• Proceedings of the Korean Institute of Navigation and Port Research Conference
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• 2006.06b
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• pp.227-232
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• 2006

In this paper, a Kalman filter application for GDSS(Group Digital Surveillance System) developed to protect an aquaculture farms is discussed GDSS is composed by a WIWAS(Watching, Identification, Warning, and Action System) and a FDS(Fishery Detection System) that will monitor incoming and outgoing vessels in the aquaculture farms. In the FDS, a tracking function to track vessels without F-AIS(Fishery Automatic Identification System) is needed and the Kalman filter is applied to track vessels around the aquaculture farms. Some simulation results for the multi-objects with white noise is presented and the adaptation possibility for tracking system is discussed.

• Journal of the Korean Institute of Intelligent Systems
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• v.25 no.2
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• pp.186-190
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• 2015

Intelligent vehicle plans motion and navigate itself based on the surrounding environment perception. Hence, the precise environment recognition is an essential part of self-driving vehicle. There exist many vulnerable road users (e.g. vehicle, pedestrians) on vehicular driving environment, the vehicle must percept all the dynamic obstacles accurately for safety. In this paper, we propose an multiple vehicle tracking algorithm using microwave radar. Our proposed system includes various special features. First, exceptional radar measurement model for vehicle, concentrated on the corner, is described by mixture density network (MDN), and applied to particle filter weighting. Also, to conquer the curse of dimensionality of particle filter and estimate the time-varying number of multi-target states, reversible jump markov chain monte carlo (RJMCMC) is used to sampling step of the proposed algorithm. The robustness of the proposed algorithm is demonstrated through several computer simulations.

• Korean Journal of Optics and Photonics
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• v.26 no.3
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• pp.147-154
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• 2015

We propose a method for simultaneously measuring the front and back surface profiles of transparent optical components. The proposed method combines dual-wavelength transmission deflectometry with liquids to record distorted phases at different wavelengths, and then numerically reconstructs the three-dimensional phase information to image the front and back surfaces of the lens. We propose a theoretical model to determine the surface information, and a bifocal lens is experimentally investigated. Unlike conventional transmission deflectometry, our proposed method supports direct observation of the front and back surface profiles of the optical elements.

• Journal of the Institute of Electronics Engineers of Korea SC
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• v.49 no.3
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• pp.1-11
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• 2012

Data association plays an important role in intelligent systems. This paper presents the Bayesian formulation of data association and its applications to intelligent systems. We first describe the Bayesian formulation of data association developed for solving multi-target tracking problems in a cluttered environment. Then we review applications of data association in intelligent systems, including surveillance using wireless sensor networks, identity management for air traffic control, camera network localization, and multi-sensor fusion.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.21 no.6
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• pp.28-34
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• 2020

This paper proposes an approach to the fusion of two heterogeneous sensors with two different fields-of-view (FOV): LIDAR and an RGB camera. Registration between data captured by LIDAR and an RGB camera provided the fusion results. Registration was completed once a depthmap corresponding to a 2-dimensional RGB image was generated. For this fusion, RPLIDAR-A3 (manufactured by Slamtec) and a general digital camera were used to acquire depth and image data, respectively. LIDAR sensor provided distance information between the sensor and objects in a scene nearby the sensor, and an RGB camera provided a 2-dimensional image with color information. Fusion of 2D image and depth information enabled us to achieve better performance with applications of object detection and tracking. For instance, automatic driver assistance systems, robotics or other systems that require visual information processing might find the work in this paper useful. Since the LIDAR only provides depth value, processing and generation of a depthmap that corresponds to an RGB image is recommended. To validate the proposed approach, experimental results are provided.