重要一环。此处充分结合室内环境下小尺度空间的空间特征,提出一种室内节点信标辅助的北斗伪卫星载波相位差定位方法。该方法首先将传统的大范围指纹构建问题转化为指纹节点的方式,在指纹图谱的基础上提出室内节点信标的概念,通过信标节点实现小尺度空间与周围空间的连接,并对以载噪比和载波相位为基础的信标特征谱构建与处理进行了分析;然后以室内节点信标为基础给出了基于载波相位差的位置估计过程,最后结合粒子群寻优算法提出一种顾及行人特征的位置与速度空间约束下的位置搜索算法。在真实环境下的试验结果表明,通过室内节点信标的辅助在室内环境可以实现动态定位精度优于30 cm、暂停态下的定位精度优于25 cm的定位效果。正常步速运动下算法与惯性导航定位精度相当,同时相比于惯性导航方式具有更宽松的运动姿态条件。在小尺度空间下算法具有更优的适用性。

关键词: 北斗伪卫星, 小尺度空间, 载波相位, 室内节点信标, 高精度定位

Abstract:

In order to solve the problem of high-precision positioning of the BeiDou pseudo-satellite signal in indoor small-scale space,how to save the cost of network construction on the basis of small-scale space to improve the timeliness and positioning accuracy of indoor positioning technology is an important link in the future.In this paper,a method of BeiDou pseudo-satellite carrier phase difference(CPD) localization assisted by indoor node beacons is proposed,which fully combines the characteristics of small-scale space in indoor environment.First,the problem of large-scale fingerprint construction is transformed into a fingerprint beacon,and the concept of indoor node beacon is proposed.The connection between small-scale space and surrounding space is realized by beacon nodes,and the construction and processing of the beacon characteristic spectrum based on the carrier-to-noise ratio(CN0) and carrier phase are analyzed.Then,based on the indoor node beacon,the process of position estimation based on CPD is presented.Finally,a location search algorithm considering the constraints of pedestrian location and velocity space is proposed based on particle swarm optimization(PSO).Experimental results in real environment show that the dynamic positioning accuracy of 30cm and the positioning accuracy of 25cm in a suspended state can be achieved by the indoor node beacon.Compared with inertial navigation,it has a more relaxed attitude condition and is suitable for high-precision positioning processing in small-scale space.The proposed algorithm has a better applicability in small-scale space.

Key words: BeiDou pseudo-satellite, small-scale space, carrier phase, indoor node beacon, high-precision positioning

中图分类号:

TN96

张衡, 蔚保国, 潘树国. 一种信标辅助的北斗伪卫星CPD定位方法[J]. 西安电子科技大学学报, 2024, 51(2): 107-115.

ZHANG Heng, YU Baoguo, PAN Shuguo. Beacon-aided CPD indoor positioning method for the BeiDou pseudo-satellite[J]. Journal of Xidian University, 2024, 51(2): 107-115.

图/表 12

图1

表1

室内信标节点特征图谱库"

参考点	X位置	Y位置	Z位置	特征数据集
$N d 1 r e f$	x₁	y₁	z₁	$R R a w R s s 1 1 R R a w R s s 1 2 … R v R a w R s s 1$
$N d 2 r e f$	x₂	y₂	z₂	$R R a w R s s 2 1 R R a w R s s 2 2 … R v R a w R s s 2$
︙	︙	︙	︙	︙
$N d N r e f$	x_N	y_N	z_N	$R R a w R s s N 1 R 2 R a w R s s N … R v R a w R s s N$

表1

表2

图2

图3

表3

图4

表4

图5

图6

图7

图8

参考文献 15

[1]	AHMED A U, ARABLOUEI R, HOOG F D, et al. Multi-Radio Data Fusion for Indoor Localization Using Bluetooth and WiFi[C]//International Conference on Pervasive and Embedded Computing and Communication Systems. Vienna:PECCS, 2019:13-24.
[2]	REN J, HUANG S, SONG W, et al. A Novel Indoor Positioning Algorithm for Wireless Sensor Network Based on Received Signal Strength Indicator Filtering and Improved Taylor Series Expansion[J]. Traitement du Signal, 2019,36,103-108.
[3]	SHARP I, YU K. Indoor WiFi Positioning,in Wireless Positioning:Principles and Practice[M]. Heidelberg:Springer, 2019:219-240.
[4]	YANG C, SHAO H R. WiFi-Based Indoor Positioning[J]. IEEE Communications Magazine, 2015,53:150-157.
[5]	VAZHENIN N A, VEITSEL A V, VEITSEL V V, et al. Position Determination of a Mobile Station Using Modified Wi-Fi Signals[S]. Mountain View: Google Patents, 2019.
[6]	WANG B, LIU X, YU B G, et al. An Improved WiFi Positioning Method Based on Fingerprint Clustering and Signal Weighted Euclidean Distance[J]. Sensors, 2019,19:2300.
[7]	LIU Y, TAO Z, LI X. High Efficiency WiFi Fingerprint Localization Based on Distance Costraints[C]//Proceedings of the ACM Turing Celebration Conference-China. New York: ACM, 2019:1-5.
[8]	ZHOU M, DOLGOV M, LIU Y, et al. WIFI/PDR Indoor Integrated Positioning System in a Multi-Floor Environment[J]. EAI Endorsed Transactions on Cognitive Communications, 2018, 4(14):155075.
[9]	GUO G, CHEN R, YE F, et al. Indoor Smartphone Localization:A Hybrid WiFi RTT-RSS Ranging Approach[J]. IEEE Access, 2019,7:176767-176781.
[10]	FUJII K, SAKAMOTO Y, WANG W, et al. Hyperbolic Positioning with Antenna Arrays and Multi-Channel Pseudolite for Indoor Localization[J]. Sensors, 2015,15:25157-25175.
[11]	黄璐, 蔚保国, 李宏生, 等. GNSS拒止环境下的伪卫星指纹定位方法[J]. 电子学报, 2022, 40(4):811-822.
	HUANG Lu, YU Baoguo, LI Hongsheng, et al. Pseudo-Satellite Fingerprint Localization Method in GNSS Rejection Environment[J]. Journal of Electronics, 2022, 40(4):811-822.
[12]	HUANG L, GAN X, YU B, et al. B.An Innovative Fingerprint Location Algorithm for Indoor Positioning Based on Array Pseudolite[J]. Sensors, 2019,19:4420.
[13]	ZHUANG H, PAN S. LSOS:An FG Position Method Based on Group Phase Ranging Ambiguity Estimation of BeiDou Pseudolite[J]. Remote Sensing. 2023, 15(7):1924.
[14]	王建, 张献州. 改进粒子群算法的GPS单历元模糊度搜索[J]. 测绘科学, 2013, 38(6):157-159.
	WANG Jian, ZHANG Xianzhou. GPS Single Epoch Ambiguity Search Based on Improved Particle Swarm Optimization Algorithm[J]. Science of Surveying and Mapping, 2013, 38(6):157-159.
[15]	翟彦蓉, 黄欢, 张申, 等. 改进粒子群优化算法在TDOA定位中的应用[J]. 传感器与微系统, 2013, 32(4):145-148.
	ZHAI Yanrong, HUANG Huan, ZHANG Shen, et al. Application of Improved Particle Swarm Optimization in TDOA Location[J]. Sensors and Microsystems, 2013, 32(4):145-148.

