• 반도체디스플레이기술학회지
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• 제22권2호
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• pp.112-119
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• 2023

In urban environments, signals of Global Positioning System (GPS) can be blocked and reflected by tall buildings, large vehicles, and complex components of road network. Therefore, the performance of the positioning system using the GPS module in urban areas can be degraded due to the loss of GPS signals necessary for the position estimation. To deal with this issue, various localization schemes using inertial measurement unit (IMU) sensors, such as gyroscope and accelerometer, and Bayesian filters, such as Kalman filter (KF) and particle filter (PF), have been designed to enhance the performance of the GPS-based positioning system. Among Bayesian filters, the PF has been widely used for the target tracking and vehicle navigation, since it can provide superior performance in estimating the state of a dynamic system under nonlinear/non-Gaussian circumstance. This paper presents a positioning system that uses the double-stacked particle filter (DSPF) as well as the accelerometer, gyroscope, and GPS receiver on the smartphone to provide higher pedestrian positioning accuracy in urban environments. The DSPF employs a nonparametric technique (Parzen-window) to create the multimodal target distribution that approximates the posterior distribution. Experimental results show that the DSPF-based positioning system can provide the significant improvement of the pedestrian position estimation in urban environments.

• 한국항행학회논문지
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• 제27권5호
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• pp.674-684
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• 2023

이 논문에서는 INS의 항법 정확도에 영향을 주는 중력 교란에 대한 실시간 예측기법으로 다층 퍼셉트론 모델을 제안하였다. 적합한 MLP 모델을 선정하기 위해서 학습 정확도 및 실행시간을 비교할 수 있게 신경망의 크기가 다른 4개의 모델을 설계하였다. 이 MLP 모델의 학습을 위해 해상 또는 육상의 지표면을 따라 이동하는 물체의 위치 및 중력교란 데이터를 사용하였으며, 중력교란 데이터의 계산은 2160차의 EGM2008을 SHM을 이용하여 이루어졌다. 학습 정확도 평가에서는 MLP4가 가장 우수한 것으로 확인 되었고, 이후 실행시간을 측정하기 위해 학습이 완료된 4개 모델의 가중치와 바이어스 항들을 INS의 내장형 컴퓨터에 저장하여 MLP 모델을 구현하였다. 4개 모델 중 MLP4의 실행시간이 가장 짧은 것을 확인할 수 있었다. 이러한 연구 결과는 향후 중력 교란 보상을 통한 INS의 항법 정확도를 향상시키는데 활용될 수 있을 것으로 기대된다.

• 대한조선학회논문집
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• 제56권5호
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• pp.439-446
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• 2019

A real time transporter locating system for shipyard has been implemented through the GNSS and IMU sensor. There are a lot of block movements by transporters at the shipyard, which need to be controlled and monitored for conforming to the shipbuilding process. For the precise and safe transporter motion at the yard, a locating system has been developed by using the GNSS and IMU sensors for the transporter. There are several obstacles of the GPS signals for locating the transporter at the yard, such as, buildings and metal structures. To overcome the weakness of the GPS signal transmission, the IMU data have been properly integrated together. The performance of the proposed real time block locating system has been verified through the real experiments with transporters carrying blocks at a shipyard.

• 대한원격탐사학회지
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• 제19권1호
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• pp.91-97
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• 2003

The design of Graphic Information System(GIS) in various applications is suffering from the difficulty of data acquisition, which is labor-intensive and time consuming. In order to provide the spatial data rapidly and accurately, 4S-Van, a prototype mobile mapping system, has been developed. The 4S-Van consists of 1)Global Positioning System(GPS), Inertial Navigation System(INS) for estimating the geographic position and attitude of the moving van, i.e.,(x, y, z) and the direction of the Van, 2) Charge Coupled Device(CCD) camera and laser scanner for capturing images and for measuring depth from geographic objects, and 3) External Synchronization Device(ESD) and industrial PC for synchronizing data from GPS/INS/CCD camera and for storing the data. In this paper, we present the design and implementation of the proto-Dpe 4S-Van system for spatial data acquisition for various GIS applications.

