• International Journal of Aeronautical and Space Sciences
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• v.13 no.4
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• pp.499-506
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• 2012

In this paper, a dynamic modeling for the velocity and position information of a single frequency stand-alone GPS(Global Positioning System) receiver is described. In static condition, the position error dynamic model is identified as a first/second order transfer function, and the velocity error model is identified as a band-limited Gaussian white noise via non-parametric method of a PSD(Power Spectrum Density) estimation in continuous time domain. A Kalman filter is proposed considering both correlated/white measurements noise based on identified GPS error model. The performance of the proposed Kalman filtering method is verified via numerical simulation.

• The Transactions of the Korean Institute of Electrical Engineers D
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• v.51 no.6
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• pp.221-227
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• 2002

In this paper, the system model for the compensation of the low-cost personal navigation system is derived and the error compensation method using GPS is also proposed. WNS(Walking Navigation System) is a kind of personal navigation system using the number of a walk, stride and azimuth. Because the accuracy of these variables determines the navigation performance, computational methods have been investigated. The step is detected using the walking patterns, stride is determined by neural network and azimuth is calculated with gyro output. The neural network filters off unnecessary motions. However, the error compensation method is needed, because the error of navigation information increases with time. In this paper, the accumulated error due to the step detection error, stride error and gyro bias is compensated by the integrating with GPS. Loosely coupled Kalman filter is used for the integration of WNS and GPS. It is shown by simulation that the error is bounded even though GPS signal is blocked.

• Journal of Positioning, Navigation, and Timing
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• v.4 no.1
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• pp.33-41
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• 2015

Compact Network Real-Time Kinematic (RTK) is a method that combines compact RTK and network RTK, and it can effectively reduce the time and spatial de-correlation errors. A network RTK user receives multiple correction information generated from reference stations that constitute a network, calculates correction information that is appropriate for one's own position through a proper combination method, and uses the information for the estimation of the position. This combination method is classified depending on the method for modeling the GPS error elements included in correction information, and the user position accuracy is affected by the accuracy of this modeling. Among the GPS error elements included in correction information, tropospheric delay is generally eliminated using a tropospheric model, and a combination method is then applied. In the case of a tropospheric model, the estimation accuracy varies depending on the meteorological condition, and thus eliminating the tropospheric delay of correction information using a tropospheric model is limited to a certain extent. In this study, correction information modeling accuracy performances were compared focusing on the Low-Order Surface Model (LSM), which models the GPS error elements included in correction information using a low-order surface, and a modified LSM method that considers tropospheric delay characteristics depending on altitude. Both of the two methods model GPS error elements in relation to altitude, but the second method reflects the characteristics of actual tropospheric delay depending on altitude. In this study, the final residual errors of user measurements were compared and analyzed using the correction information generated by the various methods mentioned above. For the performance comparison and analysis, various GPS actual measurement data were collected. The results indicated that the modified LSM method that considers actual tropospheric characteristics showed improved performance in terms of user measurement residual error and position domain residual error.

• Journal of Positioning, Navigation, and Timing
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• v.2 no.1
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• pp.59-65
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• 2013

The signal broadcast from a GPS satellite experiences code delay and carrier phase advance while passing through the ionosphere, which causes a signal error. Many ionosphere models have been studied to correct this ionospheric delay error. In this paper, the ionosphere modeling for the Korean Peninsula was carried out using a spherical harmonics based model. In contrast to the previous studies, we considered a real-time ionospheric delay correction model using fewer number of basis functions. The modeling performance was evaluated by comparing with a grid model. Total number of basis functions was set to be identical to the number of grid points in the grid model. The performance test was conducted using the GPS measurements collected from 5 reference stations during 24 hours. In the test result, the modeling residual error was smaller than that of the existing grid model. However, when the number of measurements was small and the measurements were not evenly distributed, the overall trend was found to be problematic. For improving this problem, we implemented the modeling with additional virtual measurements.

