• 제어로봇시스템학회:학술대회논문집
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• 2001.10a
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• pp.114.3-114
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• 2001

The pure navigation system using Inertial Navigation Unit(INU) which has very accurate short term stabilities but not long term gives rise to position errors propotional to time. On the contrary, Global Positioning System(GPS) which is bounded its errors to some fixed ranges shows higher accuracy in the long term, and lower accuracy in the short term than that of INS. Recently the integration of these two systems is one of the main topic in the field of navigation system. In this thesis, the implementation of kalman filter on the real time navigation computer and step jump error compensation method is suggested.

• Journal of Navigation and Port Research
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• v.35 no.3
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• pp.187-195
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• 2011

A ship handling simulator is popular means of preventing marine accidents caused by human error. It can also be used to train navigators. A real-time 3D visualization system, a component of a ship handling simulator, is an important component, as realistic and intuitive image generation play an essential role in improving the effects of education using ship handling simulators. This paper discusses the design of a new real-time 3D visualization system based on an open source 3D graphics engine as well as its implementation. The developed real-time 3D visualization system satisfies the operational requirements derived in terms of visualization functionalities, reuse of legacy graphic data, and interoperability with other systems constituting a ship handling simulator. This system has an architecture in which new functionalities are easily added.

• Journal of Advanced Navigation Technology
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• v.19 no.5
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• pp.411-416
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• 2015

The service size of an IoT environment is determined by the various types of sensors. A gateway for relaying sensor information from various sensors is a representative middleware system, and an infographics showing the information with a graphical presentation of data and information is a client system for representing real-time information efficiently, it is necessary a similar test bed with IoT environment to develop a real-time infographics displaying a large amount of information effectively. The testing tools used in developing the existing network systems are mostly made to be suitable for functional testing and performance testing of the driven unit. In this paper, we proposed a mean which is web-based simulation framework to create a variety of information required for real-time infographics development, and evaluate the function of the system proposed by the test function of the comparison with the previous network test tool.

• Journal of Advanced Navigation Technology
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• v.17 no.4
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• pp.435-441
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• 2013

This paper proposes a neural net based-predictive connection admission control (CAC) scheme for multiclass users in wireless cognitive radio networks. We classifies cognitive users(cu) into real and non real time services, and then permit only real time services to reserve the demanded resource for spectrum handoff in guard channel for provisioning the desired QoS. Neural net is employed to predict primary user's arrival on time and demanded channels. Resource scheduling scheme is based on $C_IA$(cognitive user I complete access) shown in this paper. For keeping primary users from interference, the CAC is performed on only cognitive user not primary user. Simulation results show that our schemes can guarantee the desired QoS by cognitive real time services.

• Journal of Navigation and Port Research
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• v.46 no.3
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• pp.243-250
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• 2022

The purpose of this study was to propose technology to detect the wave in the image in real-time, and calculate the height of the wave-overtopping through image analysis using artificial intelligence. It was confirmed that the proposed wave overtopping detection system proposed in this study could detect the occurring of wave overtopping, even in severe weather and at night in real-time. In particular, a filtering algorithm for determining if the wave overtopping event was used, to improve the accuracy of detecting the occurrence of wave overtopping, based on a convolutional neural networks to catch the wave overtopping in CCTV images in real-time. As a result, the accuracy of the wave overtopping detection through AP50 was reviewed as 59.6%, and the speed of the overtaking detection model was 70fps based on GPU, confirming that accuracy and speed are suitable for real-time wave overtopping detection.

• Journal of the Korea Institute of Military Science and Technology
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• v.2 no.2
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• pp.186-196
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• 1999

The CPS provides data with long-term stability independent of passed time and the INS provides high-rate data with short-term stability. By integrating these complementary systems, a highly accurate navigation system can be achieved. In this paper, a loosely-coupled GPS/INS integration system is designed. It is a simple structure and is easy to implement and preserves independent navigation capability of GPS and INS. The integration system consists of a NCU, an IMU, a GPS receiver, and a monitoring system. The navigation algorithm in the NCU is designed under the multi-tasking environment based on a real-time kernel system and the monitoring system is designed using the Visual C++. The integrated Kalman filter is designed as a feedback formed 15-state filter, in which the states are position errors, velocity errors, attitude errors and sensor bias errors. The van test result shows that the integrated system provides more accurate navigation solution then the inertial or the GPS-alone navigation system.

