Influence of B1 code correlation loop for vector tracking structures under complicated environment

doi:10.21629/JSEE.2019.06.01

Journal of Systems Engineering and Electronics ›› 2019, Vol. 30 ›› Issue (6): 1053-1063.doi: 10.21629/JSEE.2019.06.01

• Electronics Technology • Next Articles

Influence of B1 code correlation loop for vector tracking structures under complicated environment

Qian WANG^1,*(), Feng SHANG¹(), Liming DU²(), Wenjia ZHOU¹()

¹ School of Electronic Engineering, Xi'an University of Posts and Telecommunications, Xi'an 710121, China
² Qingdao Huatong Intelligent Research Institute, Qingdao 266111, China

Received:2018-11-06 Online:2019-12-20 Published:2019-12-25
Contact: Qian WANG E-mail:wqaloha@139.com;shangfeng@xupt.edu.cn;xinde130@163.com;zhouwj1986@163.com
About author:WANG Qian was born in 1978. He received his Ph.D. degree in Computer Science Department of Beihang University. He is a senior researcher in Xi’an University of Posts and Telecommunications. His research interests include the design of algo- rithms for signal tracking, integrated navigation and precision positioning. E-mail: wqaloha@139.com|SHANG Feng was born in 1966. He received his M.S. degree in electromagnetic field and microwave technology of Xidian University. He is a professor in Xi'an University of Posts and Telecommunications. His research interests include the antenna theory and engineering, and radio frequency signal processing. E-mail: shangfeng@xupt.edu.cn|DU Liming was born in 1978. He received his M.S. degree in communication and information system of Nanjing University of Aeronautics and Astronautics. He is a senior engineer at Qingdao Huatong Intelligent Research Institute. He is mainly engaged in the research of digital signal processing and satellites navigation. E-mail: xinde130@163.com|ZHOU Wenjia was born in 1986. She received her Ph.D. degree in control science and engineering, Northwestern Polytechnical University. She is a lecturer in Xi'an University of Posts and Telecommunications. Her research interests include microwave delay technology and microwave devices. E-mail: zhouwj1986@163.com
Supported by:
This work was supported by the National Natural Science Fundation of China(41474027);This work was supported by the National Natural Science Fundation of China (41474027)

Abstract

Abstract:

The code tracking loop is a key component for user positioning. The pseudorange information of BeiDou B1 signals has been fused and changed for vector tracking, so a correlation output model for complex scenarios is designed to prevent the propagation of error and valuate the signal performance. The relevant software and hardware factors that affect the output are analyzed. A single channel time-division multiplexing (TDM) method for multicorrelation data extraction is proposed. Statistical characteristics of the correlation output data for both vector and scalar structures are evaluated. Simulation results show that correlation outputs for both structures follow normal or Chi-squared distributions in normal conditions, and the Gamma distribution in harsh conditions. It is shown that a tracking model based on the multi-channel fusion hardly changes the probability distribution of the correlation output in the normal case, but it reduces the ranging error of the code loop, and hence the tracking ability of the code loop for weak signals is improved. Furthermore, vector tracking changes the pseudorange characteristics of channels anytime, and affects the mutual correlation outputs of the code loops in the abnormal case. This study provides a basis for the subsequent design of autonomous integrity algorithms for vector tracking.

Key words: vector tracking, signal quality, code correlation, pseudorange error, scalar tracking, correlation peak loss

Qian WANG, Feng SHANG, Liming DU, Wenjia ZHOU. Influence of B1 code correlation loop for vector tracking structures under complicated environment[J]. Journal of Systems Engineering and Electronics, 2019, 30(6): 1053-1063.

