• 한국통신학회논문지
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• 제40권9호
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• pp.1856-1864
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• 2015

본 논문에서는 실내 환경에서 정규분포 확률을 이용한 Wi-Fi 핑거프린트 방식과 스마트 폰에 내장된 가속도 센서 (accelerometer sensor), 자이로스코프 센서 (gyroscope sensor)를 이용하여 정확도를 향상시킨 위치추정 알고리즘을 제안하고, 실제 실험을 통하여 성능을 분석하였다. 제안한 알고리즘의 성능 실험은 본 대학교 공대 건물내의 가로 세로 20m * 10m의 공간에서 실시하였으며, 사용자가 각 구간을 이동 할 때 제안한 알고리즘의 위치추정 성능을 핑거프린트 (fingerprint) 방식과 추측항법 (dead reckoning)과 서로 비교하였다. 실험 결과, 제안한 알고리즘의 성능은 두 방식과 비교 했을 때, 최대 오차 거리는 각각 2cm, 36cm, 그리고 평균 오차 거리는 각각 16.64cm, 36.25cm 더 우수함을 확인하였다. 또한, 핑거프린트 맵 (map) 탐색 알고리즘의 성능도 맵 전체를 탐색하는 방식에 비해 약 0.15초 더 단축됨을 확인하였다.

• 제어로봇시스템학회논문지
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• 제19권5호
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• pp.481-487
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• 2013

This paper presents an FIR (Finite Impulse Response) fixed-interval smoothing filter for fast and exact estimating state variables of a discrete nonlinear system with modeling uncertainty. Conventional IIR (Infinite Impulse Response) filter and smoothing filter can estimate state variables of a system with an exact model when the system is observable. When there is an uncertainty in the system model, however, conventional IIR filter and smoothing filter may cause large errors because the filters cannot estimate the state variables corresponding to the uncertain model exactly. To solve this problem, FIR filters that have fast estimation properties and have robustness to the modeling uncertainty have been developed. However, there is time-delay estimation phenomenon in the FIR filter. The FIR smoothing filter proposed in this paper makes up for the drawbacks of the IIR filter, IIR smoothing filter, and FIR filter. Therefore, the FIR smoothing filter has good estimation performance irrespective of modeling uncertainty. The proposed FIR smoothing filter is applied to the integrated navigation system composed of a magnetic compass based DR (Dead Reckoning) and a GPS (Global Positioning System) receiver. Even when the magnetic compass error that changes largely as the surrounding magnetic field is modeled as a random constant, it is shown that the FIR smoothing filter can estimate the varying magnetic compass error fast and exactly with simulation results.

• 한국ITS학회 논문지
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• 제19권1호
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• pp.94-106
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• 2020

근래의 위치 측위 방법으로 GPS(Global Positioning System) 위성정보를 활용하는 전파항법 방식을 많이 사용하고 있다. GPS 활용범위가 넓어지고 다양한 측위 정보를 기반으로 하는 분야가 생기면서 보다 높은 정확도를 얻기 위한 새로운 방법들이 요구되고 있다. 자율주행차의 경우 IMU(Inertial Measurement Unit)를 사용한 항법 시스템인 INS(Inertial Navigation System)와 차량 내부 센서를 이용한 DR(Dead Reckoning) 알고리즘을 사용하여 GPS의 정확도 저하나 음영지역에서의 위치 측정방법으로 사용하고 있다. 그러나 이러한 측위 방법은 대형화되는 빌딩 지역, 터널, 지하 주차장 등 다양한 음영지역과 시간이 지남에 따라 오차가 계속 증가하는 누적 기반 위치추정 방법의 한계로 인해 많은 문제 요소가 있다. 본 논문은 GPS 음영지역에서 차량의 위치 측위를 위해, 대중적 무선 통신인 WLAN을 이용한 Fingerprint 기법을 4개의 Anchor 형태로 AP(Access Point)와 지향성 안테나를 위치하여 넓은 지하 주차공간에서 효율적인 측위 방법을 제시하고 시간이 지남에 따라 주차된 차량이 이동하는 환경에서도 변화가 없는 위치 측위 결과를 입증하였다.