• Journal of Advanced Navigation Technology
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• v.16 no.4
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• pp.602-610
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• 2012

Ionospheric delay error, one of main error sources in GPS signal, varies with signal frequency. Dual-frequency user uses L1, L2 frequency pseudorange to estimate the ionospheric delay, and there are errors caused by pseudorange measurement noise. So, filter is usually used to smooth the measurement. Weighted hatch filter can estimate optimal smoothed pseudorange measurement. But measurement noise model is needed to use this filter. In this paper, measurement noise modeling is conducted for NDGPS reference station. Using noise modeling result, weighted hatch filter estimate smoothed pseudorange measurement and ionospheric delay. Standard deviation of ionospheric dealy error drops to one-twenty fifth of non-filtered result.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.14 no.10
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• pp.2223-2229
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• 2010

The integrity monitoring of anomalous GPS signal have been researched because of the degradation of GPS satellite performance. It is known that anomalous GPS signal can occur by failure of GPS satellite, sudden increase of ionosphere delay error, SA, wrong modeling for navigation parameters from control segment, and an electromagnetic wave interference, etc. In case of GPS anomaly by satellites can arise from carrier frequency, code and navigation message. In this paper, the scenarios with navigation message errors were made by using GPS simulator, and the influences of GPS navigation message error to receiver were analysed. The anomalies of preamble, bits related TOW count message, subframe ID in HOW, bits related satellite healthy, and the other navigation message errors were described and simulated. Also, the number of satellites, DOP and pseudorange are analyzed to know how the anomalous signal can affect on GPS receiver.

• Journal of Institute of Control, Robotics and Systems
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• v.19 no.5
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• pp.481-487
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• 2013

This paper presents an FIR (Finite Impulse Response) fixed-interval smoothing filter for fast and exact estimating state variables of a discrete nonlinear system with modeling uncertainty. Conventional IIR (Infinite Impulse Response) filter and smoothing filter can estimate state variables of a system with an exact model when the system is observable. When there is an uncertainty in the system model, however, conventional IIR filter and smoothing filter may cause large errors because the filters cannot estimate the state variables corresponding to the uncertain model exactly. To solve this problem, FIR filters that have fast estimation properties and have robustness to the modeling uncertainty have been developed. However, there is time-delay estimation phenomenon in the FIR filter. The FIR smoothing filter proposed in this paper makes up for the drawbacks of the IIR filter, IIR smoothing filter, and FIR filter. Therefore, the FIR smoothing filter has good estimation performance irrespective of modeling uncertainty. The proposed FIR smoothing filter is applied to the integrated navigation system composed of a magnetic compass based DR (Dead Reckoning) and a GPS (Global Positioning System) receiver. Even when the magnetic compass error that changes largely as the surrounding magnetic field is modeled as a random constant, it is shown that the FIR smoothing filter can estimate the varying magnetic compass error fast and exactly with simulation results.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.9 no.3
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• pp.528-533
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• 2005

The purpose of the study is to develop ship's bearing sensor using GPS receiver which can play a role as a ship's secondary compass. In this research, two GPS receivers are used to determine the bearing in real time. Then we investigated the bearing accuracy associated with the error pattern of two GPS receivers. Especially, the results are as follows the investigation on the system design of GPS-Compass, the modeling to compute heading of sailing, the analysis on bearing accuracy with the error pattern, the defining possibility to play a role as a ship's secondary compass.

• Journal of Institute of Control, Robotics and Systems
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• v.21 no.2
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• pp.81-86
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• 2015

GPS position errors were corrected for guidance of autonomous vehicles. From the vision, we can obtain the lateral distance from the center of lane and the angle difference between the left and right detected line. By using a controller which makes these two measurements zero, a lane following system can be easily implemented. However, the problem is that if there's no lane, such as crossroad, the guidance system of autonomous vehicle does not work. In addition, Line detection has problems working on curved areas. In this case, the lateral distance measurement has an error because of a modeling mismatch. For this reason, we propose GPS error correction filter based on curve-modeled lane detection and evaluated the performance applying it to an autonomous vehicle at the test site.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2004.05b
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• pp.101-105
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• 2004

The purpose of the study is to develop ship's bearing sensor using CPS receiver which can play a role as a ship's secondary compass. In this research, two GPS receivers are used to determine the bearing in real time. Then we investigated the bearing accuracy associated with the error pattern of two GPS receivers. Especially, the results are as follows ; - The investigation on the system design of GPS-Compass - The modeling to compute heading of sailing - The analysis on bearing accuracy with the error pattern - The defining possibility to play a role as a ship's secondary compass