• Journal of Positioning, Navigation, and Timing
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• v.9 no.4
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• pp.357-366
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• 2020

This paper addressed a relative navigation method for autonomous rendezvous and docking of cube-satellites using single frequency Differential GPS (DGPS) under the intermittent communication between satellites. Since the ionospheric error of GPS measurement is variable depending on the visible satellites, a few meters error of relative navigation is occurred in the Low-Earth Orbit (LEO) environment. Therefore, it is essential to remove the ionospheric error to perform relative navigation. Besides, an intermittent communication period for receiving GPS measurements of the target satellite is limited for getting information every sampling time. To solve this problem, a method combining range domain DGPS and orbit propagation is proposed in this paper. The proposed method improves the performance of DGPS by using Hatch filter and solves an intermittent communication problem by estimating the relative position and velocity using Hill-Clohessy-Wiltshire Equation. Through the simulation, it is verified that the suggested algorithm provides the relative position error within RMS 0.5 m and the relative velocity error within RMS 3 cm/s. Furthermore, it has the advantage that it is suitable for real-time implementation using single-frequency GPS measurements and is computationally efficient.

• Journal of the Institute of Electronics Engineers of Korea SP
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• v.39 no.3
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• pp.66-77
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• 2002

This paper deals with an implementation of the navigation parameter extraction technique using the TMS320C80 multimedia video processor (MVP). Especially, this Paper focuses on the relative position estimation algorithm which plays an important role in real-time operation of the overall system. Based on the relative position estimation algorithm using the images obtained at two locations, we develop a fast algorithm that can reduce large amount of computation time and fit into fixed-point processors. Then, the algorithm is reconfigured for parallel processing using the 4 parallel processors in the MVP. As a result, we shall demonstrate that the navigation parameter extraction system employing the MVP can operate at full-frame rate, satisfying real-time requirement of the overall system.

• Journal of Positioning, Navigation, and Timing
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• v.10 no.4
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• pp.315-333
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• 2021

Due to the Global Navigation Satellite System (GNSS) modernization, recently launched GNSS satellites transmit signals at various frequency bands such as L1, L2 and L5. Considering the Korean Positioning System (KPS) signal and other GNSS augmentation signals in the future, there is a high probability of applying more complex communication techniques to the new GNSS signals. For the reason, GNSS receivers based on flexible Software Defined Radio (SDR) concept needs to be developed to evaluate various experimental communication techniques by accessing each signal processing module in detail. This paper proposes a novel SDR-based A-GNSS receiver capable of processing multi-GNSS/RNSS signals at multi-frequency bands. Due to the modular structure, the proposed receiver has high flexibility and expandability. For real-time implementation, A-GNSS server software is designed to provide immediate delivery of satellite ephemeris data on demand. Due to the sampling bandwidth limitation of RF front-ends, multiple SDRs are considered to process the multi-GNSS/RNSS multi-frequency signals simultaneously. To avoid the overflow problem of sampled RF data, an efficient memory buffer management strategy was considered. To collect and process the multi-GNSS/RNSS multi-frequency signals in real-time, the proposed SDR A-GNSS receiver utilizes multiple threads implemented on a CPU and multiple NVIDIA CUDA GPGPUs for parallel processing. To evaluate the performance of the proposed SDR A-GNSS receiver, several experiments were performed with field collected data. By the experiments, it was shown that A-GNSS requirements can be satisfied sufficiently utilizing only milliseconds samples. The continuous signal tracking performance was also confirmed with the hundreds of milliseconds data for multi-GNSS/RNSS multi-frequency signals and with the ten-seconds data for multi-GNSS/RNSS single-frequency signals.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.30 no.6A
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• pp.481-487
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• 2005

In order to increase the autonomous navigation capability of a mobile robot, it is very crucial to develop a method for recognizing a priori known environmental characteristics. This paper proposes an ultrasonic sensor based real-time method for recognizing a priori known indoor environmental characteristics like a wall and corner. The ultrasonic sensor consists of an ultrasonic transmitter and two ultrasonic receivers placed symmetrically about the transmitter. Unlike previous methods the information obtained from the sensor is processed in real-time by extended Kalman filter to be able to correct the position and orientation of robot with respect to known environmental characteristics.