• Journal of IKEEE
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• v.23 no.2
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• pp.710-715
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• 2019

We consider parameter estimation in distributed systems in which measurements at local nodes are quantized in a non-regular manner, where multiple codewords are mapped into a single local measurement. For the system with non-regular quantization, to ensure a perfect independent encoding at local nodes, a local measurement can be encoded into a set of a great number of codewords which are transmitted to a fusion node where estimation is conducted with enormous computational cost due to the large cardinality of the sets. In this paper, we propose an efficient estimation technique that can handle the non-regular quantized data by efficiently finding the feasible combination of codewords without searching all of the possible combinations. We conduct experiments to show that the proposed estimation performs well with respect to previous novel techniques with a reasonable complexity.

• Journal of the Society of Disaster Information
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• v.20 no.2
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• pp.315-328
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• 2024

Purpose: The purpose of this paper is to present a service construction plan using multiple complex sensor information to detect abnormal situations in urban life safety that are difficult to identify on CCTV. Method: This study selected service scenarios based on actual testbed data and analyzed service importance for local government control center operators, which are main users. Result: Service scenarios were selected as detection of day and night dynamic object, Detection of sudden temperature changes, and Detection of time-series temperature changes. As a result of AHP analysis, walking and mobility collision risk situation services and fire foreshadowing detection services leading to immediate major disasters were highly evaluated. Conclusion: This study is significant in proposing a plan to build an anomaly detection service that can be used in local governments based on real data. This study is significant in proposing a plan to build an anomaly detection service that can be used by local governments based on testbed data.

• Journal of the Microelectronics and Packaging Society
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• v.23 no.3
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• pp.21-29
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• 2016

In this paper, we developed a flexible transparent capacitive pressure sensor which can recognize X and Y coordinates and the size of force simultaneously by sensing a change in electrical capacitance. The flexible transparent capacitive pressure sensor was composed of 3 layers which were top electrode, pressure sensing layer, and bottom electrode. Silver nanowire(Ag NW)/poly(3,4-ethylenedioxythiophene): poly(styrenesulfonate) (PEDOT:PSS) hybrid film was used for top and bottom flexible transparent electrode. The fabricated capacitive pressure sensor had a total size of 5 inch, and was composed of 11 driving line and 19 sensing line channels. The electrical, optical properties of the Ag NW/PEDOT:PSS and capacitive pressure sensor were investigated respectively. The mechanical flexibility was also investigated by bending tests. Ag NW/PEDOT:PSS exhibited the sheet resistance of $44.1{\Omega}/square$, transmittance of 91.1%, and haze of 1.35%. Notably, the Ag NW/PEDOT:PSS hybrid electrode had a constant resistance change within a bending radius of 3 mm. The bending fatigue tests showed that the Ag NW/PEDOT:PSS could withstand 200,000 bending cycles which indicated the superior flexibility and durability of the hybrid electrode. The flexible transparent capacitive pressure sensor showed the transmittance of 84.1%, and haze of 3.56%. When the capacitive pressure sensor was pressed with the multiple 2 mm-diameter tips, it can well detect the force depending on the applied pressure. This indicated that the capacitive pressure sensor is a promising scheme for next generation flexible transparent touch screens which can provide multi-tasking capabilities through simultaneous multi-touch and multi-force sensing.

• Korean Journal of Optics and Photonics
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• v.34 no.3
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• pp.106-116
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• 2023

In this paper, we designed a coaxial dual camera incorporating two optical systems-one for the visible rays and the other for far-infrared ones-with the aim of capturing images in both wavelength ranges. The far-infrared system, which uses an uncooled detector, has a sensor array of 640×480 pixels. The visible ray system has 1,945×1,097 pixels. The coaxial dual optical system was designed using a hot mirror beam splitter to minimize heat transfer caused by infrared rays in the visible ray optical system. The optimization process revealed that the final version of the dual camera system reached more than 90% of the fusion performance between two separate images from dual systems. Multiple rigorous testing processes confirmed that the coaxial dual camera we designed demonstrates meaningful design efficiency and improved image conformity degree compared to existing dual cameras.

• ETRI Journal
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• v.30 no.1
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• pp.59-67
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• 2008

The necessity for the precise time synchronization of measurement data from multiple sensors is widely recognized in the field of global positioning system/inertial navigation system (GPS/INS) integration. Having precise time synchronization is critical for achieving high data fusion performance. The limitations and advantages of various time synchronization scenarios and existing solutions are investigated in this paper. A criterion for evaluating synchronization accuracy requirements is derived on the basis of a comparison of the Kalman filter innovation series and the platform dynamics. An innovative time synchronization solution using a counter and two latching registers is proposed. The proposed solution has been implemented with off-the-shelf components and tested. The resolution and accuracy analysis shows that the proposed solution can achieve a time synchronization accuracy of 0.1 ms if INS can provide a hard-wired timing signal. A synchronization accuracy of 2 ms was achieved when the test system was used to synchronize a low-grade micro-electromechanical inertial measurement unit (IMU), which has only an RS-232 data output interface.

