• 제어로봇시스템학회:학술대회논문집
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• 2003.10a
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• pp.798-802
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• 2003

The robustness and reliability of vision algorithms is the key issue in robotic research and industrial applications. In this paper, the robust real time visual tracking in complex scene is considered. A common approach to increase robustness of a tracking system is to use different models (CAD model etc.) known a priori. Also fusion of multiple features facilitates robust detection and tracking of objects in scenes of realistic complexity. Because voting is a very simple or no model is needed for fusion, voting-based fusion of cues is applied. The approach for this algorithm is tested in a 3D Cartesian robot which tracks a toy vehicle moving along 3D rail, and the Kalman filter is used to estimate the motion parameters, namely the system state vector of moving object with unknown dynamics. Experimental results show that fusion of cues and motion estimation in a tracking system has a robust performance.

• 제어로봇시스템학회:학술대회논문집
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• 2000.10a
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• pp.363-363
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• 2000

The conventional algorithms which identify and follow a moving target using a camera located at a fixed position are not appropriate for applying to the cases o( using mobile robots, due to their long processing time. This paper proposes a new tracking algorithm based on the sensing system which uses a line light with a single camera. The algorithm categirizes the motion patterns of a pair of mobile objects into parallel, branching, and merging motion, to decide of which objects the trajectories should be calculated to follow the reference object. Kalman Filter is used to estimate the trajectories of selected objects. The proposed algorithm has shown in the experiments that the mobile robot does not miss the target in most cases.

• Journal of Institute of Control, Robotics and Systems
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• v.17 no.11
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• pp.1117-1124
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• 2011

An integrated fault detection and isolation method is proposed in this paper. The main objective of this paper is development fault detection, isolation and diagnosis algorithm based on the DKF (Decentralized Kalman Filter) and the bank of IMM (Interacting Multiple Model) filters using penalty scalar for both partial and total faults and the outlier detection algorithm for preventing false alarm also included. The proposed FDI (Fault Detection and Isolation) scheme is developed in four phases. In the first phase, the outlier detection filter is designed to prevent false alarm as a pre-filter. In the second phases, two local filters and master filter are designed to detect sensor faults. In the third phases, the proposed FDI scheme checks sensor residual to isolate sensor faults and 11 EKFs actuator fault models are designed to detect wherever actuator faults occur. In the last phases, four filters are designed to identify the fault type which is either the total fault or partial fault. The developed scheme can deal with not only sensor and actuator faults, but also preventing false alarm. An important feature of the proposed FDI scheme can decreases fault isolation time and figure out not only fault detection and isolation but also fault type identification. To verify the proposed FDI algorithm performance, the Simulator is also developed under the Matlab/Simulink environment.

• Proceedings of the IEEK Conference
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• 2008.06a
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• pp.301-302
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• 2008

In this paper, we present an algorithm which decrease a frequency offset effect for 868MHz IEEE 802.15.4b LR - WPAN (Low Rate - Wireless Personal Area Network) receiver. The proposed method improve the robustness to frequency offset and receiver's stability using the multiple delay differential filter of receiver correlator.

• Proceedings of the KIEE Conference
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• 2008.07a
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• pp.1937-1938
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• 2008

본 논문에서는 868/915MHz 대역 IEEE 802.15.4b LR-WPAN(Low-Rate Wireless Personal Area Network; ZigBee)시스템의 수신기를 위한 주파수 옵셋 영향을 감소시키는 알고리즘을 제안한다. 저가 구현을 지향하는 LR-WPAN 시스템의 특성에 맞추어 반송파 중심주파수의 $\pm$80ppm에 해당하는 주파수 옵셋 환경에서 안정된 수신을 보장할 수 있는 알고리즘으로 868/915MHz수신기 Correlator에 multiple delay differential filter를 적용함으로써 주파수 옵셋에 대한 강인성 및 수신 성능의 안정성을 증대시켰다.

