• ETRI Journal
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• 제38권3호
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• pp.579-588
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• 2016

To improve the ability to determine a vehicle's movement information even in a challenging environment, a hybrid approach called non-Gaussian square rootunscented particle filtering (nGSR-UPF) is presented. This approach combines a square root-unscented Kalman filter (SR-UKF) and a particle filter (PF) to determinate the vehicle state where measurement noises are taken as a finite Gaussian kernel mixture and are approximated using a sparse Gaussian kernel density estimation method. During an outage-free GPS period, the updated mean and covariance, computed using SR-UKF, are estimated based on a GPS observation update. During a complete GPS outage, nGSR-UPF operates in prediction mode. Indeed, because the inertial sensors used suffer from a large drift in this case, SR-UKF-based importance density is then responsible for shifting the weighted particles toward the high-likelihood regions to improve the accuracy of the vehicle state. The proposed method is compared with some existing estimation methods and the experiment results prove that nGSR-UPF is the most accurate during both outage-free and complete-outage GPS periods.

• The Journal of the Acoustical Society of Korea
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• 제13권2E호
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• pp.68-75
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• 1994

신호처리의 많은 분야에서, 심하게 비가우시안 성질을 가지는 분포, 혹은 분포의 중간은 가우시안 특성을 가지지만 양 끝에서는 편차가 크게 나는 분포를 다루어야 하는 경우가 종종 있다. 이러한 편차에 효과적으로 대처하기 위하여 본 논문에서는 음성 신호의 여기 신호로서 혼합 분포(mixture distribution)을 고려한다. 이것은 음성 분석시 피치 주파수가 미치는 영향을 감소시키며, 배경 잡음을 제거하는 데에도 효과적이다. 음성 신호 파라미터의 추정 및 향상을 위하여 EM 알고리즘을 사용하묘, 향상 과정에서는 강인 칼만 필터링 기법을, 파라미터 추정 관정에서는 검출/추정 기법을 사용한다. 실험 결과, 본 논문에서 제안하는 알고리즘이 입력 신호대잡음비가 열악한 경우에 기존의 것보다 우수한 성능을 보인다.

• The Journal of Asian Finance, Economics and Business
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• 제7권9호
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• pp.63-74
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• 2020

This study investigates the behavior of foreign investors in the Stock Exchange of Thailand (SET) in the time of coronavirus disease 2019 (COVID-19) as to whether trading is abnormal, what strategy is followed, whether herd behavior is present, and whether the actions destabilize the market. Foreign investors' trading behavior is measured by net buying volume divided by market capitalization, whereas the stock market behavior is measured by logged return on the SET index portfolio. The data are daily from Tuesday, August 28, 2018, to Monday, May 18, 2020. The study extends the conditional-regression model in an event-study framework and extracts the unobserved abnormal trading behavior using the Kalman filtering technique. It then applies vector autoregressions and impulse responses to test for the investors' chosen strategy, herd behavior, and market destabilization. The results show that foreign investors' abnormal trading volume is negative and significant. An analysis of the abnormal trading volume with stock returns reveals that foreign investors are not positive-feedback investors, but rather, they self-herd. Although foreign investors' abnormal trading does not destabilize the market, it induces stock-return volatility of a similar size to normal trade. The methodology is new; the findings are useful for researchers, local authorities, and investors.

• 대한전자공학회논문지SP
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• 제37권3호
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• pp.57-69
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• 2000

본 논문에서는 주행차량에 장착된 CCD 카메라를 통하여 획득되어진 영상으로부터 moving window를 사용하여 차선을 인식하고 장애물을 감지하는 방법을 제안한다 입력되는 동영상을 실시간에 처리하기 위해서는 하드웨어적으로 상당히 많은 제약을 초래한다. 이러한 문제점을 극복하고 영상을 사용하여 실시간에 차선 인식 및 장애물을 감지하기 위해, 도로조건과 차량상태에 바탕을 둔 최적의 window 크기를 결정하고 그 window 영상만을 처리하여 차선 인식 및 장애물 감지를 실시간에 가능하게 하는 기법을 제안한다 영상의 각 프레임에 대하여 moving window는 칼만필터에 의해 정확성이 향상된 예측방향으로 옮겨진다. 제안된 알고리즘의 효용성을 고속도로 주행영상을 사용한 실험을 통해 보여준다

• 대한전자공학회논문지SP
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• 제46권6호
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• pp.88-94
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• 2009

본 논문에서는 보안 및 감시 시스템 분야에 적용할 수 있는 실시간 객체 탐지 및 추적 알고리듬을 제안한다. 구현된 시스템은 객체 탐지 단계, 객체 추적 단계로 구성되었다. 객체탐지에서는 정화한 객체의 움직임 검출을 위한 향상된 검출 방법인 적응배경 차분법과 적응적 블록 기반 모델을 제안한다. 객체추적에서는 칼만 필터에 기반한 다중 물체 추적 시스템을 설계하였다. 실험결과 이동객체의 움직임을 추정할 수 있었고, 추적 과정에서도 다수의 객체를 잃어버리지 않고 정상적으로 추적할 수 있었다. 또한 원거리 탐지 및 추적에서 향상된 결과를 얻을 수 있었다.

