A GPS-slaved time synchronization system for hybrid navigation

Li, Binghao; Rizos, Chris; Lee, Hung Kyu

doi:10.1007/s10291-006-0022-z

Cited by 36 publications

(11 citation statements)

References 5 publications

(7 reference statements)

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“…Accelerometers usually act as part of the IMU, so the time synchronization problem between GNSS and accelerometers is also the problem between GNSS and IMU. Time synchronization between IMU and the GNSS is the primary issue that needs to be addressed before data fusion [122][123][124][125][126].…”

Section: Time Synchronizationmentioning

confidence: 99%

“…The one pulse per second (1PPS) output of GPS receiver was introduced to solve the time synchronization problem of multi-sensor system. The main processing idea of this problem is to output a PPS from the GPS receiver as input to other sensors in the multi-sensor system as the reference time for others [124,125]. The main formula is as follows: is the computer time of PPS; for more details, please refer to the references [123][124][125][126].…”

Section: Time Synchronizationmentioning

confidence: 99%

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A Review of Global Navigation Satellite System (GNSS)-Based Dynamic Monitoring Technologies for Structural Health Monitoring

et al. 2019

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In the past few decades, global navigation satellite system (GNSS) technology has been widely used in structural health monitoring (SHM), and the monitoring mode has evolved from long-term deformation monitoring to dynamic monitoring. This paper gives an overview of GNSS-based dynamic monitoring technologies for SHM. The review is classified into three parts, which include GNSS-based dynamic monitoring technologies for SHM, the improvement of GNSS-based dynamic monitoring technologies for SHM, as well as denoising and detrending algorithms. The significance and progress of Real-Time Kinematic (RTK), Precise Point Position (PPP), and direct displacement measurement techniques, as well as single-frequency technology for dynamic monitoring, are summarized, and the comparison of these technologies is given. The improvement of GNSS-based dynamic monitoring technologies for SHM is given from the perspective of multi-GNSS, a high-rate GNSS receiver, and the integration between the GNSS and accelerometer. In addition, the denoising and detrending algorithms for GNSS-based observations for SHM and corresponding applications are summarized. Challenges of low-cost and widely covered GNSS-based technologies for SHM are discussed, and problems are posed for future research.

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Section: Time Synchronizationmentioning

confidence: 99%

Section: Time Synchronizationmentioning

confidence: 99%

A Review of Global Navigation Satellite System (GNSS)-Based Dynamic Monitoring Technologies for Structural Health Monitoring

et al. 2019

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“…Since many sensors are used in relative navigation, time synchronization is very important. Related to the time synchronization in multi-sensor fusion, an analytic calibration method was proposed by Lee et al (2002), a GPS-slaved time synchronization method was introduced by Li et al (2006), a method using a counter and two latching registers was employed by Ding et al (2008), and a method to estimate the constant time synchronization error by time stamp filtering was proposed by Nilsson and Handel (2010).…”

Section: Introductionmentioning

confidence: 99%

Adaptive GPS/INS integration for relative navigation

et al. 2015

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Relative navigation based on GPS receivers and inertial measurement units is required in many applications including formation flying, collision avoidance, cooperative positioning, and accident monitoring. Since sensors are mounted on different vehicles which are moving independently, sensor errors are more variable in relative navigation than in single-vehicle navigation due to different vehicle dynamics and signal environments. In order to improve the robustness against sensor error variability in relative navigation, we present an efficient adaptive GPS/INS integration method. In the proposed method, the covariances of GPS and inertial measurements are estimated separately by the innovations of two fundamentally different filters. One is the position-domain carrier-smoothed-code filter and the other is the velocity-aided Kalman filter. By the proposed two-filter adaptive estimation method, the covariance estimation of the two sensors can be isolated effectively since each filter estimates its own measurement noise. Simulation and experimental results demonstrate that the proposed method improves relative navigation accuracy by appropriate noise covariance estimation.

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“…To maximize the performance of GPS/INS integrated systems, time synchronization between GPS and INS is an important issue [4,5,6,7]. Various methods have been developed to reduce the effect of the time synchronization error in fusion of multiple sensors [8,9,10].…”

Section: Introductionmentioning

confidence: 99%

The effect of measurement for time synchronization error in the tightly coupled GPS/INS integration

Yang

Shim

2013

2013 9th Asian Control Conference (ASCC)

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The performance of tightly coupled GPS/INS integration becomes worse if the time synchronization error occurs between the GPS receiver and INS(Inertial Navigation System). In this paper the effect of measurement due to time synchronization error is investigated for tightly coupled GPS/INS integration. Two kinds of measurement isused; one is pseudorange only, and the other is both pseudorange and pseudorange rate.

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A GPS-slaved time synchronization system for hybrid navigation

Cited by 36 publications

References 5 publications

A Review of Global Navigation Satellite System (GNSS)-Based Dynamic Monitoring Technologies for Structural Health Monitoring

A Review of Global Navigation Satellite System (GNSS)-Based Dynamic Monitoring Technologies for Structural Health Monitoring

Adaptive GPS/INS integration for relative navigation

The effect of measurement for time synchronization error in the tightly coupled GPS/INS integration

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