• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
• /
• 2017.10a
• /
• pp.256-257
• /
• 2017

Pressure sensors are usually used in the measurement of drone altitude in an indoor environment since GPS (global positioning system) signal is not available. In this paper, we propose a new method which uses the Chebyshev filter to decrease a high frequency error in the measured values of the pressure sensor. Considering performance of a drone flight controller, the filter order is limited to the $3^{rd}$ order. We explain the transfer function of the $3^{rd}$ order Chebyshev filter.

• Journal of Positioning, Navigation, and Timing
• /
• v.2 no.1
• /
• pp.75-80
• /
• 2013

This article presents the design of long range navigation (LORAN)-disciplined oscillator (LDO), employing the timing information of the LORAN system, which was developed as a backup system that corrects the vulnerability of the global positioning system (GPS)-based timing information utilization. The LDO designed on the basis of hardware generates a timing source synchronized with reference to the timing information of the LORAN-C receiver. As for the LDO-based timing information measurement, the Kalman filter was applied to estimate the measurement of which variance was minimized so that the stability performance could be improved. The oven-controlled crystal oscillator (OCXO) was employed as the local oscillator of the LDO. The controller was operated by digital proportional-integral-derivative (PID) controlling method. The LDO performance evaluation environment that takes into account the additional secondary factor (ASF) of the LORAN signals allows for the relative ASF observation and data collection using the coordinated universal time (UTC). The collected observation data are used to analyze the effect of ASF on propagation delay. The LDO stability performance was presented by the results of the LDO frequency measurements from which the ASF was excluded.

• Journal of Korean Society of Transportation
• /
• v.24 no.3 s.89
• /
• pp.17-27
• /
• 2006

Car following model is a theory that examines changes of condition and interrelationship of acceleration deceleration. headway, velocity and so on closely based on the hypothesis that the Posterior vehicle always follows the preceding vehicle. Car following mode) which is one of the research fields of microscopic traffic flow was first introduced in 1950s and was in active progress in 1960s. However, due to the limitation of data gathering the research depression was prominent for quite a while and then soon was able to tune back on track with development in global positioning system using satellite and generalization of computer use. Recently, there has been many research studies using reception materials of global Positioning system(GPS). Introducing GPS technology to traffic has made real time tracking of a vehicle position possible. Position information is sequential in terms of time and simultaneous measurement of several vehicles in continuous driving is also practicable. Above research was focused on judging whether it is feasible to overcome the following model research by adopting the GPS reception device that was restrictively proceeded due to the limitation of data gathering. For practical judgment, we measured the accuracy and confidence level of the GPS reception devices material by carrying out a practical experiment. Car following model is also being applied in simulations of traffic flow analysis, but due to the difficulty of estimating parameters the basis of the above result. it is our goal to produce an accurate calibration of car following model's parameters that is suitable in this domestic actuality.

• International Journal of Control, Automation, and Systems
• /
• v.5 no.4
• /
• pp.388-396
• /
• 2007

This paper describes a multipath estimation method for Global Positioning System (GPS) dual frequency carrier phase measurements. Multipath is a major error source in high precision GPS applications, i.e., carrier phase measurements for precise positioning and attitude determinations. In order to estimate and remove multipath at carrier phase measurements, an array GPS antenna system has been used. The known geometry between the antennas is used to estimate multipath parameters. Dual frequency carrier phase measurements increase the redundancy of measurements, so it can reduce the number of antennas. The unscented Kalman filter (UKF) is recently applied to many areas to overcome some of the limitations of the extended Kalman filter (EKF) such as weakness to severe nonlinearity. This paper uses the UKF for estimating multipath parameters. A series of simulations were performed with GPS antenna arrays located on a straight line with one reflector. The geometry information of the antenna array reduces the number of estimated multipath parameters from four to three. Both the EKF and the UKF are used as estimation algorithms and the results of the EKF and the UKF are compared. When the initial parameters are far from true parameters, the UKF shows better performance than the EKF.

• 제어로봇시스템학회:학술대회논문집
• /
• 2003.10a
• /
• pp.1706-1709
• /
• 2003

This paper demonstrates a unique method for measuring vehicle states such as body sideslip angle and tire sideslip angle using Global Positioning System(GPS) velocity information in conjunction with other sensors. A method for integrating Inertial Navigation System (INS) sensors with GPS measurements to provide higher update rate estimates of the vehicle states is presented, and the method can be used to estimate the tire cornering stiffness. The experimental results for the GPS velocity-based sideslip angle measurement. From the experimental results, it can be concluded that the proposed method has an advantage for future implementation in a vehicle safety system.

