• Journal of the Korea Institute of Military Science and Technology
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• v.16 no.2
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• pp.95-100
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• 2013

Localization is very important for the autonomous navigation of Unmanned Ground Vehicles; however, it is difficult that they have a precise Inertial Navigation System(INS) sensor, especially Small Unmanned Ground Vehicle(SUGV). Moreover, there are some condition such as denial of global position system(GPS), GPS/INS integrated system is not robust. This paper proposes the estimation algorithm with optical flow sensor and INS. Being compared with previous researches, the proposed algorithm is suitable for skid steering vehicles. We revised the measurement model of previous research for the accuracy of side direction position. Experimental results were performed to verify the algorithm, and the result showed an excellent performance.

• Journal of Positioning, Navigation, and Timing
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• v.13 no.2
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• pp.137-147
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• 2024

This paper presents a novel Long Short-Term Memory (LSTM) network architecture for the integration of an Inertial Measurement Unit (IMU) and Global Navigation Satellite Systems (GNSS). The proposed algorithm consists of two independent LSTM networks and the LSTM networks are trained to predict attitudes and velocities from the sequence of IMU measurements and mechanization solutions. In this paper, three GNSS receivers are used to provide Real Time Kinematic (RTK) GNSS attitude and position information of a vehicle, and the information is used as a target output while training the network. The performance of the proposed method was evaluated with both experimental and simulation data using a lowcost IMU and three RTK-GNSS receivers. The test results showed that the proposed LSTM network could improve positioning accuracy by more than 90% compared to the position solutions obtained using a conventional Kalman filter based IMU/GNSS integration for more than 30 seconds of GNSS outages.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.10 no.4
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• pp.693-699
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• 2006

Digital airborne image must be precisely orthorectified to become geographical information. For orthorectification of airborne images, GPS/INS (Global Positioning System/Inertial Navigation System) and LIDAR (LIght Detection And Ranging) elevation data were employed. In this study, 635 frame airborne images were produced and LIDAR data were converted to raster image for applying to image orthorectification. To derive images with constant brightness, flat field correction was applied to images. The airborne images were geometrically corrected by calculating internal orientation and external orientation using GPS/INS data and then orthorectified using LIDAR digital elevation model image. The precision of orthorectified images was validated by collecting 50 ground control points from arbitrary five images and LIDAR intensity image. As validation result, RMSE (Root Mean Square Error) was 0.387 as almost same as only two times of pixel spatial resolution. It is possible that this automatic orthorectification method of airborne image with higher precision is applied to airborne image industry.

• Proceedings of the Korean Institute of Navigation and Port Research Conference
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• v.1
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• pp.115-120
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• 2006

This article propose a new idea of developing a hybrid scheme to achieve faster INS alignment with higher accuracy using a novel procedure to estimate the initial attitude angles that combines a Kalman filter and Adaptive Neuro-Fuzzy Inference System architecture. A tactical grade inertial measurement unit was applied to verify the performance of proposed scheme in this study. The preliminary results indicated the outstanding improvements in both time consumption for fine alignment process and accuracy of estimated attitude angles, especially in heading angles. In general, the improvement in terms of time consumption and the accuracy of estimated attitude estimated accuracy reached 80% and 70% respectively during alignment process after compensating the attitude angles estimated by an extended Kalman filter with 15 states using proposed approach. It is worth mentioned that the proposed approach can be implemented in general real time navigation applications.

• Journal of Advanced Navigation Technology
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• v.20 no.1
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• pp.37-44
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• 2016

Republic of Korea has established its performance-based navigation (PBN) implementation plan in 2010 for ensuring a smooth transition to PBN operations and relevant new flight procedures are being developed in accordance with the roadmap. Various Navigation aids (NAVAIDs) like global navigation satellite systems (GNSS), distance measuring equipment (DME), VHF omnidirectional range (VOR), inertial navigation system (INS) are used to support PBN procedures. Among them, GNSS would play a central role in PBN implementation. However, vulnerability of satellite navigation signals to artificial and natural interferences has been discovered and various alternative positioning, navigation and timing (APNT) technologies are under development in many countries. In this paper, we study whether continuous PBN operations can be achievable without GNSS signals. As a result, it shows that some of the domestic airports require the construction of APNT in the approach area.

• Aerospace Engineering and Technology
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• v.10 no.2
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• pp.1-10
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• 2011

This is a comparative study of three inertia navigation units and focuses on the verification of reliability about GPS/INS for the SmartUAV(DGNS). Those GPS/INS have been tested using a manned aircraft and an automobile. The comparative aspect of units include details about the GPS positions and the inertia sensor performance. With the flight scenario, the DGNS guarantees the reliability of the navigation operation and performs the flight test for the development of the SmartUAV.

• Journal of the Korean Institute of Intelligent Systems
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• v.18 no.5
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• pp.706-711
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• 2008

This paper is presented an accurate localization scheme for mobile robots based on the fusion of ultrasonic satellite (U-SAT) with inertial navigation system (INS), i.e., sensor fusion. Our aim is to achieve enough accuracy less than 100 mm. The INS consist of a yaw gyro, two wheel-encoders. And the U-SAT consist of four transmitters, a receiver. Besides the localization method in this paper fuse these in an extended Kalman filter. The performance of the localization is verified by simulation and two actual data(straight, curve) gathered from about 0.5 m/s of driving actual driving data. localization methods used are general sensor fusion and sensor fusion through Kalman filter using data from INS. Through the simulation and actual data studies, the experiment show the effectiveness of the proposed method for autonomous mobile robots.

• Journal of Institute of Control, Robotics and Systems
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• v.19 no.2
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• pp.140-145
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• 2013

This paper proposes an efficient integration method for GPS (Global Positioning System) and INS (Inertial Navigation System). To obtain accuracy and computational conveniency at the same time with low cost global positioning system receivers and micro mechanical inertial sensors, a new mechanization method and a new filter architecture are proposed. The proposed mechanization method simplifies velocity and attitude computation by eliminating the need to compute complex transport rate related to the locally-level frame which continuously changes due to unpredictable vehicle motions. The proposed filter architecture adopts two heterogeneous filters, i.e. position-domain Hatch filter and velocity-aided Kalman filter. Due to distict characteristics of the two filters and the distribution of computation into the two hetegrogeneous filters, it eliminates the cascaded filter problem of the conventional loosly-coupled integration method and mitigates the computational burden of the conventional tightly-coupled integration method. An experiment result with field-collected measurements verifies the feasibility of the proposed method.

• 제어로봇시스템학회:학술대회논문집
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• 2001.10a
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• pp.116.4-116
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• 2001

We consider a robust configuration problem of inertial sensors for inertial navigation system(INS). Fault detection and isolation(FDI) is necessary to improve reliability of the system. For FDI, there used to be more than three mutually orthogonal sensors and thus we have to consider configuration methods of sensors. Various studies in this area have been done, but the former results did not consider effect of uncertainty(misalignment, scale factor error) to determine the configuration of the sensors. In this paper robust configuration of sensors is proposed through sensitivity analysis. Also total least square(TLS) method ...

• Proceedings of the Korean Society of Precision Engineering Conference
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• 2005.06a
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• pp.1429-1432
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• 2005

This work is towards the development of a low-cost, small-sized inertial navigation system(INS) which consists of 3 accelerometers, 3 semiconductor gyros and a magnetic compass sensor. This paper explains in detail the structure of the developed system and proposes a 3 dimensional attitude estimation algorithm with Indirect Kalman Filter. The experiments are performed with the developed system attached to a 6 DOF robot for showing the effectiveness of the algorithm.