Evaluation of GPS Data for Navigational Solution and Error Reduction Using Kalman Filter

Vani, N.; Banu, S. Khadeeja

doi:10.1109/icdi3c.2018.00012

Cited by 2 publications

(2 citation statements)

References 6 publications

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“…Along the three orthogonal directions, the decomposition of the ephemeris error is carried out. Root sum square value of the clock error and line of sight of ephemeris error contributes to the range error of errors in clock and ephemeris [22], [28], [29].…”

Section: Control System Errormentioning

confidence: 99%

Study of positioning estimation with user position affected by outlier: a case study of moving-horizon estimation filter

et al. 2022

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Many applications which require accurate location point positioning systems utilize global position system for pseudosciences. One of the main challenges faced by the system occurs due to the inherent errors that are a resultant of outliers. This considerably reduces the accuracy of the observations of global position system device. In this paper, we briefly introduce the problem of position estimation when the pseudo range measurements have an outlier. Moving horizon estimation algorithm has been adapted for the simulation result compared with the extended Kalman filter model, which is still imperfect for the case of outlier. The point at which a pseudo range becomes an outlier is considered at a fixed time instance. A simulation example is presented using an existing model with a moving horizon estimator and an extended Kalman filter. The moving horizon filter turns to be more robust than Kalman filtering with presence of outlier under certain choice of tunning parameter.

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Section: Control System Errormentioning

confidence: 99%

Study of positioning estimation with user position affected by outlier: a case study of moving-horizon estimation filter

et al. 2022

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“…12, No. 1, February 2022: 179-188 180 issues for deviation alters in real-time, and iv) information obtained from it are not precise always [6]. In this regards, there has been various research work being carried out to overcome these problems; however, the legacy problem remains the same more or less.…”

Section: Introductionmentioning

confidence: 99%

An autonomous navigational system using GPS and computer vision for futuristic road traffic

Ramasamy

Kabadi²

2022

IJECE

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Navigational service is one of the most essential dependency towards any transport system and at present, there are various revolutionary approaches that has contributed towards its improvement. This paper has reviewed the global positioning system (GPS) and computer vision based navigational system and found that there is a large gap between the actual demand of navigation and what currently exists. Therefore, the proposed study discusses about a novel framework of an autonomous navigation system that uses GPS as well as computer vision considering the case study of futuristic road traffic system. An analytical model is built up where the geo-referenced data from GPS is integrated with the signals captured from the visual sensors are considered to implement this concept. The simulated outcome of the study shows that proposed study offers enhanced accuracy as well as faster processing in contrast to existing approaches.

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Evaluation of GPS Data for Navigational Solution and Error Reduction Using Kalman Filter

Cited by 2 publications

References 6 publications

Study of positioning estimation with user position affected by outlier: a case study of moving-horizon estimation filter

Study of positioning estimation with user position affected by outlier: a case study of moving-horizon estimation filter

An autonomous navigational system using GPS and computer vision for futuristic road traffic

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