Next Article in Journal
Aircraft Detection in High-Resolution SAR Images Based on a Gradient Textural Saliency Map
Previous Article in Journal
Optimization and Control of Cyber-Physical Vehicle Systems
Article Menu

Export Article

Open AccessArticle
Sensors 2015, 15(9), 23050-23070; doi:10.3390/s150923050

Deep Coupled Integration of CSAC and GNSS for Robust PNT

1,2,* , 1,2
,
1,2
,
1,2
and
1,2
1
Department of Precision Instrument, Tsinghua University, Beijing 100084, China
2
State Key Laboratory of Precision Measurement Technology and Instruments, Tsinghua University, Beijing 100084, China
*
Author to whom correspondence should be addressed.
Academic Editor: Vittorio M. N. Passaro
Received: 1 July 2015 / Revised: 6 September 2015 / Accepted: 9 September 2015 / Published: 11 September 2015
(This article belongs to the Section Physical Sensors)
View Full-Text   |   Download PDF [1292 KB, uploaded 11 September 2015]   |  

Abstract

Global navigation satellite systems (GNSS) are the most widely used positioning, navigation, and timing (PNT) technology. However, a GNSS cannot provide effective PNT services in physical blocks, such as in a natural canyon, canyon city, underground, underwater, and indoors. With the development of micro-electromechanical system (MEMS) technology, the chip scale atomic clock (CSAC) gradually matures, and performance is constantly improved. A deep coupled integration of CSAC and GNSS is explored in this thesis to enhance PNT robustness. “Clock coasting” of CSAC provides time synchronized with GNSS and optimizes navigation equations. However, errors of clock coasting increase over time and can be corrected by GNSS time, which is stable but noisy. In this paper, weighted linear optimal estimation algorithm is used for CSAC-aided GNSS, while Kalman filter is used for GNSS-corrected CSAC. Simulations of the model are conducted, and field tests are carried out. Dilution of precision can be improved by integration. Integration is more accurate than traditional GNSS. When only three satellites are visible, the integration still works, whereas the traditional method fails. The deep coupled integration of CSAC and GNSS can improve the accuracy, reliability, and availability of PNT. View Full-Text
Keywords: integration; CSAC; GNSS; weighted linear optimal estimation; Kalman filter integration; CSAC; GNSS; weighted linear optimal estimation; Kalman filter
Figures

Figure 1

This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. (CC BY 4.0).

Scifeed alert for new publications

Never miss any articles matching your research from any publisher
  • Get alerts for new papers matching your research
  • Find out the new papers from selected authors
  • Updated daily for 49'000+ journals and 6000+ publishers
  • Define your Scifeed now

SciFeed Share & Cite This Article

MDPI and ACS Style

Ma, L.; You, Z.; Li, B.; Zhou, B.; Han, R. Deep Coupled Integration of CSAC and GNSS for Robust PNT. Sensors 2015, 15, 23050-23070.

Show more citation formats Show less citations formats

Related Articles

Article Metrics

Article Access Statistics

1

Comments

[Return to top]
Sensors EISSN 1424-8220 Published by MDPI AG, Basel, Switzerland RSS E-Mail Table of Contents Alert
Back to Top