Minimal Detectable Biases of GPS observations for a weighted ionosphere

Jong, Kees de; Teunissen, Peter

doi:10.1186/bf03352295

Cited by 9 publications

(5 citation statements)

References 8 publications

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“…The MDB is an important diagnostic tool for inferring the strength of model validation. Examples of such studies for geometry-dependent and integrated GNSS models can be found in (Salzmann 1991;Teunissen 1998b;de Jong and Teunissen 2000;Hewitson and Wang 2010).…”

Section: Introductionmentioning

confidence: 99%

Single-receiver single-channel multi-frequency GNSS integrity: outliers, slips, and ionospheric disturbances

Teunissen

Bakker

2012

J Geod

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In this contribution the integrity of singlereceiver, single-channel, multi-frequency GNSS models is studied. The uniformly most powerful invariant test statistics for spikes and slips are derived and their detection capabilities are described by means of minimal detectable biases (MDBs). Analytical closed-form expressions of the phase-slip, code-outlier and ionospheric-disturbance MDBs are given, thus providing insight into the various factors that contribute to the detection capabilities of the various test statistics. This is also done for the phaseless and codeless cases, as well as for the case of a temporary loss-of-lock on all frequencies. The analytical analysis presented is supported by means of numerical results.

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Section: Introductionmentioning

confidence: 99%

Single-receiver single-channel multi-frequency GNSS integrity: outliers, slips, and ionospheric disturbances

Teunissen

Bakker

2012

J Geod

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“…By means of reliability measures we can describe the performance of this testing [28]. The Minimal Detectable Bias (MDB) describes the internal reliability, determined by matching a certain probability of false alarm α and of detection, power γ = 1 − β, where β is the probability is missed detection [29,30].…”

Section: Internal Reliability: Minimal Detectable Biasmentioning

confidence: 99%

Precision and Reliability of Tightly Coupled PPP GNSS and Landmark Monocular Vision Positioning

Pang

Tiberius

2020

Sensors

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This paper presents an approach to analyse the quality, in terms of precision and reliability, of a system which integrates—at the observation-level—landmark positions and GNSS measurements, obtained with a single camera and a digital map, and a single frequency GNSS receiver respectively. We illustrate the analysis by means of design computations, and we present the actual performance by means of a small experiment in practice. It is shown that the integration model is able to produce a position solution even when both sensors individually fail to do so. With realistic assumptions on measurement noise, the proposed integrated, low-cost system can deliver a horizontal position with a precision of better than half a meter. The external reliability of the integrated system is at the few decimetre-level, showing that the impact of undetected faults in the measurements, for instance incorrectly identified landmarks in the image, on the horizontal position is limited and acceptable, thereby confirming the fault-robustness of the system.

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“…Some methods used linear combinations of the observations or their time-difference to estimate cycle slips (Blewitt 1990, Dai 2012. The Detection-Identification-Adaptation (DIA) is another method for quality control of single-baseline GNSS observations, which has been discussed in Teunissen (1990), Teunissen (1998), andTeunissen (2000). De Bakker el al.…”

Section: Introductionmentioning

confidence: 99%

GNSS multi-frequency receiver single-satellite measurement validation method

El‐Mowafy

2013

GPS Solut

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A method is presented for real-time validation of GNSS measurements of a single receiver, where data from each satellite are independently processed. A geometry-free observation model is used with a reparameterized form of the unknowns to overcome rank deficiency of the model. The ionosphere error and non-constant biases such as multipath are assumed changing relatively smoothly as a function of time. Data validation and detection of errors is based on statistical testing of the observation residuals using the Detection-Identification-Adaptation (DIA) approach. The method is applicable to any GNSS with any number of frequencies. The performance of validation method was evaluated using multiple-frequency data from three GNSS (GPS, GLONASS and Galileo) that span three days in a test site at Curtin University, Australia. Performance of the method in detection and identification of outliers in code observations and detection of cycle slips in phase data was examined. Results show that the success rate vary according to precision of observations and their number as well as size of the errors. The method capability is demonstrated when processing four IOV Galileo satellites in a single point positioning mode, and in another test by comparing its performance with Bernese software in detection of cycle slips in PPP processing using GPS data.

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Minimal Detectable Biases of GPS observations for a weighted ionosphere

Cited by 9 publications

References 8 publications

Single-receiver single-channel multi-frequency GNSS integrity: outliers, slips, and ionospheric disturbances

Single-receiver single-channel multi-frequency GNSS integrity: outliers, slips, and ionospheric disturbances

Precision and Reliability of Tightly Coupled PPP GNSS and Landmark Monocular Vision Positioning

GNSS multi-frequency receiver single-satellite measurement validation method

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