• 제어로봇시스템학회논문지
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• 제16권2호
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• pp.188-193
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• 2010

With GPS being the primary navigation system, Loran use is in steep decline. However, according to the final report of vulnerability assessment of the transportation infrastructure relying on the global positioning system prepared by the John A. Volpe National Transportation Systems Center, there are current attempts to enhance and re-popularize Loran as a GPS backup system through the characteristic of the ground based low frequency navigation system. To advance the Loran system such as Loran-C modernization and eLoran development, research is definitely needed in the field of Loran-C receiver signal processing as well as Loran-C signal design and the technology of a receiver. We have developed a set of Matlab tools, which implement a software Loran-C receiver that performs the receiver's position determination through the following procedure. The procedure consists of receiving the Loran-C signal, cycle selection, calculation of the TDOA and range, and receiver's position determination through the Least Square Method. We experiences the effect of an incorrect cycle selection and various error factors (ECD, ASF, sky wave, CRI, etc.) from the result of the Loran-C signal processing. It is apparent that researches which focus on the elimination and mitigation of various error factors need to be investigated on a software Loran-C receiver. These aspects will be explored in further work through the method such as PLL and Kalman filtering.

• Smart Structures and Systems
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• 제14권2호
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• pp.191-207
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• 2014

In this research, an internal model based method is proposed to estimate the structural displacements and velocities under ambient excitation using only acceleration measurements. The structural response is assumed to be within the linear range. The excitation is assumed to be with zero mean and relatively broad bandwidth such that at least one of the fundamental modes of the structure is excited and dominates in the response. Using the structural modal parameters and partial knowledge of the bandwidth of the excitation, the internal models of the structure and the excitation can be respectively established, which can be used to form an autonomous state-space representation of the system. It is shown that structural displacements, velocities, and accelerations are the states of such a system, and it is fully observable when the measured output contains structural accelerations only. Reliable estimates of structural displacements and velocities are obtained using the standard Kalman filtering technique. The effectiveness and robustness of the proposed method has been demonstrated and evaluated via numerical simulations on an eight-story lumped mass model and experimental data of a three-story frame excited by the ground accelerations of actual earthquake records.

• 한국산학기술학회논문지
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• 제12권12호
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• pp.5856-5864
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• 2011

본 논문은 도로상에 설치한 고정 카메라로부터 획득된 비디오 영상으로부터 이동물체를 검출하는 방법을 제안한다. 제안된 방법은 배경과 입력 비디오 프레임에서 가우시안 피라미드를 사용한 배경 차영상 기법에 기반하며, 입력 비디오 프레임과 배경영상의 오정합으로 발생하는 오검출을 줄이는데 화소기반 방법에 비해 효과적이다. 차영상에서 임계값을 효과적으로 결정하기위하여 각 프레임에서 Otsu의 방법으로 계산된 임계값에 스칼라 칼만필터를 적용하여 필터링하였다. 실험 결과 도로 비디오 영상에서 움직이는 물체를 효과적으로 검출함을 보였다.

• 한국측량학회:학술대회논문집
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• 한국측량학회 2004년도 Korea-Russia Joint Conference on Geometics
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• pp.47-54
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• 2004

In order to meet the users demand, who needs faster and more accurate data in geographic information it is necessary to obtain and process the data more effectively. Now more effective data obtainment about geographic information is possible through the development of unified technology, which is applied to the field of geographic information, as well as through the development of hardware and software engineering. With the fast and precise correction and update, the development of unified technology can bring the reduction of the time and money. For the obtainment of geographic information which can meet the demand of the users, the unified technology has been applied to various fields, and in Aerial Photogrammetry field, many are doing researches actively for the GPS/INS unified system. To obtain fast and precise geographic information using Aerial Photogrammetry method, it is necessary to develop Airborne GPS/INS unified system, which makes GCP to the minimum. For this reason, this study has tried to develop a system which could unite and process both GPS and INS data. For this matter, code-processing module for DGPS and OTF initialization module, which can decide integer ambiguity even in motion, have been developed. And also, continuous kinematic carrier-processing module has been developed to calculate the location at the moment of filming. In addition, this study suggests a possibility of using a module, which can unite GPS and INS, using Kalman filtering, and also shows the INS navigation theory.

• 한국지능시스템학회논문지
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• 제19권5호
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• pp.641-647
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• 2009

본 논문에서는 새로운 방식의 적응형 순항제어 필터링 방식을 제안한다. 제안한 알고리즘은 선행 차량의 모드를 추정하는 문제를 분류기의 문제로 보고 신경망 분류기를 이용하여 이를 수행한다. 신경망은 각 모드에 대한 사후 확률을 출력하며 이를 IMM과 결합하여 선행차량의 추적을 수행한다. 끝으로 10가지 시나리오에 대하여 신경망 분류기와 IMM을 결합한 NIMM (Neural Network IMM)을 적용하여 성능을 확인한다.