序号	人体活动分类	速度经验值
1	散步	1~5
2	快走	5~8
3	慢跑	8~10
4	快跑	>10

名称	P1	T1	T2	P2	P3	T3
X/m	538 272.078	538 271.88	538 267.61	538 261.912	538 262.32	538 268.489
Y/m	4 212 819.80	4 212 822.169	4 212 821.75	4 212 820.74	4 212 818.537	4 212 819.656

名称	位置点86		位置点78		位置点84
名称	X	Y	X	Y	X	Y
中值	538 272.57	4 212 820	538 273.24	4 212 820.11	538 273.08	4 212 819.43
RMSE	0.073	0.08	0.080 4	0.090 6	0.121	0.078

一种信标辅助的北斗伪卫星CPD定位方法

Beacon-aided CPD indoor positioning method for the BeiDou pseudo-satellite

RichHTML

PDF (PC)

赞

可视化

摘要/Abstract

引用本文

使用本文

图/表 12

参考文献 15

相关文章 15

Metrics

本文评价

推荐阅读 0

[1]	朱东霞, 贾洪杰, 黄龙霞. 非负拉格朗日松弛优化的子空间聚类算法[J]. 西安电子科技大学学报, 2024, 51(1): 100-113.
[2]	李雅宁,李宏生,蔚保国. 一种室内伪卫星混合指纹定位方法[J]. 西安电子科技大学学报, 2023, 50(5): 21-31.
[3]	郑安琪, 秦宁宁. 模糊空间下双标签指纹定位算法[J]. 西安电子科技大学学报, 2023, 50(2): 81-91.
[4]	秦宁宁,张臣臣. 模糊聚类下的接入点选择匹配定位算法[J]. 西安电子科技大学学报, 2022, 49(4): 71-81.
[5]	卞志昂,卢虎,史浩东. 运动参数辅助的无人机单站机会信号定位方法[J]. 西安电子科技大学学报, 2022, 49(3): 101-110.
[6]	秦宁宁,吴忆松,孙顺远. 一种双信标机制下的指纹库构建方法[J]. 西安电子科技大学学报, 2022, 49(3): 111-119.
[7]	国强,刘雪萌,周凯. 一种改进粒子滤波算法实现的多径参数估计[J]. 西安电子科技大学学报, 2022, 49(3): 120-128.
[8]	孙顺远,朱红洲,秦宁宁. 一种动态校正的信号双尺度近邻定位方法[J]. 西安电子科技大学学报, 2022, 49(3): 93-100.
[9]	秦宁宁,吴忆松,杨乐. 动态模糊匹配下的多元相似度定位算法[J]. 西安电子科技大学学报, 2021, 48(4): 27-35.
[10]	秦宁宁,王超. 时序测量信息触发的递归贝叶斯定位算法[J]. 西安电子科技大学学报, 2020, 47(4): 10-17.
[11]	王博远,刘学林,蔚保国,贾瑞才,甘兴利,黄璐. WiFi指纹定位中改进的加权k近邻算法[J]. 西安电子科技大学学报, 2019, 46(5): 41-47.
[12]	权源, 赵修斌, 庞春雷, 张豪, 王勇, 伍劭实. 改进型双频相关的整周模糊度单历元解算算法[J]. 西安电子科技大学学报, 2018, 45(6): 130-136.
[13]	路卫军;雷登云;于敦山. 一种适用于弱信号的混合差分位同步算法[J]. 西安电子科技大学学报, 2016, 43(3): 90-94+154.
[14]	高平;李小平;谢楷. GPS导航系统再入黑障现象地面再现实验[J]. 西安电子科技大学学报, 2016, 43(2): 77-82.
[15]	薛睿;魏强;徐锡超. 混沌序列测距码性能研究[J]. J4, 2015, 42(3): 103-108.