• IEMEK Journal of Embedded Systems and Applications
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• v.10 no.6
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• pp.373-379
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• 2015

A hybrid navigation system is implemented to apply for a mobile robot. The hybrid navigation system consists of an inertial navigation system and a global positioning system. The inertial navigation system quickly calculates the position and the attitude of the robot by integrating directional accelerations, angular speed, and heading angle from a strap-down inertial measurement unit, but the results are available for a short time since it tends to diverge quickly. Global positioning system delivers position, heading angle, and traveling speed stably, but it has large deviation with slow update. Therefore, a hybrid navigation system uses the result from an inertial navigation system and corrects the result with the help of the global positioning system where an indirect feedback Kalman filter is used. We implement and confirm the performance of the hybrid navigation system through driving a car attaching it.

• Journal of Advanced Navigation Technology
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• v.7 no.2
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• pp.156-161
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• 2003

In this study, a hybrid navigation system with a low-cost GPS Receiver plus Gyro and Odometer is developed and tested. This hybrid navigation system adopted a modified coupling method which can be distinguished from tightly coupled method or loosely coupled method, so that GPS receivers or Gyros or Odometers can be chosen arbitrary. Comparing to the existing hybrid navigation system, the test results show that this navigation system enhances the accuracy and is robust against the multipath error. It is also proven that this system has an advantage of acquiring GIS data for post processing.

• Journal of Ocean Engineering and Technology
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• v.17 no.4
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• pp.73-80
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• 2003

This paper presents considerations on the results of the rotating arm test, which was carried out for assessment of an hybrid navigation system for a semi-autonomous underwater vehicle. The navigation system consists of an inertial measurement unit(IMU), an ultra-short baseline(USBL) acoustic navigation sensor and a doppler velocity log(DVL) accompanying a magnetic compass. A navigational systemmodel is derived to include the scale effect and bias errors of the DVL, of which the state equation composed of the navigation states and sensor parameters are 25 in the order. The extended Kalman filter was used to propagate the error covariance, The rotating arm tests were carried out in the Ocean Engineering Basin of KRISO, to generate circular motion. The hybrid underwater navigation system shows good tracking performance against the circular planar motion. Additionally this paper checked the effects of the sampling ratio of the navigation system and the possibility of the dead reckoning with the DVL and the magnetic compass to estimate the position of the vehicle.

• Journal of the Korean Society of Fisheries and Ocean Technology
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• v.20 no.2
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• pp.105-111
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• 1984

Recently, Hybrid Navigation Systems combining Omega, NNSS, Loran C and Dead reckoning etc. served to give us highly accurate ship's position, and a number of ships are equipped with these navigation systems. In order to evaluate for the accuracy of this navigation system observations of Loran C, 5970 and 9970 chains and Radar at the same time were made on board m.s Jeonbuk 401 and 403 training ships of Gunsan Fisheries Collage at nine stations in the yellow sea from July, 1982 to June, 1983, and then were done by the Hybrid Navigation System combining Dead reckoning and Loran C at the same areas. The authors investigated the accuracy of the Hybrid Navigation System based on measurements of the relative positional error which is defined as the difference between the position fixed by this system or the Loran C system, and the one by the Radar. The obtained results are as follows; 1. The mean standard deviation of the time difference of Loran C were about 0.21$\mu$s in 9970 chain and about 0.06$\mu$s in 5970 chain, and the fluctuation of the time difference of Loran C in 5970 chain was smaller than that in 9970 chain. 2. The positional error between two positions by Radar and the Hybrid Navigation System in 9970 chain was about 0.4 miles, and between two positions by Radar and Loran C was about 0.51 miles. The Hybrid Navigation System was therefore more accurate than Loran C System. 3. The positional error between two positions by Radar and Hybrid Navigation System in 5970 chain was about 0.4 miles, and between two positions by Radar and computer simulation of Loran C was about 0.98 miles. Consequently, Hybrid Navigation System was more accurate than computer simulation of Loran C system.

• Journal of Institute of Control, Robotics and Systems
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• v.7 no.9
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• pp.774-782
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• 2001

In this paper, we propose a new approach to the autonomous and high-speed indoor navigation of wheeled mobile robots using hybrid system controller. The hierarchical structure of hybrid system presented consists of high-level reasoning process and the low-level motion control process and the environmental interaction. In a discrete event system, the discrete states are defined by the user-defined constraints and the reference motion commands are specified in the abstracted motions. The hybrid control system applied for the nonholonomic mobile robots can combine the motion planning and autonomous navigation with obstacle avoidance in the indoor navigation problem. For the evaluation of the proposed algorithm, the algorithm is implemented to the two-wheel driven mobile robot system. The experimental results show that the hybrid system approach is an effective method for the autonomous navigation in indoor environments.