• Journal of Advanced Navigation Technology
• /
• v.21 no.3
• /
• pp.251-257
• /
• 2017

Recently, hybrid positioning system combining GPS, vision sensor, and inertial sensor has drawn many attentions to estimate accurate vehicle positions. Since accurate multi-sensor fusion requires efficient time synchronization, this paper proposes an efficient method to obtain time synchronized measurements of vision sensor, inertial sensor, and OBD device based on GPS time information. In the proposed method, the time and position information is obtained by the GPS receiver, the attitude information is obtained by the inertial sensor, and the speed information is obtained by the OBD device. The obtained time, position, speed, and attitude information is converted to the color information. The color information is inserted to several corner pixels of the corresponding image frame. An experiment was performed with real measurements to evaluate the feasibility of the proposed method.

• Journal of Broadcast Engineering
• /
• v.9 no.4 s.25
• /
• pp.411-423
• /
• 2004

In Korea, Eureka-147 DAB (Digital Audio Broadcasting) temporarily decided as the standard system for digital audio broadcasting was evolved into DMB (Digital Multimedia Broadcasting) to complement the technical vulnerability in mobile reception of terrestrial DTV. According to introducing video service in T-DMB (Terrestrial DMB), 'Terrestrial DMB Experimental Broadcasting for Video Service', a national project of the MIC (Ministry of Information and Communication), was done for verifying the possibility of video service via T-DMB. The main objective of the project is computing the effective field strength and coverage for making a plan to build T-DMB broadcasting network and developing transmitting and receiving equipment. In case of digital broadcasting, it is absolutely essential to measure BER (Bit Error Rate) and electric field strength in order to evaluate coverage and quality of received signal. In this paper, we implement an integrated mobile measurement system for T-DMB. For this purpose, we propose efficient data structure and algorithm for BER measurement. By adding GPS (Global Positioning System) and electric field strength measurement parts into BER measurement part, we complete the integrated mobile measurement system, and then verify it by experiments and field tests. The developed system was used in a national project, 'Terrestrial DMB Experimental Broadcasting for Video Service' and measurement results will be used as fundamental data for building T-DMB broadcasting network.

• Journal of Astronomy and Space Sciences
• /
• v.20 no.4
• /
• pp.359-364
• /
• 2003

In this paper, we present multi-sensor data fusion for telematics application. Successful telematics can be realized through the integration of navigation and spatial information. The well-determined acquisition of vehicle's position plays a vital role in application service. The development of GPS is used to provide the navigation data, but the performance is limited in areas where poor satellite visibility environment exists. Hence, multi-sensor fusion including IMU (Inertial Measurement Unit), GPS(Global Positioning System), and DMI (Distance Measurement Indicator) is required to provide the vehicle's position to service provider and driver behind the wheel. The multi-sensor fusion is implemented via algorithm based on Kalman filtering technique. Navigation accuracy can be enhanced using this filtering approach. For the verification of fusion approach, land vehicle test was performed and the results were discussed. Results showed that the horizontal position errors were suppressed around 1 meter level accuracy under simulated non-GPS availability environment. Under normal GPS environment, the horizontal position errors were under 40㎝ in curve trajectory and 27㎝ in linear trajectory, which are definitely depending on vehicular dynamics.

• Journal of Astronomy and Space Sciences
• /
• v.26 no.1
• /
• pp.59-74
• /
• 2009

Relative navigation system is presented using GPS measurements from a single-channel global positioning system (GPS) simulator. The objective of this study is to provide the real-time inter-satellite relative positions as well as absolute positions for two formation flying satellites in low earth orbit. To improve the navigation performance, the absolute states are estimated using ion-free GRAPHIC (group and phase ionospheric correction) pseudo-ranges and the relative states are determined using double differential carrier-phase data and singled-differential C/A code data based on the extended Kalman filter and the unscented Kalman filter. Furthermore, pseudo-relative dynamic model and modified relative measurement model are developed. This modified EKF method prevents non-linearity of the measurement model from degrading precision by applying linearization about absolute navigation solutions not about the priori estimates. The LAMBDA method also has been used to improve the relative navigation performance by fixing ambiguities to integers for precise relative navigation. The software-based simulation has been performed and the steady state accuracies of 1 m and 6 mm ($1{\sigma}$ of 3-dimensional difference errors) are achieved for the absolute and relative navigation using EKF for a short baseline leader/follower formation. In addition, the navigation performances are compared for the EKF and the UKF for 10 hours simulation, and relative position errors are mm-level for the two filters showing the similar trends.

• Journal of Advanced Navigation Technology
• /
• v.23 no.3
• /
• pp.221-227
• /
• 2019

In this paper, interacting multiple model (IMM) filter was designed that guarantees a stable navigation performance even in the unstable satellite navigation position. In order to design IMM filter in INS / GPS integrated navigation system, sub filter of the IMM filter is defined as Kalman filter. In the IMM filter configuration, two subfilters are determined. Each Kalman filter defines the six-teenth state composed of position, velocity, attitude, and sensor error from the INS error equation and the states additionally derived in case of the coloured measurement noise. In order to verify the performance of the proposed filter, we compared the performance how the filter works in the presence of arbitrary error in GPS navigation solution. The Monte Carlo simulation was performed 100 times and the results were compared with the root mean square(RMS). The results show that the proposed method is stable against errors and show fast convergence.