• Proceedings of the Korean Institute of Intelligent Systems Conference
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• 1993.06a
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• pp.1001-1004
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• 1993

The Multisensor Fusion Problem (MFP) deals with the methodologies involved in effectively combining together homogeneous or non-homegeneous information obtained from multiple redundant or disparate sensors in order to perform a task more accurately, efficiently, and reliably. The inherent uncertainties in the sensory information are represented using Fuzzy Numbers, -numbers, and the Uncertainty-Reductive Fusion Technique (URFT) is introduced to combine the multiple sensory information into one consensus -number. The MFP is formulated from the Information Theory perspective where sensors are viewed as information sources with a fixed output alphabet and systems are modeled as a network of information processing and processing and propagating channels. The performance of the URFT is compared with other fusion techniques in solving the 3-Sensor Problem.

• Journal of the Korea Computer Graphics Society
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• v.6 no.3
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• pp.9-15
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• 2000

We Propose a sensor fusion technique for motion capture system. In our system, two kinds of sensors are used for mutual assistance. Four magnetic sensors(markers) are attached on the upper arms and the back of the hands for assisting twelve optical sensors which are attached on the arms of a performer. The optical sensor information is not always complete because the optical markers can be hidden due to obstacles. In this case, magnetic sensor information is used to link discontinuous optical sensor information. We use a system identification techniques for modeling the relation between the sensors' signals. Dynamic systems are constructed from input-output data. We determine the best model from the set of candidate models using the canonical system identification techniques. Our approach is using a simple signal processing technique currently. In the future work, we will propose a new method using other signal processing techniques such as Wiener or Kalman filter.

• Journal of the Korean Society for Precision Engineering
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• v.16 no.2 s.95
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• pp.176-182
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• 1999

This paper presents a new autonomous kinematic calibration technique by using a laser-vision sensor called "Perceptron TriCam Contour". Because the sensor measures by capturing the image of a projected laser line on the surface of the object, we set up a long, straight line of a very fine string inside the robot workspace, and then allow the sensor mounted on a robot to measure the point intersection of the line of string and the projected laser line. The point data collected by changing robot configuration and sensor measuring are constrained to on a single straght line such that the closed-loop calibration method can be applied. The obtained calibration method is simple and accurate and also suitable for on-site calibration in an industrial environment. The method is implemented using Hyundai VORG-35 for its effectiveness.

• Proceedings of the KSRS Conference
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• 2002.10a
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• pp.382-387
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• 2002

In this paper, we propose a geostatistical approach incorporated to the Bayesian data fusion technique for supervised classification of multi-sensor remote sensing data. Traditional spectral based classification cannot account for the spatial information and may result in unrealistic classification results. To obtain accurate spatial/contextual information, the indicator kriging that allows one to estimate the probability of occurrence of classes on the basis of surrounding observations is incorporated into the Bayesian framework. This approach has its merit incorporating both the spectral information and spatial information and improves the confidence level in the final data fusion task. To illustrate the proposed scheme, supervised classification of multi-sensor test remote sensing data set was carried out.

• Proceedings of the KIEE Conference
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• 2007.10a
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• pp.327-328
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• 2007

This paper is to develop the path-tracking of free-ranging AGV(Autonomous Guided Vehicle). Encorders are used to trace the location of the AGV. A gyroscope is used to complement encorders that have the error accumulation problem by increasing the distance covered. A sensor fusion technique is applied to correct the error. The path of the AGV is controlled by kinematics and PID which is obtained the data from the sensor fusion. Experimental results are presented to verify the efficiency of proposed method.

• International Journal of Fuzzy Logic and Intelligent Systems
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• v.5 no.3
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• pp.268-273
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• 2005

We propose the specialized product-line development methodology for developing the embedded system of an MSDFS (Multi Sensor Data Fusion System : called MSDFS). The product-line methodology provides a simultaneous design between software and hardware, high level reusability. However this is insufficient in requirement analysis stage due to be focused on software architecture, detailed design and code. Thus we apply the business model based on IDEF0 technique to traditional methodology. In this paper, we describe the processes of developing Core-Asset, which are requirement analysis, feature modeling, validation. The proposed model gives the efficient result for eliciting features, and ensures the high level reusability of modules performing on embedded system.

• Proceedings of the KSRS Conference
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• 2002.10a
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• pp.407-407
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• 2002

The most widespread techniques for DEM generation are stereoscopy for optical sensor images and interfereometry for SAR images. These techniques suffer from certain sensor and processing limitations, which can be overcome by the synergetic use of both sensors and DEMs respectively. In this paper, different strategies for fusing SAR and optical data are combined to derive high quality DEM products. The filtering techniques, which take advantage of the complementary properties of SAR and stereo optical DEMs, will be applied for the fusion process. By taking advantage of the fact that errors of the DEMs are of different nature using the filtering technique, affected part are filtered and replaced by those of the counterpart and is tested with two sets of SPOT and ERS DEM, resulting in a remarkable improvement in DEM. for the analysis of results, the reference DEM is generated from digital base map(1:5000).

• International Journal of Internet, Broadcasting and Communication
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• v.10 no.2
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• pp.45-50
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• 2018

Recently the water management department advised the water treatment industry to focus on deploy the chemical free and the environmentally responsible process to adopt on water treatment plants in every country. In this objective, water treatment process started using ultrasonic based phycocyanin extraction with fluorescence measurement techniques to detect the change in the yield of phycocyanin. This paper propose the design of optical filter model for fluorescence technique based immersive optical phycocyanin measurement sensor design. The proposed design uses the multi-wavelength sensor module for irradiating part, and this plays a role of removing a wavelength band other than 590 ~ 620 nm. The preliminary study on immersed phycocyanin sensor, the fluorescence value of picocyanin according to the ultrasonic intensity, treatment time and number of cells was measured using JM phycocyanin module to emulate the proposed design, and were compared performance of the proposed sensor emulation. In this design, the phycocyanin fluorescence value increased about 2.1 ~ 4.7 times as the ultrasonic treatment time increased as compared with JM phycocyanin module, and the phycocyanin fluorescence value within the analysis range was obtained by ultrasonic treatment within one minute.

• Proceedings of the KIEE Conference
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• 1995.07b
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• pp.699-701
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• 1995

An input estimation technique is derived in multi-sensor environment. The proposed approach distribute the computational burden of input estimation to each local sensor and fusion center without loss of its optimality. The performances of proposed method in 2-sensor system are compared with those in single sensor system. Simulation results show that a reliable maneuvering target tracking system can be constructed in multi-sensor environment via proposed approach.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.37 no.5C
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• pp.355-364
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• 2012

Target processing mechanisms are necessary to collect target information, real-time data fusion, and tactical environment recognition for cooperative engagement ability. Among these mechanisms, the target tracking starts from predicting state of speed, acceleration, and location by using sensors' measurements. However, it can be a problem to give the reliability because the measurements have a certain uncertainty. Thus, a technique which uses multiple sensors is needed to detect the target and increase the reliability. Also, data fusion technique is necessary to process the data which is provided from heterogeneous sensors for target tracking. In this paper, a target tracking algorithm is proposed based on probabilistic data association(PDA) by fusing radar and ESM sensor measurements. The radar sensor's azimuth and range measurements and the ESM sensor's bearing-only measurement are associated by the measurement fusion method. After gating associated measurements, state estimation of the target is performed by PDA filter. The simulation results show that the proposed algorithm provides improved estimation under linear and circular target motions.