• 제어로봇시스템학회:학술대회논문집
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• 1997.10a
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• pp.1403-1406
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• 1997

Generally, G.P.S(Global Positioning System) is using for the car navigation system but it has some restrictions such as the discontinuity of earth satellites and SA (Selective Availability). Recently, the hybrid navigation system combining with G.P.S and Dead-reckoning are much attractuve for improving the accuracy of a vehicle positioning. G.P.S called satellite navigation system, can measure its position by using satellites. Dead-Reckoning is the self-contained navigatioin system using a wheel sensor for the vehicle velocity and a gyro sensor for the vehicle angular velocity. Some algorithm could be generated for finding the vehicle position and orientation. In this paper, we developed a hybrid algotithm wiht G.P.S DR and Map-Matching.

• Transactions of the Korean Society of Automotive Engineers
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• v.12 no.5
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• pp.171-179
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• 2004

Today, the number of vehicle increased rapidly with the development of modem science technology, and it caused serious problems; traffic jam, accident and pollution etc. One of the solve methods these problems it is necessary to develope the vehicle navigation systems and it is already widely used to in field of military etc. Vehicle navigation system can increase the efficiency of traffic flow and offer at a drivers at a best driving conditions. In the vehicle navigation, most important thing is to measure of correct position. There are classifiable as three types. The first is G.P.S., method at artificial satellites which measures the present position and velocity any time, any where in the world at the same time. Secondly, a vehicle can determine its position and path information with a gyroscope and odometer signal, which is called Dead-Reckoning method. Thirdly, hybrid navigation system is the combined of two methods to make utilize the advantage of each navigation system. In the paper, we are analyzed to characteristics at a gyro sensor and introduce at a composition of hybrid navigation system which is combined with the G.P.S., D.R., and map-matching technique. We analyze deeply for the Map-Matching method and explain the coordinate transformation for G.P.S., and the Hybrid navigation algorithm is developed and experimented. Finally, we conclude and comment about our road test results.

• Journal of Ocean Engineering and Technology
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• v.17 no.6
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• pp.83-90
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• 2003

This paper presents an underwater hybrid navigation system for a semi-autonomous underwater vehicle (SAUV). The navigation system consists of an inertial measurement unit (IMU), and a Doppler velocity log (DVL), accompanied by a magnetic compass. The errors of inertial measurement units increase with time, due to the bias errors of gyros and accelerometers. A navigational system model is derived, to include the scale effect and bias errors of the DVL, of which the state equation composed of the navigation states and sensor parameters is 20. The conventional extended Kalman filter was used to propagate the error covariance, update the measurement errors, and correct the state equation when the measurements are available. Simulation was performed with the 6-d.o,f equations of motion of SAUV, using a lawn-mowing survey mode. The hybrid underwater navigation system shows good tracking performance, by updating the error covariance and correcting the system's states with the measurement errors from a DVL, a magnetic compass, and a depth sensor. The error of the estimated position still slowly drifts in the horizontal plane, about 3.5m for 500 seconds, which could be eliminated with the help of additional USBL information.

• IEMEK Journal of Embedded Systems and Applications
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• v.9 no.5
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• pp.299-305
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• 2014

In this paper, a simple version of the hybrid navigation system using Kalman filter is proposed. The implemented hybrid navigation system is composed of a GPS to measure the position and the velocity, and a IMU(inertial measurement unit) to measure the acceleration and the posture of a mobile robot. A discrete Kalman filter is applied to provide the position of the robot by fusing both of the sensor data. When GPS signal is available, the navigation system estimates the position of the robot from the Kalman filter using position and velocity from GPS, and acceleration from IMU. During the interval until next GPS signal arrives, the system calculates the position of the robot using acceleration from IMU and velocity obtained at the previous step. Performance of the navigation system is verified by comparing the real path and the estimated path of the mobile robot. From experiments, we conclude that the navigation system is acceptable for the mobile robot.

• 제어로봇시스템학회:학술대회논문집
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• 2005.06a
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• pp.1450-1455
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• 2005

This paper describes a DR construction for land navigation and the sigma point based receding horizon Kalman FIR (SPRHKF) filter for DR/GPS hybrid navigation system. A simple DR construction is adopted to improve the performance both of the pure land DR navigation and the DR/GSP hybrid navigation system. In order to overcome the flaws of the EKF, the SPKF is merged with the receding horizon strategy. This filter has several advantages over the EKF, the SPKF, and the RHKF filter. The advantages include the robustness to the system model uncertainty, the initial estimation error, temporary unknown bias, and etc. The computational burden is reduced. Especially, the proposed filter works well even in the case of exiting the unmodeled random walk of the inertial sensors, which can be occurred in the MEMS inertial sensors by temperature variation. Therefore, the SPRHKF filter can provide the navigation information with good quality in the DR/GPS hybrid navigation system for land navigation seamlessly.