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Deep Coupled Integration of CSAC and GNSS for Robust PNT

1,2,*, 1,2, 1,2, 1,2 and 1,2
Department of Precision Instrument, Tsinghua University, Beijing 100084, China
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
Sensors 2015, 15(9), 23050-23070;
Received: 1 July 2015 / Revised: 6 September 2015 / Accepted: 9 September 2015 / Published: 11 September 2015
(This article belongs to the Section Physical Sensors)
PDF [1292 KB, uploaded 11 September 2015]


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

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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.

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