• Journal of Power Electronics
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• v.18 no.1
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• pp.185-194
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• 2018

Interaction among multiple grid-connected inverters has a negative impact on the stable operations and power quality of a power grid. The interrelated influences of inverter inductor-capacitor-inductor filters constitute a high-order power network, and consequently, excite complex resonances at various frequencies. This study first establishes a micro-grid admittance matrix, in which inverters use deadbeat control. Multiple resonances can then be evaluated via modal analysis. For the active damping method applied to deadbeat control, the sampling frequency and the stable domain of the virtual damping ratio are also presented by analyzing system stability in the discrete domain. Simulation and experimental results confirm the efficiency of modal analysis and stable domain calculation in multi-inverter grid-connected systems.

• Journal of the Institute of Electronics Engineers of Korea SC
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• v.40 no.5
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• pp.333-340
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• 2003

Doppler processing is the heart of pulsed Doppler radar. It gives a clutter elimination and coherent integration. With the improvement of digital signal processors (DPSs), the implementation using them is more widely used in radar systems. Generally, so as for Doppler processor to process the input data in real time, a parallel processing concept using multiple DSPs should be used. This paper implements a programmable Doppler processor, which consists of MTI filter, DFB and square-law detector, using 8 ADSP21060s. Formulating the distribution time of the input data, the transfer time of the output data and the time required to compute each algorithm, it estimates total processing time and the number of required DSP. Finally, using the TSG that provides radar control pulses and simulated target signals, performances of the implemented Doppler processor are evaluated.

• 제어로봇시스템학회:학술대회논문집
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• 1998.10a
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• pp.329-334
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• 1998

This work is concerned with the problem of tracking a maneuvering target. In this paper, an error monitoring and recovery method of perception net is utilized to improve tracking performance for a highly maneuvering tar-get. Many researches have been performed in tracking a maneuvering target. The conventional Interacting Multiple Model (IMM) filter is well known as a suboptimal hybrid filter that has been shown to be one of the most cost-effective hybrid state estimation scheme. The subfilters of IMM can be considered as fusing its initial value with new measurements. This approach is also shown in this paper. Perception net based error monitoring and recovery technique, which is a kind of geometric data fusion, makes it possible to monitor errors and to calibrate possible biases involved in sensed data and extracted features. Both detecting a maneuvering target and compensating the estimated state can be achieved by employing the properly implemented error monitoring and recovery technique. The IMM filter which employing the error monitoring and recovery technique shows good tracking performance for a highly maneuvering target as well as it reduces maximum values of estimation errors when maneuvering starts and finishes. The effectiveness of the pro-posed method is validated through simulation by comparing it with the conventional IMM algorithm.

• Journal of Institute of Control, Robotics and Systems
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• v.21 no.1
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• pp.7-13
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• 2015

Unmanned air vehicles (UAVs) are getting popular not only as a private usage for the aerial photograph but military usage for the surveillance, reconnaissance and supply missions. For an UAV to successfully achieve these kind of missions, geolocation (localization) must be implied to track an interested target or fly by reference. In this research, we adopted multi-sensor fusion (MSF) algorithm to increase the accuracy of the geolocation and verified the algorithm using two multicopter UAVs. One UAV is equipped with an optical camera, and another UAV is equipped with an optical camera and a laser range finder. Throughout the experiment, we have obtained measurements about a fixed ground target and estimated the target position by a series of coordinate transformations and sequential Kalman filter. The result showed that the MSF has better performance in estimating target location than the case of using single sensor. Moreover, the experimental result implied that multi-sensor geolocation algorithm is able to have further improvements in localization accuracy and feasibility of other complicated applications such as moving target tracking and multiple target tracking.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2016.10a
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• pp.393-396
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• 2016

Digital image processing is the technical area of processing and analysis with intellectual and efficient ways, which has been commercialized in a variety of applications. However, the noise is occurred in the image data with multiple reasons and various studies have been performed to eliminate the noise. Generally, the types of noise vary by causes and forms, and composite noise is the representative one. Hence, the modified switching filter to process by types of noise was suggested to eliminate composite noise in the image effectively and to have excellent characteristics of edge conservation.