• Korean Journal of Remote Sensing
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• v.31 no.3
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• pp.205-214
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• 2015

In this study, a novel land-cover classification framework for multi-temporal SAR data is presented that can combine multiple features extracted through data transforms and multiple classifiers. At first, data transforms using principle component analysis (PCA) and 3D wavelet transform are applied to multi-temporal SAR dataset for extracting new features which were different from original dataset. Then, three different classifiers including maximum likelihood classifier (MLC), neural network (NN) and support vector machine (SVM) are applied to three different dataset including data transform based features and original backscattering coefficients, and as a result, the diverse preliminary classification results are generated. These results are combined via a majority voting rule to generate a final classification result. From an experiment with a multi-temporal ENVISAT ASAR dataset, every preliminary classification result showed very different classification accuracy according to the used feature and classifier. The final classification result combining nine preliminary classification results showed the best classification accuracy because each preliminary classification result provided complementary information on land-covers. The improvement of classification accuracy in this study was mainly attributed to the diversity from combining not only different features based on data transforms, but also different classifiers. Therefore, the land-cover classification framework presented in this study would be effectively applied to the classification of multi-temporal SAR data and also be extended to multi-sensor remote sensing data fusion.

• Journal of the Korean Society for Aeronautical & Space Sciences
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• v.46 no.3
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• pp.219-229
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• 2018

This paper proposes Kalman Filter-based relative navigation algorithms for proximity tasks such as rendezvous/docking/cluster-operation of spacecraft using PSD Sensors and Infrared Beacon Modules. Numerical simulations are performed for comparative analysis of the performance of each relative-navigation technique. Based on the operation principle and optical modeling of the PSD Sensor and the Infrared Beacon Module used in the relative navigation algorithm, a measurement model for the Kalman filter is constructed. The Extended Kalman Filter(EKF) and the Unscented Kalman Filter(UKF) are used as probabilistic relative navigation based on measurement fusion to utilize kinematics and dynamics information on translational and rotation motions of satellites. Relative position and relative attitude estimation performance of two filters is compared. Especially, through the simulation of various scenarios, performance changes are also investigated depending on the number of PSD Sensors and IR Beacons in target and chaser satellites.

• Journal of KIISE
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• v.43 no.12
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• pp.1365-1375
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• 2016

One of the most important capabilities for autonomous service robots working in living environments is to recognize and understand the correct context in dynamically changing environment. To generate high-level context knowledge for decision-making from multiple sensory data streams, many technical problems such as multi-modal sensory data fusion, uncertainty handling, symbolic knowledge grounding, time dependency, dynamics, and time-constrained spatio-temporal reasoning should be solved. Considering these problems, this paper proposes an effective dynamic context management and spatio-temporal reasoning method for intelligent service robots. In order to guarantee efficient context management and reasoning, our algorithm was designed to generate low-level context knowledge reactively for every input sensory or perception data, while postponing high-level context knowledge generation until it was demanded by the decision-making module. When high-level context knowledge is demanded, it is derived through backward spatio-temporal reasoning. In experiments with Turtlebot using Kinect visual sensor, the dynamic context management and spatio-temporal reasoning system based on the proposed method showed high performance.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.40 no.9
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• pp.1837-1845
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• 2015

The longitudinal velocity is necessary for accurate vehicular positioning in urban environment. The pitch angle, which is a road slope, should be calculated to acquire the longitudinal velocity. However, it is impossible to consider very accurate pitch, when using a sensor and an algorithm. That's why process noise and positioning stimation error of IMU should be adjusted to the driving environment and fuse GPS, OBD data with ACF which consist of AKF, CF in this paper. Then, final pitch angle which is appropriate for driving environment is estimated by IMMKF in order to optimize the system model according to road slope models.

• Korean Journal of Remote Sensing
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• v.31 no.3
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• pp.245-253
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• 2015

According to wide civilian utilization of multi sensor satellite information, practical needs for fusion processing and interoperable operation with multiple remote sensing imageries within distributed remote server are being increased. For this task, OGC standards with respect to satellite images and its derived products are crucial factors. This study is to present an applicability of WPS through testing implementation of image processing algorithm. Open sources such as Geoserver and OTB were used linked to WPS application for implementation. WPS can be solely used for web service supporting geoprocessing algorithm, but technical consideration compromising with other important standard protocols including WMS, WFS, WCS, or WMTS is necessary to build full featured geo web for remote sensing imageries. It is expected that application of these international standards for geo-spatial information is an important approach to produce value-added results by interoperable processing between interorganizations or information dissemination containing practical satellite image processing functionalities.