Assessing the IRNSS L5-signal in combination with GPS, Galileo, and QZSS L5/E5a-signals for positioning and navigation

Nadarajah, Nandakumaran; Khodabandeh, Amir; Teunissen, Peter

doi:10.1007/s10291-015-0450-8

Cited by 59 publications

(34 citation statements)

References 12 publications

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“…For receivers of different manufacturers, although DISBs cannot be eliminated, their stability in time has been proven, and thus can be calibrated in advance. Using these characteristics, the obvious improvement of ambiguity resolution (AR) and positioning with calibrated DISBs for short and long baseline RTK have been verified, the details of which can be seen in [11,[13][14][15][16]. For the real-time estimation of DISBs and application for AR, Tian et al [12] proposed a particle filter-based method to estimate GPS L1-Galileo E1 phase DISBs based on the fact that the accuracy of a given DISB value can be qualified by the related fixing ratio.…”

Section: Introductionmentioning

confidence: 93%

“…2017, 9, 948 5 of 16 By Equation (10), we can reparameterize the inter-system DD ambiguities into ambiguities relative to the BDS reference satellite, plus the ambiguity of the BDS reference satellite with respect to the GPS reference satellite. This last ambiguity and the SD ambiguity of the GPS reference satellite are then estimable jointly with the differential phase DISB.…”

Section: Intra-system and Inter-system Observation Modelmentioning

confidence: 99%

“…2017, 9, 948 3 of 16 The rest of this paper is organized as follows: In Section 2, the models for combined GPS and BDS observations are introduced, including the classical differencing and the inter-system differencing models. In Section 3, the stability of L1-B1 and L2-B2 code and phase DISBs in time domain is analyzed with several zero and ultra-short baselines.…”

Section: Introductionmentioning

confidence: 99%

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Inter-System Differencing between GPS and BDS for Medium-Baseline RTK Positioning

Gao

Pan

et al. 2017

Remote Sensing

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An inter-system differencing model between two Global Navigation Satellite Systems (GNSS) enables only one reference satellite for all observations. If the associated differential inter-system biases (DISBs) are priori known, double-differenced (DD) ambiguities between overlapping frequencies from different GNSS constellations can also be fixed to integers. This can provide more redundancies for the observation model, and thus will be beneficial to ambiguity resolution (AR) and real-time kinematic (RTK) positioning. However, for Global Positioning System (GPS) and the regional BeiDou Navigation Satellite System (BDS-2), there are no overlapping frequencies. Tight combination of GPS and BDS needs to process not only the DISBs but also the single-difference ambiguity of the reference satellite, which is caused by the influence of different frequencies. In this paper, we propose a tightly combined dual-frequency GPS and BDS RTK positioning model for medium baselines with real-time estimation of DISBs. The stability of the pseudorange and phase DISBs is analyzed firstly using several baselines with the same or different receiver types. The dual-frequency ionosphere-free model with parameterization of GPS-BDS DISBs is proposed, where the single-difference ambiguity is estimated jointly with the phase DISB parameter from epoch to epoch. The performance of combined GPS and BDS RTK positioning for medium baselines is evaluated with simulated obstructed environments. Experimental results show that with the inter-system differencing model, the accuracy and reliability of RTK positioning can be effectively improved, especially for the obstructed environments with a small number of satellites available.

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Section: Introductionmentioning

confidence: 93%

Section: Intra-system and Inter-system Observation Modelmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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Inter-System Differencing between GPS and BDS for Medium-Baseline RTK Positioning

Gao

Pan

et al. 2017

Remote Sensing

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“…Montenbruck and Steigenberger (2015) used the observations of the IRNSS-1A and 1B to investigate the quality of the IRNSS navigation messages. Nadarajah et al (2015), after assessing the IRNSS noise characteristics, combines the L5/E5 signals of IRNSS, GPS, Galileo and QZSS for instantaneous attitude determination. The positioning results over India based on the data of I1, I2, I3, and I4 are presented in .…”

Section: Introductionmentioning

confidence: 99%

IRNSS/NavIC and GPS: a single- and dual-system L5 analysis

Zaminpardaz

Teunissen

Nadarajah

2017

J Geod

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The Indian Regional Navigation Satellite System (IRNSS) has recently (May 2016) become fully-operational. In this contribution, for the fully-operational IRNSS as a standalone system and also in combination with GPS, we provide a first assessment of L5 integer ambiguity resolution and positioning performance. While our empirical analyses are based on the data collected by two JAVAD receivers at Curtin University, Perth, Australia, our formal analyses are carried out for various onshore locations within the IRNSS service area. We study the noise characteristics (carrier-tonoise density, measurement precision, time-correlation), the integer ambiguity resolution performance (success rates and ambiguity dilution of precision (ADOP)), and the positioning performance (ambiguity float and ambiguity fixed). The results show that our empirical outcomes are consistent with their formal counterparts and that the GPS L5-data have a lower noise level than that of IRNSS L5-data, particularly in case of the code data. The underlying model in our assessments varies from standalone IRNSS (L5) to IRNSS+GPS (L5), from unconstrained to height-constrained and from kinematic to static. Significant improvement of ambiguity resolution and positioning performance are achievable upon integrating L5-data of IRNSS with GPS.

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“…While the GLONASS L3 signal has a BPSK(10) modulation (Urlichich et al 2011), the GPS L1 (C/A) signal has a BPSK(1) modulation (GPSD 2013). The C/N0 graph of the GLONASS L3 signal has a similar signature to that of GPS L5-signal (see Nadarajah et al (2015)), which also has a BPSK(10) modulation.…”

Section: Carrier-to-noise Densitymentioning

confidence: 85%

GLONASS CDMA L3 ambiguity resolution and positioning

2016

Self Cite

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A first assessment of GLONASS CDMA L3 ambiguity resolution and positioning performance is provided. Our analyses are based on GLONASS L3 data from the satellite pair SVNs 755-801, received by two JAVAD receivers at Curtin University, Perth, Australia. In our analyses, four different versions of the two-satellite model are applied: the geometry-free model, the geometry-based model , the height-constrained geometry-based model, and the geometry-fixed model. We study the noise characteristics (carrier-to-noise density, measurement precision), the integer ambiguity resolution performance (success rates and distribution of the ambiguity residuals), and the positioning performance (ambiguity float and ambiguity fixed). The results show that our empirical outcomes are consistent with their formal counterparts and that the GLONASS data have a lower noise level than that of GPS, particularly in case of the code data. This difference is not only seen in the noise levels but also in their onward propagation to the ambiguity time series and ambiguity residuals distribution.

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Assessing the IRNSS L5-signal in combination with GPS, Galileo, and QZSS L5/E5a-signals for positioning and navigation

Cited by 59 publications

References 12 publications

Inter-System Differencing between GPS and BDS for Medium-Baseline RTK Positioning

Inter-System Differencing between GPS and BDS for Medium-Baseline RTK Positioning

IRNSS/NavIC and GPS: a single- and dual-system L5 analysis

GLONASS CDMA L3 ambiguity resolution and positioning

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