Absolute Positioning with Single-Frequency GPS Receivers

Øvstedal, O.

doi:10.1007/pl00012910

Cited by 101 publications

(44 citation statements)

References 5 publications

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“…In the past few years, research has been done on the performance of single-frequency precise point positioning using L1 measurements (Øvstedal 2002;Le and Tiberius 2007;van Bree et al 2009). To show how much performance has improved over the last decade, an indicative comparison of positioning error statistics is made in Table 6.…”

Section: L1 Results During Last Decadementioning

confidence: 99%

Real-time single-frequency precise point positioning: accuracy assessment

Bree

Tiberius

2011

GPS Solut

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The performance of real-time single-frequency precise point positioning is demonstrated in terms of position accuracy. This precise point positioning technique relies on predicted satellite orbits, predicted global ionospheric maps, and in particular on real-time satellite clock estimates. Results are presented using solely measurements from a user receiver on the L1-frequency (C1 and L1), for almost 3 months of data. The empirical standard deviations of the position errors in North and East directions are about 0.15 m, and in Up direction about 0.30 m. The 95% errors are about 0.30 m in the horizontal directions, and 0.65 m in the vertical. In addition, single-frequency results of six receivers located around the world are presented. This research reveals the current ultimate real-time single-frequency positioning performance. To put these results into perspective, a case study is performed, using a moderately priced receiver with a simple patch antenna.

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Section: L1 Results During Last Decadementioning

confidence: 99%

Real-time single-frequency precise point positioning: accuracy assessment

Bree

Tiberius

2011

GPS Solut

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“…The overall RMS value for each day is calculated by taking the square root of the accumulated squared deviations divided by the total number of satellites [42].…”

Section: Accuracy Assessment Of the Global Ionosphere Modelmentioning

confidence: 99%

The Impacts of the Ionospheric Observable and Mathematical Model on the Global Ionosphere Model

Nie

Rovira‐Garcia

et al. 2018

Remote Sensing

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A high-accuracy Global Ionosphere Model (GIM) is significant for precise positioning and navigating with the Global Navigation Satellite System (GNSS), as well as space weather applications.To obtain a precise GIM, it is critical to take both the ionospheric observable and mathematical model into consideration. In this contribution, the undifferenced ambiguity-fixed carrier-phase ionospheric observable is first determined from a global distribution of permanent receivers. Accuracy assessment with a co-located station experiment shows that the observational errors affecting the ambiguity-fixed carrier-phase ionospheric observables range from 0.10 to 0.35 Total Electron Content Units (TECUs, where 1 TECU = 10 16 e − /m 2 and corresponds to 0.162 m on the Global Positioning System, GPS L1 frequency), indicating that the ambiguity-fixed carrier-phase ionospheric observable is over one order of magnitude more accurate than the carrier-phase leveled-code one (from 1.21 to 3.77 TECUs). Second, to better model the structure of the ionosphere, a two-layer GIM has been built based on the above carrier-phase observable. Preliminary global accuracy evaluation demonstrates that the accuracy of the two-layer GIM is below 1 TECU and about 2 TECUs during low and high solar activity periods. Third, the single-frequency point positioning experiment is adopted to test the ionosphere mitigation effects of the GIMs. Positioning results demonstrate that the single-frequency positioning accuracy can be improved by more than 30% using the undifferenced ambiguity-fixed ionospheric observable-derived two-layer GIM, compared with that using the carrier-phase leveled-code ionospheric observable-based single-layer GIM.

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“…Root Mean Square (RMS) was used to evaluate approximations results [10]. RMS value is computed using:…”

Section: Testing the Proposed Methodsmentioning

confidence: 99%

Performance Improvement of GPS GDOP Approximation Using Recurrent Wavelet Neural Network

Tafazoli¹,

Mosavi²

2011

JGIS

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One of the most important factors affecting the precision of the performance of a GPS receiver is the relative positioning of satellites to each other. Therefore, it is essential to choose appropriate accessible satellites utilized in the calculation of GPS positions. Optimal subsets of satellites are determined using the least value of their Geometric Dilution of Precision (GDOP). The most correct method of calculating GPS GDOP uses inverse matrix for all combinations and selecting the lowest ones. However, the inverse matrix method, especially when there are so many satellites, imposes a huge calculation load on the processor of the GPS navigator. In this paper, the rapid and precise calculation of GPS GDOP based on Recurrent Wavelet Neural Network (RWNN) has been introduced for selecting an optimal subset of satellites. The method of NNs provides a realistic calculation approach to determine GPS GDOP without any need to calculate inverse matrix.

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Absolute Positioning with Single-Frequency GPS Receivers

Cited by 101 publications

References 5 publications

Real-time single-frequency precise point positioning: accuracy assessment

Real-time single-frequency precise point positioning: accuracy assessment

The Impacts of the Ionospheric Observable and Mathematical Model on the Global Ionosphere Model

Performance Improvement of GPS GDOP Approximation Using Recurrent Wavelet Neural Network

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