scholarly journals GPS Positioning Accuracy Improvement Using Multiple Reference Stations

1999 ◽  
Vol 101 (0) ◽  
pp. 15-20
Author(s):  
Takeyasu SAKAI ◽  
Kazunobu KOREMURA
2020 ◽  
Vol 12 (4) ◽  
pp. 138-148 ◽  
Author(s):  
Shijian Su ◽  
Xianping Zeng ◽  
Shuang Song ◽  
Mingqiang Lin ◽  
Houde Dai ◽  
...  

Sensors ◽  
2015 ◽  
Vol 15 (7) ◽  
pp. 16895-16909 ◽  
Author(s):  
Chang-Ki Hong ◽  
Chi Park ◽  
Joong-hee Han ◽  
Jay Kwon

2020 ◽  
Vol 12 (19) ◽  
pp. 3178
Author(s):  
Jian Wang ◽  
Tianhe Xu ◽  
Wenfeng Nie ◽  
Guochang Xu

Reliable real-time kinematic (RTK) is crucially important for emerging global navigation satellite systems (GNSSs) applications, such as drones and unmanned vehicles. The performance of conventional single baseline RTK (SBRTK) with one reference station degrades greatly in dense, urban environments, due to signal blockage and multipath error. The increasing use of multiple reference stations for kinematic positioning can improve RTK positioning accuracy and availability in urban areas. This paper proposes a new algorithm for multi-baseline RTK (MBRTK) positioning based on the equivalence principle. The advantages of the solution are to keep observation independent and increase the redundancy to estimate the unknown parameters. The equivalent double-differenced (DD) observation equations for multiple reference stations are firstly developed through the equivalent transform. A modified Kalman filter with parameter constraints is proposed, as well as a partial ambiguity resolution (PAR) strategy is developed to determine an ambiguity subset. Finally, the static and kinematic experiments are carried out to validate the proposed algorithm. The results demonstrate that, compared with single global positioning system (GPS) and Beidou navigation system (BDS) RTK positioning, the GPS/BDS positioning for MBRTK can enhance the positioning accuracy with improvement by approximately (45%, 35%, and 27%) and (12%, 6%, and 19%) in the North (N), East (E), and Up (U) components, as well as the availability with improvement by about 33% and 10%, respectively. Moreover, the MBRTK model with two and three reference receivers can significantly increase the redundancy and provide smaller ambiguity dilution of precision (ADOP) values. Compared with the scheme-one and scheme-two for SBRTK, the MBRTK with multiple reference receivers have a positioning accuracy improvement by about (9%, 0%, and 6%) and (9%, 16%, and 16%) in N, E, and U components, as well as the availability improvement by approximately 10%. Therefore, compared with the conventional SBRTK, the MBRTK can enhance the strength of the kinematic positioning model as well as improve the positioning accuracy and availability.


2014 ◽  
Vol 945-949 ◽  
pp. 3364-3368
Author(s):  
Min Fan

the taxi intelligent terminal management system using the latest GPS and Beidou Positioning Technology and network technology, embedded programming technology, Windows CE terminal operating system, cloud computing technology, the original taxi valuation multiple system, GPS positioning system, the taxi service evaluation system, intelligent light system, monitoring system and one card system. Integration, design a set of complete city taxi intelligent terminal management system, to achieve a high level of management. Double backup location system using GPS positioning and Chinese Beidou Positioning, positioning accuracy, reliable, real-time operational data store upload taxi and reliable data, which can realize safe driving record, automobile security alarm, accident alarm and anti-theft alarm and tracking and control, in the taxi can achieve "flat-share carpool", can realize the time-sharing, people, time, metering and billing and other functions, and improves the bearing rate of the vehicle, more energy saving and environmental protection. The system has broad application prospects and the market space. The system will realize some technical indicators: receive 10 channels, the positioning accuracy of <5 meters, the cold start time <30 seconds, hot start time <3 seconds, GPS relocation time <30 seconds.


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