• International Journal of Computer Science & Network Security
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• 제21권11호
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• pp.241-247
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• 2021

In the article, an analysis of the factors was carried out, which injected into the efficiency of the function of navigation systems in the minds of unimportance. Carrying out analyzes allowing for the visibility of relevant direct adjustments to the effectiveness of the function Inertial navigation systems in the minds of non-value. The designation of the navigation system was assigned to a complex of navigation systems on ships processing of the vector of navigation parameters, so that they can be victorious in the control systems of the ship's collapse, and the safety of floating is safe.

• 대한임베디드공학회논문지
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• 제9권5호
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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.

• 한국지능시스템학회논문지
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• 제14권2호
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• pp.239-246
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• 2004

In this paper, we develop and implement a high integrity GNC(Guidance, Navigation, and Control) system, based on the combined use of the Global Positioning System (GPS) and an Inertial Measurement Unit (IMU), for autonomous land vehicle applications. This paper highlights guidance for the predetermined trajectory and navigation with detection of possible faults during the fusion process in order to enhance the integrity of the navigation loop. The implementation of the GNC system to the autonomous land vehicle presented with fault detection methodology considers high frequency faults from the GPS receiver caused by shadowing and multipath error The implementation, based on a low-cost, strapdown INS aided by standard GPS technology, is described. The results of the field test in the urban environment are presented and showed effectiveness of the GNC system.

• 제어로봇시스템학회:학술대회논문집
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• 제어로봇시스템학회 2001년도 ICCAS
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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.

• ETRI Journal
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• 제29권5호
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• pp.688-690
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• 2007

This letter presents a filter for a car navigation system integrating a low-grade inertial measurements unit (IMU) and a global positioning system receiver. The filter is designed according to the state variables to be estimated and the usable measurements. The usable measurements change from case to case, and the estimative state variables also change due to the measurements; therefore, multiple models must be used for real environmental maneuvers. In this letter, four models for land navigation are chosen and switched by rearranging the system matrix and resetting the error covariance matrices.

• 센서학회지
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• 제28권6호
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• pp.345-354
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• 2019

The 3D position of pedestrians is a physical quantity used in various fields, such as automotive navigation and augmented reality. An inertial navigation system (INS) based pedestrian dead reckoning (PDR), hereafter INS-PDR, estimates the relative position of pedestrians using an inertial measurement unit (IMU). Since an INS-PDR integrates the accelerometer signal twice, cumulative errors occur and cause a rapid increase in drifts. Various correction methods have been proposed to reduce drifts. For example, one of the most commonly applied correction method is the zero velocity update (ZUPT). This study investigated the characteristics of the existing INS-PDR methods based on shoe-mounted IMU and compared the estimation performances under various conditions. Four methods were chosen: (i) altitude correction (AC); (ii) step length correction (SLC); (iii) advanced heuristic drift elimination (AHDE); and (iv) magnetometer-based heading correction (MHC). Experimental results reveal that each of the correction methods shows condition-sensitive performance, that is, each method performs better under the test conditions for which the method was developed than it does under other conditions. Nevertheless, AC and AHDE performed better than the SLC and MHC overall. The AC and AHDE methods were complementary to each other, and a combination of the two methods yields better estimation performance.

• 제어로봇시스템학회논문지
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• 제20권4호
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• pp.468-473
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• 2014

This paper describes the in-flight alignment of SDINS (Strapdown Inertial Navigation Systems) using an EKF (Extended Kalman Filter) and a UKF (Unscented Kalam Filter), which allow large initial attitude error uncertainty. Regardless of the inertial sensors, there are nonlinear error dynamics of SDINS in cases of large initial attitude errors. A UKF that is one of the nonlinear filtering approaches for IFA (In-Flight Alignment) are used to estimate the attitude errors. Even though the EKF linearized model makes velocity errors when predicting incorrectly in case of large attitude errors, a UKF can represent correctly the velocity errors variations of attitude errors with nonlinear attitude error components. Simulation results and analyses show that a UKF works well to handle large initial attitude errors of SDINS and the alignment error attitude estimation performance are quite improved.

• 제어로봇시스템학회논문지
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• 제7권11호
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• pp.944-952
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• 2001

Inertial navigation system(INS) errors increase with time due to inertial sensor errors, and therefore it is desired to combine INS with external aids such as GPS. However GPS informations have a randomly abrupt jump due to a sudden corruption of the received satellite signals and environment, and moreover GPS can\`t provide navigation solutions. In this paper, smoothing and prediction schemes are proposed for GPS`s jump or unavailable GPS. The smoothing algorithm which is designed as a scalar adaptive filter, smooths abrupt jump. The prediction algorithm which is proved by Schuler error model of INS, estimates INS error in appropriate time. The outputs of proposed algorithm apply stable measurements to GPS aided INS Kalman filter. Simulations show that the proposed algorithm can effectively remove measurement jump and predict INS error.

• International Journal of Aeronautical and Space Sciences
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• 제11권3호
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• pp.184-192
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• 2010

In this paper, an initial fine alignment algorithm, which is developed for the strap-down inertial navigation systems of satellite launch vehicles, is considered. For fast and accurate alignment, a simple closed-loop estimation algorithm using a proportional-integral controller is introduced. Through computer simulation for the sway condition in the launch pad, it is shown that a simple filter structure can guarantee fast computational speed that is adequate for real-time implementation as well as the required alignment accuracy and robustness. In addition, its implementation results are presented for the Naro-1 flight test.

• 제어로봇시스템학회:학술대회논문집
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• 제어로봇시스템학회 2005년도 ICCAS
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• pp.888-893
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• 2005

Since inertial sensor errors which increase with time are caused by initial orientation error and sensor errors(accelerometer bias and gyro drift bias), the accuracy of these devices, while still improving, is not adequate for many of today's high-precision, long-duration sea, aircraft, and long-range flight missions. This paper presents a navigation error compensation scheme for Strap-Down Inertial Navigation System(SDINS) using star tracker. To be specific, SDINS error model and measurement equation are derived, and Kalman filter is implemented. Simulation results show the boundedness of position and attitude errors.