• 제어로봇시스템학회:학술대회논문집
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• 2000.10a
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• pp.409-409
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• 2000

In this paper, the implementation of a tightly coupled real-time GPS/INS integrated system is discussed. The hardware is developed for any GPS receiver and any IMU. The navigation software is modularized by tasks, so that can be easily modified when the integrated system is restructured. A van test was performed to show the feasibility of the proposed system.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.22 no.1
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• pp.53-62
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• 2004

This paper deals with a new approach to acquire the exterior orientation parameters based on GPS(Global Positioning System) in combination with IMU(Inertial Measuring Unit), which enables us to achieve the same accuracy with minimal ground control points comparing to the conventional photogrammetric method. To prove the possibility of practical use of GPS/INS photogrammetry, a survey flight was conducted loading with all necessary photographing systems. The observed data set by GPS/IMU were analyzed and verified :he accuracy performance of kinematic GPS, and also compared to those of conventional photogrammetry in various points of view.

• Proceedings of the KSME Conference
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• 2003.11a
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• pp.1524-1529
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• 2003

In this paper deals with a unique method for measuring vehicle states such as body sideslip angle and tire sideslip angle using 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 and cornering stiffness estimates are compared with the theoretical predictions. 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 the Institute of Electronics Engineers of Korea SC
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• v.41 no.1
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• pp.1-8
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• 2004

The INS(Inertial Navigation System) provides high rate position, velocity and attitude data with good short-term stability while the GPS(Global Position System) provides position and velocity data with long-term stability. By integrating the INS with GPS, a navigation system can be achieved to Provide highly accurate navigation Performance. For the best performance, time synchronization of GPS and INS data is very important in GPS/INS integrated system But, it is impossible to synchronize them exactly due to the communication and computation time-delay. In this paper, to reduce the error caused by the measurement time-delay in GPS/INS integrated systems, error compensation methods using separate bias Kalman filter are suggested for both the loosely-coupled and the tightly-coupled GPS/INS integration systems. Linearized error models for the position and velocity matching GPS/INS integrated systems are Int derived by linearizing with respect to its time-delay and augmenting the delay-state into the conventional state equations for each case. And then separate bias Kalman Inter is introduced to estimate the time-delay during only initial navigation stage. The simulation results show that the present method is effective enough resulting in considerably less position error.

• Journal of the Institute of Electronics and Information Engineers
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• v.49 no.11
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• pp.159-166
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• 2012

There are several ways such as GPS(Global Positioning System) and INS (Inertial Navigation System) to track the location of moving vehicle. The GPS has the advantages of having non-accumulative error even if it brings about errors. In order to obtain the position information, we need to receive at least 3 satellites information. But, the weak point is that GPS is not useful when the 혠 signal is weak or it is in the incommunicable region such as tunnel. In the case of INS, the information of the position and posture of mobile with several Hz~several hundreds Hz data speed is recorded for velocity, direction. INS shows a very precise navigational performance for a short period, but it has the disadvantage of increasing velocity components because of the accumulated error during integration over time. In this paper, sensor fusion algorithm is applied to both of INS and GPS for the position information to overcome the drawbacks. The proposed system gets an accurate position information from experiment using SVD in a non-accessible GPS terrain.

• Journal of the Institute of Electronics and Information Engineers
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• v.52 no.5
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• pp.190-196
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• 2015

In this paper, we propose multiple location error compensation algorithm for GPS/INS fusion using kalman filter and introduce the way to reduce location error in 9-axis navigation devices for implementing inertial navigation technique. When evaluating location, there is an increase of location error. So navigation systems need robust algorithms to compensate location error in GPS/INS fusion. In order to improve robustness of 9-axis inertial sensor(mpu-9150) over its disturbance, we used tilt compensation method using compensation algorithm of acceleration sensor and Yaw angle compensation to have exact azimuth information of the object. And it shows improved location result using these methods combined with kalman filter.

• Proceedings of the KIEE Conference
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• 2001.07d
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• pp.1984-1986
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• 2001

In order to provided continuous solutions, latest developing navigation systems tend to integrate GPS receiver with INS or DR. Using the GPS carrier-phase measurements, an attitude GPS receiver with three antennas obtain the 3-dimensional attitude such as roll, pitch, and heading as well as position and velocity. With these angle measurements, in the attitude GPS/INS integrated system, attitude or gyro errors can be directly compensated. In this paper, we develop an integrated navigation system that combines attitude GPS receiver with INS. The performance of real-time integrated navigation system is determined by not only the implements of integration filter but also the synchronization of measurements. To meet these real-time requirements, the navigation software is implemented in multi-tasking structure in this paper. We also employ time-synchronization technique in the multi-sensor fusion. Experimental results show that the performance of the attitude GPS/INS integrated system is consistent even when cycle-slip occurs in carrier-phase measurements.

• Journal of the Institute of Electronics and Information Engineers
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• v.50 no.6
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• pp.267-275
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• 2013

EKF has been widely used for GPS/INS integration as standard method but EKF has one well-known drawback. if the errors are not within the bounded region, the filter may be divergent. The particle filter has the advantage of the nonlinear and non-gaussian system. This paper proposes a method for compensating the GPS position errors based on the particle filter and presents loosely-coupled GPS/INS integration using proposed algorithm. We used GPS position pattern with particle filter and added attitude kalman filter for improving attitude accuracy. To verify the performance, the proposed method is compared with high cost GPS as reference. In the experimental result, we verified that the accuracy and robust were well improved by the proposed method filter effectively and robustness than by original loosely-coupled integration when vehicle turns at corner.

• Journal of the Korean Institute of Intelligent Systems
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• v.19 no.3
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• pp.408-414
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• 2009

A GPS/INS system is widely used in the UGV to estimate position during the mission. However, there are few restrictions when a GPS/INS system used alone. For example, GPS provides precise location information but easily interrupted by external factors like weather, environment, etc. INS provides continuous location data but positioning errors grew very rapidly with time. Therefore, it is necessary to integrating multi-sensors for more continuous and correct position estimation. In this paper, we propose location estimation algorithm of the UGV for GPS/INS integrated system that combines Fuzzy Inference and Unscented Particle Filter(UPF) to improve navigation. Fuzzy inference provides the simplest method integrating GPS/INS and UPF is non-linear estimation filter well suited to the correction of errors. The performance of the proposed algorithm was tested to compare with other algorithms. the results show that the proposed algorithm is more accuracy in position estimation and ensures continuous position tracking.

• Proceedings of the Korean Institute of Navigation and Port Research Conference
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• v.2
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• pp.439-442
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• 2006

본 논문에서는 IIR/FIR 필터 융합을 위한 기법을 제안하고 이를 INS/GPS 결합항법장치에 적용한다. IIR 형태의 EKF와 FIR 형태의 RHKF 필터를 각 필터의 잉여값과 잉여값 공분산을 이용한 적응형 융합 확률을 계산하여 융합함으로써 두 필터의 장점을 갖도록 한다. 이 융합 기법을 적용한 INS/GPS 결합항법장치는 기존의 단독 필터를 사용하는 것보다 강인한 특성을 갖고 항법정보를 제공한다.