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1	MONTENBRUCK O, HAUSCHILD A, STEIGENBERGER P, et al. Initial assessment of the COMPASS/BeiDou-2 regional navigation satellite system. GPS Solution, 2013, 17 (2): 211- 222.
2	YANG Y X, LI J L, WANG A B, et al. Preliminary assessment of the navigation and positioning performance of BeiDou regional navigation satellite system. Science China Earth Sciences, 2014, 57 (1): 144- 152.
3	DOU S H, KUANG C L, ZHOU Y Z, et al. Analysis of signal quality and navigation performance for Beidou system. Proc. of the 8th China Satellite Navigation Conference, 2017, 5, 671- 681.
4	HE H B, LI J L, YANG Y X, et al. Performance assessment of single-and dual-frequency BeiDou/GPS single-epoch kinematic positioning. GPS Solution, 2014, 18 (3): 393- 403.
5	LIU T H. Data research and analysis on B1 signal of BDS. Shanghai: Shanghai Jiao Tong University, 2013. (in Chinese)
6	KIM S H, PARK K D. Improving DGPS accuracy by consi-linebreak dering the correlation of pseudorange correction and satellite elevation angle. The Journal of Navigation, 2017, 70 (6): 1267- 1275. doi: 10.1017/S0373463317000297
7	SENNOTT J W. A flexible GPS software development system and timing analyzer for present and future microprocessors. Navigation, 1984, 31 (2): 84- 95. doi: 10.1002/j.2161-4296.1984.tb00864.x
8	LIU J, CUI X W, LU M Q, et al. Vector tracking loops in GNSS receivers for dynamic weak signals. Journal of Systems Engineering and Electronics, 2013, 24 (3): 349- 364. doi: 10.1109/JSEE.2013.00044
9	ZHAO S H, LU M Q, FENG Z M. GNSS vector lock loop based on adaptive Kalman filter. Journal of Harbin Institute of Technology, 2012, 44 (7): 139- 143.
10	CHEN X Y, WANG X Y, XU Y. Performance enhancement for a GPS vector-tracking loop utilizing an adaptive iterated extended Kalman filter. Sensors, 2014, 14 (12): 23630- 23649. doi: 10.3390/s141223630
11	LASHLEY M, BEVLY D, PETOVELLO M G. What are vector tracking loops and what are their benefits and drawbacks?. GNSS Solutions Column Inside GNSS, 2009, 4 (3): 16- 21.
12	LIU D. Research on GPS signal monitoring technology. Beijing: Beihang University, 2012. (in Chinese)
13	FENG X C, FU Y H, GONG L, et al. Detect technique and test analysis on navigation signal code correlation peak. Proc. of the 6th China Satellite Navigation Conference, 2015, 5, 517- 528.
14	JIANG H, WANG H T, WANG Z M, et al. Real-time monitoring for BDS signal-in-space anomalies using ground observation data. Sensors, 2018, 18 (6): 1- 17. doi: 10.1109/JSEN.2018.2792888
15	YANG J, YANG Y K, LI J S, et al. A novel satellite-equipped receiver for autonomous monitoring of GNSS navi-linebreak gation signal quality. Science China Technological Sciences, 2016, 59 (7): 1137- 1146. doi: 10.1007/s11431-016-6032-3
16	ZHU L, ZHEN J, ZHAO X, et al. Real IF signal quality ana-linebreak lysis using general GNSS software receiver. ZENG Q A. Eds. Wireless communications, networking and applications. New Delhi: Springer, 2016: 837-849.
17	WANG J. Research on GNSS anti-spoofing technology by using acquisition module. Beijing, China: Tsinghua University, 2014. (in Chinese)
18	LI C Q. The characteristics of PN code correlation and its applications under high dynamics. Changsha, China: National University of Defense Technology, 2005. (in Chinese)
19	PANY T, MOON S W, IRSIGLER M, et al. Performance assessment of an under sampling SWC receiver for simulated high-bandwidth GPS/Galileo signals and real signals. Proc. of the International Technical Meeting of the Satellite Division of the Institute of Navigation, 2003: 103-116.
20	WANG Q, HU C B. Loop design of numerically controlled oscillator driven by multichannel united data. Journal of Chinese Inertial Technology, 2015, 23 (4): 483- 488.
21	WANG Q, CUI X, LIU J, et al. Quantitative analysis of the performance of vector tracking algorithms. High Technology Letters, 2017, 23 (3): 238- 244.
22	CHANG K J. Optimality criteria methods using K-S function. Structural Optimization, 1992, 4, 213- 217. doi: 10.1007/BF01742747
23	XIAN D Y, FAN P R, WU H L. Test system for BDS user terminal based on RF replay apparatus. Proc. of the 7th China Satellite Navigation Conference, 2016, 5, 413- 422.

Chl-1/dB-Hz>	Chl-[2:12]/dB-Hz	$\Delta \tau$Chl-1/m	$\Delta dB$Chl-1
20	45	2.85	9.62E-6
25	45	2.15	7.24E-6
30	45	1.52	5.12E-6
35	45	1.32	4.44E-6

Symbol	Explanation	Number setting	Unit
S_a	Power spectral density (PSD) of processing noise for signal amplitude	10E-3	(V/s)²/Hz
S_car	PSD of processing noise for signal carrier	$2\cdot(4{\rm{\pi }} ^2 /3)\cdot$10E-3	$\rm(rad / s)^2 / Hz$
S_f	Coefficient-1 of variance for Allan	2E-19·c2/2	(m/s)²/Hz
S_g	Coefficient-2 of variance for Allan	2E-20·c²·2π²	(m/s²)²/Hz

Setting (CNR[1:11]/Dyn.		CNR[1]:25 /CNR[2-11]:45/0.1g
Code bias		0	0.125	0.25
	Scalar-Chl[1]	3.423 9	3.303 4	3.237 1
	Scalar-Chl[2]	21.062 0	18.580 6	11.182 9
Symmetry	Vector-Chl[1]	3.401 0	3.272 6	3.260 1
	Vector-Chl[2]	21.119 5	18.713 9	11.268 9
	Scalar-Chl[1]	23.523 2(TSR:89.9%)
CNR	Vector-Chl[1]	24.119 4(TSR:95.7%)
estimation	Scalar-Chl[2]	44.840 4
	Vector-Chl[2]	44.992 6

CNR[1:11]/Dyn.		45/8 g			45/0.1 g
Code bias		0	0.125	0.25	0	0.125	0.25
Symmetry	Scalar	19.051 3	16.829 1	10.182 3	21.031 6	18.546 5	11.106 1
Symmetry	Vector	19.989 7	17.722 2	11.021 5	21.086 5	18.691 9	11.221 1
CNR	Scalar		44.303 9			44.813 6
estimation	Vector		44.650 1			44.978 2

CNR[1:11]/Dyn.		35/4g			30/0.1g
Code bias		0	0.125	0.25	0	0.125	0.25
Symmetry	Scalar	6.407 2	5.747 1	4.276 8	4.547 2	4.284 2	3.737 3
Symmetry	Vector	6.905 8	6.301 6	4.470 0	4.547 6	4.291 9	3.715 3
CNR	Scalar		34.191 4			29.501 1
estimation	Vector		34.587 3			29.948 6

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[2]	Qian WANG, Chuanding ZHANG, Deyong XIAN. Multi-channel signal parameters joint optimization for GNSS terminals [J]. Journal of Systems Engineering and Electronics, 2018, 29(1): 39-47.

Influence of B1 code correlation loop for vector tracking structures under complicated environment

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