Cycle Slip Detection in Kinematic GPS with a Jerk Model for Land Vehicles

Sugimoto

et al. 2016

Transactions of ISCIE

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In this paper, we propose methods of detecting Doppler outliers which cause positioning errors at Doppler-aided GNSS (Global Navigation Satellite System) positioning, and correcting the errors. We apply the existing detection method based on the innovation process in Kalman filtering to Doppler outlier problems, and we propose a novel detection method based on the measurements by the difference between C/A code pseudoranges and Doppler shift range-rates. Both methods are based on chi-squared tests. We apply two correction methods which are Doppler bias exclusion, or the estimation for detected anomalies. The efficient detection of anomalous observables can be developed to RAIM (Receiver Autonomous Integrity Monitoring), and useful to achieve higher accuracy positioning for increasing satellite signals by multi-frequencies and multi-GNSSs. Doppler shift observables are utilized on a priority basis even in urban areas because of immunity to cycleslip and continuous availability, however unexpected Doppler outliers prone to cause positioning errors. The experimental results of positioning by using real receiver data show the feasibility of the proposed detection and correction methods.

Section: State Equationmentioning

confidence: 99%

Detection and Correction of Doppler Outliers in Kalman Filter-based Positioning

Mouri

Sugimoto

et al. 2016

Transactions of ISCIE

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“…Let us derive the state equation for kinematic positioning. Since the kinematic case requires mathematical models of the moving objects, we often apply one of the dynamical models which are assumed as first-order Markov processes of, the velocity of u (: v), of the acceleration of u (: a) (the so-called Singer's moving model [10]), or of the jerk of u (: γ), [11,12], with or without the constraints [13,14].…”

Section: State Equationsmentioning

confidence: 99%

Detection and Correction of Doppler Biases in Kalman Filter-based Positioning

Mouri

Stochastic Systems Theory and its Applications (SSS)

Sugimoto

2015

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In this paper, we present methods of detecting and correcting Doppler biases which cause positioning errors in Doppler-aided Kalman filter-based GNSS (Global Navigation Satellite System) positioning. It is well known that Doppler frequency shift observables are more precise compared with C/A code pseudorange observables. Doppler shifts are transformed into range-rates and utilized to smooth code pseudoranges. And Doppler shift observables are immune to cycleslip and continuously available as long as the receiver can track the signals. The precise raw Doppler shift observables can be further exploited for RTK (Real Time Kinematic) positioning to provide robust carrierphase anomaly detection and correction processes [5,6]. Therefore Doppler shift observables can be utilized on a priority basis in Doppler-aided Kalman filter-based positioning than C/A code pseudoranges. However unexpected Doppler bias errors cause position errors or route departures in the positioning. If the Doppler shifts include bias errors, they can be detected by monitoring the innovation processes in Kalman filter. And then they can be corrected by the exclusion and estimation methods.

“…Since the kinematic case requires mathematical models of the moving objects, we often apply one of the dynamical models which are assumed as first-order Markov processes of, the velocity of u (user position), of the acceleration of u (the so-called Singer's moving model [5]), or of the jerk of u, [6,7], with or without the constraints [8,9].…”

Section: State Equationsmentioning

confidence: 99%

Improvement of GPS Precise Point Positioning Accuracy in Urban Canyons by Using Barometric Pressure Sensor

Ozaki

Ohashi

Stochastic Systems Theory and its Applications (SSS)

et al. 2014

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Abstractln this paper, a practical method for improving GPS-PPP(Global Positioning System-Precise Point Positioning) accuracy in urban canyons are presented by using a barometric pressure sensor. Several techniques to improve PPP quality are also integrated into a PPP algorithm which is available in case that there are few (only two or three) visible satellites from automobiles moving on the street in urban canyons. Therefore, this paper verifies the usefulness to integrate barometric pressure information into these methods.