• 한국군사과학기술학회지
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• 제10권1호
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• pp.14-21
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• 2007

This paper proposes SDINS(strapdown inertial navigation system) transfer alignment method for vertical launcher using an adaptive filter in the ship. First, the velocity and attitude matching transfer alignment method is designed to align SDINS for vertical launcher. Second, the adaptive filter is employed to estimate measurement noise variance in real time using the residual of measurements. Because it is difficult to decide measurement noise variance when noise properties of the ship SDINS are changed. To verify its performance, it is compared with the EKF(Extended Kalman filter) using uncorrect measurement variance. The monte carlo simulation results show that proposed method is more effective in estimating attitude angle than EKF.

• 한국군사과학기술학회지
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• 제9권3호
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• pp.132-140
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• 2006

In this paper, a new fault detection method for the extended Kalman filter, which uses a N-step predictor, is proposed. The N-step predictor performs the only time propagations for N-step intervals without measurement updates and its output is used as a monitoring signal for the fault detection. A consistency between the extended Kalman filter and the N-step predictor is tested to detect a fault. A test statistic is defined by the difference between the extended Kalman filter and the N-step predictor. The proposed method is applied to strapdown inertial navigation system (SDINS). By computer simulation, it is shown that the proposed method detects a fault effectively.

• 제어로봇시스템학회:학술대회논문집
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• 제어로봇시스템학회 1993년도 한국자동제어학술회의논문집(국내학술편); Seoul National University, Seoul; 20-22 Oct. 1993
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• pp.34-39
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• 1993

Presented in this paper is a complete error covariance analysis for strapdown inertial navigation system(SDINS). We have found that in SDINS the cross-coupling terms in gyrocompass alignment errors can significantly influence the SDINS error propagation. Initial heading error has a close correlation with the east component of gyro bias erro, while initial level tilt errors are closely related to accelerometer bias errors. In addition, pseudo-state variables are introduced in covariance analysis for SDINS utilizing the characteristics of gyrocompass alignment errors. This approach simplifies the covariance analysis because it makes the initial error covariance matrix to a diagonal form. Thus a real implementation becomes easier. The approach is conformed by comparing the results for a simplified case with the covariance analysis obtained from the conventional SDINS error model.

• 제어로봇시스템학회논문지
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• 제14권8호
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• pp.774-778
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• 2008

The inaccuracy of inertial sensors used in low cost IMU's limits the usage to ARS, at best. Sensor fusion technologies are widely used to overcome this problem. GPS is the most popular secondary sensor, but GPS alone cannot fully compensate the IMU errors in the initial alignment process and rectilinear flights. This paper presents a new concept of aiding the low cost IMU with the sun line of sight vector. The simulation and experimental results in this paper proves that aiding of INS/GPS with the sun line of sight vector increases the observability and improves accuracy remarkably.

• 한국군사과학기술학회지
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• 제12권3호
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• pp.368-377
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• 2009

In this paper we study the gyro bias calibration method of SDINS(Strap-Down Inertial Navigation System). Generally, SDINS's calibration is performed in 2-axis(or 3-axis) rate table with chamber for varying ambient temperature. We assumed that the majority of calibration-parameter except for gyro bias is knowned. During gyrobias calibration procedure, it can be induced some disturbances(accelerometer's short-term error induced rate table rotation and anti-vibration mount's rotation). In these cases, old gyro-bias calibration methods(using velocity error or attitude error) have an error, because these disturbances are not detectable at the same time. So that, we propose a new gyro-bias calibration method(heading error minimizing using equivalent linear transformation) that can detect anti-vibration mount's rotation. And we confirm efficiency of the new gyro-bias calibration method by simulation.

• 제어로봇시스템학회논문지
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• 제4권5호
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• pp.674-679
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• 1998

In this paper, a new coarse alignment algorithm is proposed for roughly determining the initial attitude of the vehicle. The algorithm, referred as two-step coarse alignment algorithm, computes roll and pitch angle of the vehicle using accelerometer outputs, and then determines yaw angle with gyro outputs. With the geometric relation between sensor outputs and attitude angles, the algorithm error is analytically derived and compared with the previous coarse alignment algorithm that computes a transformation matrix using accelerometer md gyro outputs simultaneously. The simulation is also performed by varying the sensor errors. The results show that the proposed two-step coarse alignment algorithm has better performance for east tilt angle.