• Journal of Advanced Marine Engineering and Technology
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• v.39 no.5
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• pp.522-526
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• 2015

Generally, underwater unmanned vehicle have adopted an inertial navigation system (INS), dead reckoning (DR), acoustic navigation and geophysical navigation techniques as the navigation method because GPS does not work in deep underwater environment. Even if the tactical inertial sensor can provide very detail measurement during long operation time, it is not suitable to use the tactical inertial sensor for small size and low cost UUV because the tactical inertial sensor is expensive and large. One alternative to INS is attitude heading reference system (AHRS) with the micro-machined electro mechanical system (MEMS) inertial sensor because of MEMS inertial sensor's small size and low power requirement. A cost effective and small size attitude heading reference system (AHRS) which incorporates measurements from 3-axis micro-machined electro mechanical system (MEMS) gyroscopes, accelerometers, and 3-axis magnetometers has been developed to provide a complete attitude solution for UUV. The AHRS based MEMS overcome many problems that have inhibited the adoption of inertial system for small UUV such as cost, size and power consumption. Several evaluation experiments were carried out for the validation of the developed AHRS's function and these experiments results are presented. Experiments results prove the fact that the developed MEMS AHRS satisfied the required specification.

• 제어로봇시스템학회:학술대회논문집
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• 2000.10a
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• pp.26-26
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• 2000

We study on the velocity matching algorithm for transfer alignment of inertial navigation system(INS) using robust H$_2$ filter. We suggest an uncertainty model for INS and apply the suggested discrete robust H$_2$ filter to the uncertainty model compared with kalman filter, the discrete robust H$_2$ filter is shown by simulation to have good performance of alignment time and accuracy.

• Journal of Positioning, Navigation, and Timing
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• v.4 no.3
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• pp.141-150
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• 2015

In this study, a Global Navigation Satellite System (GNSS) / Inertial Navigation System (INS) / odometer / barometer integrated navigation system that uses a commercial navigation device including Micro Electro Mechanical Systems (MEMS) accelerometer and gyroscope in addition to GNSS, odometer information obtained from a vehicle, and a separate MEMS barometer sensor was implemented, and the performance was verified. In the case of GNSS and GNSS/INS integrated navigation system that are generally used in a navigation device, the performance would deteriorate in areas where GNSS signals are not available. Therefore, an integrated navigation system that calculates a better navigation solution in areas where GNSS signals are not available compared to general GNSS/INS by correcting the velocity error of GNSS/INS using an odometer and by correcting the cumulative altitude error of GNSS/INS using a barometer was suggested. To verify the performance of the navigation system, a commercial navigation device (Softman, Hyundai Mnsoft, http://www.hyundai-mnsoft.com) and a barometer sensor (ST Company) were installed at a vehicle, and an actual driving test was performed. To examine the performance of the algorithm, the navigation solutions of general GNSS/INS and the GNSS/INS/odometer/barometer integrated navigation system were compared in an area where GNSS signals are not available. As a result, a navigation solution that has a smaller position error than that of GNSS/INS could be obtained in the area where GNSS signals are not available.

• Journal of the Korea Institute of Military Science and Technology
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• v.17 no.1
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• pp.135-141
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• 2014

In order to guide a flying object which uses a seeker(SKR) and an inertial navigation system(INS) properly, we should confirm that axes of both equipments are aligned in the scope expected. In this paper we have proposed a method to measure the misaligned angle between a SKR and an INS during the system integration procedure. And we expanded this method to measure misalignments between several SKRs and an INS in case of captive flight test.

• Journal of Institute of Control, Robotics and Systems
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• v.12 no.10
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• pp.982-988
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• 2006

The errors of INS (Inertial Navigation System) are known to grow in time. To compensate the accumulated errors, measurements of external or onboard sensors are extensively utilized to form an integrated navigation system. Recently, INS/GPS integrated navigation systems have become popular since exact position and velocity information can be utilized by low cost GPS receivers. Unfortunately, this configuration cannot be trusted at all times especially when there are intentional or unexpected jammings and interruptions. To aid INS irrespectively of these cases, an INS/Image sensor integrated navigation system configuration is designed only based on the information of image sensor gimble angles. The performance of the INS/Image sensor integrated navigation system is evaluated by Monte Carlo simulation.

• Journal of Institute of Control, Robotics and Systems
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• v.9 no.9
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• pp.736-744
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• 2003

The GPS attitude output or carrier phase observables can be effectively utilized to compensate the attitude error of the strapdown inertial navigation system. However, when the integer ambiguity is not correctly resolved and/or a cycle slip occurs, an erroneous GPS output can be obtained. If the erroneous GPS information is directly applied to the AGPS/INS integration system, the performance of the system can be rapidly degraded. This paper proposes an AGPS/INS integration system using the triple difference carrier phase observables. The proposed integration system contains a cycle slip detection algorithm, in which inertial information is combined. Computer simulations and van test were performed to verify the proposed integration system. The results show that the proposed system gives an accurate and reliable navigation solution even when the integer ambiguity is not correct and the cycle slip occurs.

• Journal of Advanced Navigation Technology
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• v.27 no.1
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• pp.50-56
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• 2023

INS(Inertial Navigation System) calculates navigation information using a vehicle's acceleration and angular velocity without the outside information. However, when navigation is performed for a long time, navigation error gradually diverges and the performance decreases. To enhance INS's performance, the rotation of inertial measurement unit is developed to compensate error sources of inertial sensors, which is called RINS(Rotational Inertial Navigation System). This paper analyzes the influence of several errors for dual-axis RINS and the shows the results using simulation.

• Journal of the Korea Institute of Military Science and Technology
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• v.10 no.2
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• pp.38-46
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• 2007

This paper proposes a design method of a CDU(Control Display Unit) for commercial INS(Inertial Navigation Systems). In order to guarantee reusability and extendability, the design method is based on the class programming of the Windows operating system. Since the CDU has abstracted functions and variables, it can be interfaced with any INS. It is also easy to extend the designed functions using inheritance and polymorphism of the class. In order to show usefulness of the CDU, it has been implemented for the H-726 INS.

• Journal of the Korean Society for Aeronautical & Space Sciences
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• v.45 no.6
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• pp.463-472
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• 2017

Inertial Navigation System Alignment is the process to determine direction cosine matrix which is the transformation matrix between the INS body frame and navigation frame. INS initial position value is necessary to INS attitude calculation, so that user should wait until he get such value to start the INS alignment. To remove the waiting time, we propose an alignment algorithm that immediately starts after the INS power on by using pseudo initial position input and then is completed with attitude error compensation by entering true position later. We analyse effect of INS sensor error on attitude in process of time and verify the performance and usefulness of the close-loop alignment algorithm which corrects attitude error from the change of initial position.

• 제어로봇시스템학회:학술대회논문집
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• 1996.10b
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• pp.668-671
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• 1996

Two expressions for the inertial navigation system error equations are derived using a perturbation method; one in navigation frame, and the other in geographic frame. The equivalence between two expressions is shown by explicit equations and computer simulation.