Variances of GPS Phase Observations: The SIGMA-ɛ Model

Hartinger, Horst; Brunner, Fritz K.

doi:10.1007/pl00012765

Cited by 165 publications

(85 citation statements)

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“…These results have obviously a good agreement with that reported by Hartinger and Brunner (1999), Wieser andBrunner (2000, 2001). Although, the satellite elevation may not reflect reality but it still can be used as a quality indicator.…”

Section: Gps Measurements Accuracy Due To the Satellite Elevation Anglesupporting

confidence: 93%

Comparison of the Stochastic Models for Double-Differenced GPS Measurements

Darmawan¹,

Kimata²

2004

itbj.eng.sci.

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Abstract. Double-differenced GPS carrier phase measurements are commonly used in GPS precise positioning applications and processed with algorithms based on the least-squares (LS) principle. In order to apply the LS principle, one needs to define properly both the functional and stochastic models. Whilst the functional model for precise GPS positioning is sufficiently well known, realistic stochastic modeling is still a difficult task to accomplish in practice. Incorrect stochastic models for double-differenced GPS measurements will lead to unreliable estimates for ambiguity resolution and, eventually, it will bias positioning results. The common assumption when we construct the stochastic model is that all raw GPS measurements are independent and have the same variances. In fact, this is not realistic, since due to varying noise levels measurements obtained from different GPS satellites cannot have the same accuracy. A realistic stochastic modeling should be able to capture the ordinary noises in the observables.In order to specify a realistic stochastic model for precise relative GPS positioning applications, in this paper the performance of three stochastic models namely the commonly used model or the standard model, the outer product of residual data vector model and Minimum Norm Quadratic Unbiased Estimation (MINQUE) are examined and effects of each the proposed model on statistic for ambiguity search and positioning accuracy are compared. The results indicate that the MINQUE model tends to perform better than the other models. Using the MINQUE model, the reliability of the ambiguity resolution and the statistics of the baseline components can be improved. It may suggest that the MINQUE model, which is based on modern statistical theory, is capable of capturing the ordinary noises.

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Section: Gps Measurements Accuracy Due To the Satellite Elevation Anglesupporting

confidence: 93%

Comparison of the Stochastic Models for Double-Differenced GPS Measurements

Darmawan¹,

Kimata²

2004

itbj.eng.sci.

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“…where C/N0 is the carrier noise ratio measured by the receiver and const = 1.1×10 4 is a constant [40]. In urban areas, the C/N0 based weighting method is more appropriate than the elevation based weighting method because the NLOS reception usually has a weak C/N0 but enters at a relatively high elevation angle [27].…”

Section: Fault Detection Based On Consistency Checkmentioning

confidence: 99%

Multiple Faulty GNSS Measurement Exclusion Based on Consistency Check in Urban Canyons

et al. 2017

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Abstract-Sensors play important roles for autonomous driving.Localization is definitely a key one. Undoubtedly, global positioning system (GPS) sensor will provide absolute localization for almost all the future land vehicles. In terms of driverless car, 1.5 meters of positioning accuracy is the minimum requirement since the vehicle has to keep in a driving lane that usually wider than 3 meters. However, the skyscrapers in highly-urbanized cities such as Tokyo and Hong Kong, dramatically deteriorate GPS localization performance, leading more than 50 meters of error. GPS signals are reflected at modern glassy buildings which caused the notorious multipath effect. Fortunately, the number of navigation satellite is rapidly increasing in a global scale since the rise of multi-GNSS (global navigation satellite system). It provides an excellent opportunity for positioning algorithm developer of GPS sensor. More satellites in the sky implies more measurements to be received. Novelty, this paper proposes to take advantage of the fact that clean measurements (refers to line-of-sight measurement) are consistent and multipath measurements are inconsistent. Based on this consistency check, the faulty measurements can be detected and excluded to obtain better localization accuracy. Experimental results indicate that the proposed method can achieve less than 1 meter lateral positioning error in middle urban canyons.

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“…where (C/N 0 ) j is the measured carrier-power-to-noise-density ratio of the j th satellite signal in dB-Hz and c = 1·1 × 10 4 m 2 is a constant (Hartinger and Brunner, 1999).…”

Section: E a S T -S Q U A R E S P O S I T I O N I N Gmentioning

confidence: 99%

Height Aiding, C/N₀ Weighting and Consistency Checking for GNSS NLOS and Multipath Mitigation in Urban Areas

2013

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Multiple global navigation satellite system (GNSS) constellations can dramatically improve the signal availability in dense urban environments. However, accuracy remains a challenge because buildings block, reflect and diffract the signals. This paper investigates three different techniques for mitigating the impact of non-line-of-sight (NLOS) reception and multipath interference on position accuracy without using additional hardware, testing them using data collected at multiple sites in central London. Aiding the position solution using a terrain height database was found to have the biggest impact, improving the horizontal accuracy by 35% and the vertical accuracy by a factor of 4. An 8% improvement in horizontal accuracy was also obtained from weighting the GNSS measurements in the position solution according to the carrier-power-to-noise-density ratio (C/N 0 ). Consistency checking using a conventional sequential elimination technique was found to degrade horizontal positioning performance by 60% because it often eliminated the wrong measurements in cases when multiple signals were affected by NLOS reception or strong multipath interference. A new consistency checking method that compares subsets of measurements performed better, but was still equally likely to improve or degrade the accuracy. This was partly because removing a poor measurement can result in adverse signal geometry, degrading the position accuracy. Based on this, several ways of improving the reliability of consistency checking are proposed. K E Y

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Variances of GPS Phase Observations: The SIGMA-ɛ Model

Cited by 165 publications

References 0 publications

Comparison of the Stochastic Models for Double-Differenced GPS Measurements

Comparison of the Stochastic Models for Double-Differenced GPS Measurements

Multiple Faulty GNSS Measurement Exclusion Based on Consistency Check in Urban Canyons

Height Aiding, C/N₀ Weighting and Consistency Checking for GNSS NLOS and Multipath Mitigation in Urban Areas

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Variances of GPS Phase Observations: The SIGMA-ɛ Model

Cited by 165 publications

References 0 publications

Comparison of the Stochastic Models for Double-Differenced GPS Measurements

Comparison of the Stochastic Models for Double-Differenced GPS Measurements

Multiple Faulty GNSS Measurement Exclusion Based on Consistency Check in Urban Canyons

Height Aiding, C/N0 Weighting and Consistency Checking for GNSS NLOS and Multipath Mitigation in Urban Areas

Contact Info

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Height Aiding, C/N₀ Weighting and Consistency Checking for GNSS NLOS and Multipath Mitigation in Urban Areas