• Journal of the Korea Institute of Military Science and Technology
• /
• v.26 no.1
• /
• pp.22-30
• /
• 2023

When tracking small UAVs and drone targets in cloud clutter environments, MWIR sensors are often unable to track targets continuously. To overcome this problem, the SWIR sensor is mounted on the same gimbal. Target tracking uses sensor information fusion or selectively applies information from each sensor. In this case, parallax correction using the target distance is often used. However, it is difficult to apply the existing method to small UAVs and drone targets because the laser rangefinder's beam divergence angle is small, making it difficult to measure the distance. We propose a tracking method which needs not parallax correction of sensors. In the method, images from MWIR and SWIR sensors are captured simultaneously and a tracking error for gimbal driving is chosen by effectiveness measure. In order to prove the method, tracking performance was demonstrated for UAVs and drone targets in the real sky background using MWIR and SWIR image sensors.

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

• Journal of Positioning, Navigation, and Timing
• /
• v.1 no.1
• /
• pp.35-43
• /
• 2012

The UGV is one of the special field robot developed for mine detection, surveillance and transportation. To achieve successfully the missions of the UGV, the accurate and reliable navigation data should be provided. This paper presents design and implementation of multi-sensor-based open architecture integrated navigation for localization of UGV. The presented architecture hierarchically classifies the integrated system into four layers and data communications between layers are based on the distributed object oriented middleware. The navigation manager determines the navigation mode with the QoS information of each navigation sensor and the integrated filter performs the navigation mode-based data fusion in the filtering process. Also, all navigation variables including the filter parameters and QoS of navigation data can be modified in GUI and consequently, the user can operate the integrated navigation system more usefully. The conventional GPS/INS integrated system does not guarantee the long-term reliability of localization when GPS solution is not available by signal blockage and intentional jamming in outdoor environment. The presented integration algorithm, however, based on the adaptive federated filter structure with FDI algorithm can integrate effectively the output of multi-sensor such as 3D LADAR, vision, odometer, magnetic compass and zero velocity to enhance the accuracy of localization result in the case that GPS is unavailable. The field test was carried out with the UGV and the test results show that the presented integrated navigation system can provide more robust and accurate localization performance than the conventional GPS/INS integrated system in outdoor environments.

• Proceedings of the KSRS Conference
• /
• 2003.11a
• /
• pp.399-401
• /
• 2003

This paper presents a geostatistical contextual classifier for the classification of remote sensing data. To obtain accurate spatial/contextual information, a simple indicator kriging algorithm with local means that allows one to estimate the probability of occurrence of certain classes on the basis of surrounding pixel information is applied. To illustrate the proposed scheme, supervised classification of multi-sensor remote sensing data is carried out. Analysis of the results indicates that the proposed method improved the classification accuracy, compared to the method based on the spectral information only.

• Journal of the Korea Society of Computer and Information
• /
• v.25 no.7
• /
• pp.9-16
• /
• 2020

In this paper, we propose a prototype design and implementation of a fire detection algorithm using multiple sensors. The proposed topic detection system determines fire by applying rules based on data from multiple sensors. The fire takes about 3 to 5 minutes, which is the optimal time for fire detection. This means that timely identification of potential fires is important for fire management. However, current fire detection devices are very vulnerable to false alarms because they rely on a single sensor to detect smoke or heat. Recently, with the development of IoT technology, it is possible to integrate multiple sensors into a fire detector. In addition, the fire detector has been developed with a smart technology that can communicate with other objects and perform programmed tasks. The prototype was produced with a success rate of 90% and a false alarm rate of 10% based on 10 actual experiments.

• International Journal of Internet, Broadcasting and Communication
• /
• v.7 no.2
• /
• pp.73-78
• /
• 2015

Touch panel is mainly applied to pressure type touch panel but it occur a low recognition rate and error during long-term use. So, it is partly applied to capacitive touch panel to compensate for these problems but it also can occur a same problems via pollutions. Touch technology has developed a various method but it is not used because of high costs and difficult installation process. So, in this paper, we proposed an input method of touchless panel using IrDA matrix. This method is conducted using an IrDA Matrix composed of depth sensor. It is possible to offer a various contents for multi user. The proposed technology need a development of a high sensitivity sensing method and high-speed processing method of position information for Seamless operation control. And, it is required high-precision drive technology. Also, we proposed a Seamless user recognition for interactive contents service through a touchless panel using IrDA matrix.

