Sturdy Positioning with High Sensitivity GPS Sensors Under Adverse Conditions

Trajkovski, Klemen Kozmus; Sterle, Oskar; Stopar, Bojan

doi:10.3390/s100908332

Cited by 15 publications

(10 citation statements)

References 7 publications

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“…The degradation of GNSS signals in forests (e.g., [55,56]) makes it often necessary to use total station measurements. In cases where the survey cannot be conducted from a single occupation point, this means complications and increased time consumption.…”

Section: Discussionmentioning

confidence: 99%

Accuracy of Photogrammetric UAV-Based Point Clouds under Conditions of Partially-Open Forest Canopy

Tomaštík

Mokroš

Saloň

et al. 2017

Forests

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This study focuses on the horizontal and vertical accuracy of point-clouds based on unmanned aerial vehicle (UAV) imagery. The DJI Phantom 3 Professional unmanned aerial vehicle and Agisoft PhotoScan Professional software were used for the evaluation. Three test sites with differing conditions (canopy openness, slope, terrain complexity, etc.) were used for comparison. The accuracy evaluation was aimed on positions of points placed on the ground. This is often disregarded under forest conditions as it is not possible to photogrammetrically reconstruct terrain that is covered by a fully-closed forest canopy. Therefore, such a measurement can only be conducted when there are gaps in the canopy or under leaf-off conditions in the case of deciduous forests. The reported sub-decimetre horizontal accuracy and vertical accuracy lower than 20 cm have proven that the method is applicable for survey, inventory, and various other tasks in forests. An analysis of ground control point (GCP) quantity and configuration showed that the quantity had only a minor effect on the accuracy in cases of plots with~1-hectare area when using the aforementioned software. Therefore, methods increasing quality (precision, accuracy) of GCP positions should be preferred over the increase of quantity alone.

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Section: Discussionmentioning

confidence: 99%

Accuracy of Photogrammetric UAV-Based Point Clouds under Conditions of Partially-Open Forest Canopy

Tomaštík

Mokroš

Saloň

et al. 2017

Forests

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“…Usually only the code and phase observations are used for determining position. Kozmus Trajkovski et al (2010) showed that Doppler measurements may significantly improve position determination, especially in adverse conditions in which phase observations are useless.…”

Section: Introductionmentioning

confidence: 99%

Single-frequency precise point positioning: an analytical approach

Sterle

Stopar

Prešeren

2015

J Geod

Self Cite

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An analytical approach to single-frequency precise point positioning (PPP) is discussed in this paper. To obtain highest precision results, all biases must be eliminated or modelled to centimetre level. The use of the GRAPHIC ionosphere-free linear combination that is based on single-frequency phase and code observations eliminates the ionosphere bias; however, the rank deficient GaussMarkov model is obtained. We explicitly determine rank deficiency of a Gauss-Markov model as a number of all ambiguity clusters, each of them defined as a set of all ambiguities overlapping in time. On the basis of S-transformation we prove that the single-frequency PPP represents an unbiased estimator for station coordinates and troposphere parameters, while it presents a biased estimator for ambiguities and receiver-clock error parameters. Additionally we describe the estimable parameters in each ambiguity cluster as the differences between ambiguity parameters and the sum of receiver-clock parameters with one of the ambiguities. We also show that any other particular solution on the basis of S-transformation is obtained only when the common leastsquares estimation in single step is applied. The recursive least-squares estimation with parameter pre-elimination only determines the vector of unknowns as possible to transform through S-transformation, whereas the same does not hold for the cofactor matrix of unknowns. For a case study, we present our method on GPS data from 19 permanent stations (14 IGS and 5 EPN) in Europe, for 89 consecutive days in the beginning of 2013. The static case study revealed the precision of daily coordinates as 7.6, 11.7 and 19.6 mm for N , E and U , respectively. The accuracies of the N , E and U components were determined as 6.9, 13.5 and 31.4 mm, respectively, and were calculated using the Helmert transformation of weighted-mean daily single-frequency PPP and IGb08 coordinates. The estimated convergence times were relatively diverse, expanding from 1.75 h (CAGL) to 5.25 h (GRAZ) for the horizontal position with the 10-cm precision threshold, and from 1.00 h (GRAS) to 3.25 h (BZRG) for the height component with a 20-cm precision threshold. The convergence times were shown to be strongly correlated to the remaining unmodelled biases in the GRAPHIC linear combination, primarily with multipath, where the correlation coefficient for the horizontal position was determined as ρ P = 0.68 and for height as ρ U = 0.85. The comparison to the model where raw observations are used (C, L) and where the ionosphere bias is mitigated with global ionosphere models (GIM) revealed the supremacy of the proposed single-frequency PPP method based on the GRAPHIC linear combination in both the static and the semi-kinematic case study. In the static case study, the proposed singlefrequency PPP model was superior both in terms of precision and accuracy. In the semi-kinematic case study, the usage of raw observations with GIM would improve results only when multipath and noise of code observations would prevail over the remaini...

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“…The calculated correction message is transferred to the rover, to enable highly accurate real-time positioning [4]. Multiple GPS reference stations are utilized, because using a single reference station reduces accuracy if the distance between the rover and the reference station exceeds 10 km [5,6]. The NRTK correction message may be calculated using the data from multiple GPS reference stations placed at intervals of 50–70 km across a wide area, and the results may then be transferred in NTRIP format.…”

Section: Introductionmentioning

confidence: 99%

Development of an RTK-GPS Positioning Application with an Improved Position Error Model for Smartphones

Hwang

Yun

Suh

et al. 2012

Sensors

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This study developed a smartphone application that provides wireless communication, NRTIP client, and RTK processing features, and which can simplify the Network RTK-GPS system while reducing the required cost. A determination method for an error model in Network RTK measurements was proposed, considering both random and autocorrelation errors, to accurately calculate the coordinates measured by the application using state estimation filters. The performance evaluation of the developed application showed that it could perform high-precision real-time positioning, within several centimeters of error range at a frequency of 20 Hz. A Kalman Filter was applied to the coordinates measured from the application, to evaluate the appropriateness of the determination method for an error model, as proposed in this study. The results were more accurate, compared with those of the existing error model, which only considered the random error.

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Sturdy Positioning with High Sensitivity GPS Sensors Under Adverse Conditions

Cited by 15 publications

References 7 publications

Accuracy of Photogrammetric UAV-Based Point Clouds under Conditions of Partially-Open Forest Canopy

Accuracy of Photogrammetric UAV-Based Point Clouds under Conditions of Partially-Open Forest Canopy

Single-frequency precise point positioning: an analytical approach

Development of an RTK-GPS Positioning Application with an Improved Position Error Model for Smartphones

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