• 제어로봇시스템학회논문지
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• 제19권2호
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• pp.158-163
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• 2013

The fusion of the GPS (Global Positioning System) and DR (Dead Reckoning) is widely used for position and latitude estimation of vehicles such as a mobile robot, aerial vehicle and marine vehicle. Among the many types of aerial vehicles, grater focus is given on the quad-rotor and accuracy of the position information is becoming more important. In order to exactly estimate the position information, we propose the fusion method of GPS and Gyroscope sensor using the DEKF (Dual Extended Kalman Filter). The DEKF has an advantage of simultaneously estimating state value and a parameter of dynamical system. It can also be used even if state value is not available. In order to analyze the performance of DEKF, the computer simulation for estimating the position, the velocity and the angle in a circle trajectory of quad-rotor was done. As it can be seen from the simulation results using own proposed DEKF instead of EKF on own fusion method in the navigation of a quad-rotor gave better performance values.

• Journal of Advanced Marine Engineering and Technology
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• 제39권5호
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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.

• 로봇학회논문지
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• 제12권4호
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• pp.385-394
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• 2017

Side scanning sonar (SSS) provides valuable information for robot navigation. However using the side scanning sonar images in the navigation was not fully studied. In this paper, we use range data, and side scanning sonar images from UnderWater Simulator (UWSim) and propose measurement models in a feature based simultaneous localization and mapping (SLAM) framework. The range data is obtained by echosounder and sidescanning sonar images from side scan sonar module for UWSim. For the feature, we used the A-KAZE feature for the SSS image matching and adjusting the relative robot pose by SSS bundle adjustment (BA) with Ceres solver. We use BA for the loop closure constraint of pose-graph SLAM. We used the Incremental Smoothing and Mapping (iSAM) to optimize the graph. The optimized trajectory was compared against the dead reckoning (DR).

• 대한전기학회논문지:시스템및제어부문D
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• 제54권2호
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• pp.97-103
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• 2005

Most car navigation systems(CNS) estimate the vehicle's location using global positioning system(GPS) or dead reckoning(DR) system. However, the estimated location has undesirable errors because of various noise sources such as unpredictable GPS noises. As a result, the measured position is not lying on the road, although the vehicle is known to be restricted on the road network. The purpose of map matching is to locate the vehicle's position on the road network where the vehicle is most likely to be positioned. In this paper, we analyze some general map matching algorithms first. Then, we propose a map matching method using compensation vectors to improve the performance of map matching. The proposed method calculates a compensation vector from the discrepancy between a measured position and an estimated position. The compensation vector and a newly measured position are to be used to determine the next estimation. To show the performance improvement of the map matching using compensation vectors, the real time map matching experiments are performed. The real road experiments demonstrate the effectiveness and applicability of the proposed map matching.

• 한국지반환경공학회 논문집
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• 제14권3호
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• pp.51-60
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• 2013

본 연구에서는 기압 센서의 특성과 기존의 차분 기법을 결합하여 임의의 건설현장에서 작업자의 절대고도를 확보하는 방법을 제안하고, 다양한 특성을 가진 다양한 건설 현장에서 이 방법을 적용한 결과를 분석하여 그 타당성을 검증하였다. 본 연구 결과물은 실제 건설 현장에서 작업자의 3D좌표 추출에 적용하기 위한 실용 기술로 개발된 것으로써 스마트폰에 내장된 각종 MEMS 센서들의 사양과 특징을 분석하고 데이터를 획득하여 단말기의 위치를 실내외에서 어떻게 결정할 수 있는지를 각종 시험을 통해 검증하였다. 이를 위해 다양한 실제 스마트폰으로부터 센서정보를 추출하는 프로그램을 개발하고 PC인터페이스 방법을 제시하였으며 개발과정에서 발생한 여러 문제점들을 극복하는 방안 등을 소개한다.