• Journal of Korean Society of Transportation
• /
• v.19 no.6
• /
• pp.171-182
• /
• 2001

Travel Time is an important characteristic of traffic conditions in a road network. Currently, there are so many road users to get a unsatisfactory traffic information that is provided by existing collection systems such as, Detector, Probe car, CCTV and Anecdotal Report. This paper presents the results achieved with Data Fusion Model, Hybrid Neuro Fuzzy System for on - line estimation of travel times using RTMS(Remote Traffic Microwave Sensor) and Probe Data in the signalized arterial road. Data Fusion is the most important process to compose the various of data which can present real value for traffic situation and is also the one of the major process part in the TIC(Traffic Information Center) for analyzing and processing data. On-line travel time estimation methods(FALEM) on the basis of detector data has been evaluated by real value under KangNam Test Area.

• Journal of Auto-vehicle Safety Association
• /
• v.14 no.3
• /
• pp.71-76
• /
• 2022

In autonomous driving cars, 3D pose estimation can be one of the effective methods to enhance safety control for OOP (Out of Position) passengers. There have been many studies on human pose estimation using a camera. Previous methods, however, have limitations in automotive applications. Due to unexplainable failures, CNN methods are unreliable, and other methods perform poorly. This paper proposes robust real-time multi-human 3D pose estimation architecture in vehicle using monocular RGB camera. Using particle filter, our approach integrates CNN 2D/3D pose measurements with available information in vehicle. Computer simulations were performed to confirm the accuracy and robustness of the proposed algorithm.

• Korean Journal of Remote Sensing
• /
• v.34 no.2_2
• /
• pp.377-391
• /
• 2018

In order to efficiently monitor red tide over a wide range, the need for red tide detection using remote sensing is increasing. However, the previous studies focus on the development of red tide detection algorithm for ocean colour sensor. In this study, we propose the use of multi-sensor to improve the inaccuracy for red tide detection and remote sensing data in coastal areas with high turbidity, which are pointed out as limitations of satellite-based red tide monitoring. The study area were selected based on the red tide information provided by National Institute of Fisheries Science, and spatial fusion and spectral-based fusion were attempted using GOCI image as ocean colour sensor and Landsat OLI image as terrestrial sensor. Through spatial fusion of the two images, both the red tide of the coastal area and the outer sea areas, where the quality of Landsat OLI image was low, which were impossible to observe in GOCI images, showed improved detection results. As a result of spectral-based fusion performed by feature-level and rawdata-level, there was no significant difference in red tide distribution patterns derived from the two methods. However, in the feature-level method, the red tide area tends to overestimated as spatial resolution of the image low. As a result of pixel segmentation by linear spectral unmixing method, the difference in the red tide area was found to increase as the number of pixels with low red tide ratio increased. For rawdata-level, Gram-Schmidt sharpening method estimated a somewhat larger area than PC spectral sharpening method, but no significant difference was observed. In this study, it is shown that coastal red tide with high turbidity as well as outer sea areas can be detected through spatial fusion of ocean colour and terrestrial sensor. Also, by presenting various spectral-based fusion methods, more accurate red tide area estimation method is suggested. It is expected that this result will provide more precise detection of red tide around the Korean peninsula and accurate red tide area information needed to determine countermeasure to effectively control red tide.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
• /
• v.28 no.5
• /
• pp.493-504
• /
• 2010

This study proposes a classification method based on an automated training extraction procedure that may be used with very high resolution (VHR) images of non-accessible areas. The proposed method overcomes the problem of scale difference between VHR images and geographic information system (GIS) data through filtering and use of a Landsat image. In order to automate maximum likelihood classification (MLC), GIS data were used as an input to the MLC of a Landsat image, and a binary edge and a normalized difference vegetation index (NDVI) were used to increase the purity of the training samples. We identified the thresholds of an NDVI and binary edge appropriate to obtain pure samples of each class. The proposed method was then applied to QuickBird and SPOT-5 images. In order to validate the method, visual interpretation and quantitative assessment of the results were compared with products of a manual method. The results showed that the proposed method could classify VHR images and efficiently update GIS data.