Chul Jin Cho

Video-Based Dynamic Stagger Measurement of Railway Overhead Power Lines Using Rotation-Invariant Feature Matching

In this paper we propose an effective method of assessing the reliability of railway overhead power lines by measuring the dynamic stagger of contact wires based on a video monitoring technique. Previously developed video monitoring methods may produce severe errors when applied to tilting trains due to changes in position and orientation of the pantograph. In particular, we propose to employ feature-based image matching techniques that are invariant to rotation and robust to changes in camera viewpoint. A pantograph tilting model is first developed from the video data acquired from an actual train based on the motion dynamics of the stagger behavior on moving train platform. We then evaluate the proposed method by comparing it with the conventional template matching in terms of tracking error. The experimental results confirm that the proposed method shows superior performance in all train traveling sequences, particularly over the pantograph tilting train motion segment.

Simulation and Ship Detection Using Surface Radial Current Observing Compact HF Radar

This paper proposes an effective method of improving ship detection performance of a compact high-frequency (HF) radar system which has been primarily optimized for observing surface radial current velocities and bearings. Previously developed ship detection systems have been vulnerable to error sources such as environmental noise and clutter when they are applied in a compact HF radar optimized for observing surface current. In particular, the influences of error are reduced by applying a principle component analysis of the generated range-Doppler maps. A compact radar signal model is first developed by the data acquired from an operating compact HF radar site. The proposed method is then validated by comparing it to the conventional ship detection method in terms of detection and false alarm rates. The experimental results confirm that the proposed method shows superior performance in both simulated and practical environments.

Compact HF Surface Wave Radar Data Generating Simulator for Ship Detection and Tracking

Toward a maritime surveillance objective, many ship detection and tracking algorithms have been investigated but are faced with poor performance in practical ocean environments. Compact high-frequency (HF) radar has also faced critical issues due to its long coherent processing interval and varying response from its orthogonal antenna structure. Hence, a simulator based on compact HF radar is proposed in this letter to provide a guideline for effective assessment of ship detection and tracking algorithms while considering these practical issues. To validate the proposed simulator, the simulator generated data has been compared with real data obtained by the compact HF radar sites.

Single object tracking based on active and passive detection information in distributed heterogeneous sensor network

In this paper, a single object tracking method based on fusion of detection information collected from a distributed heterogeneous sensor network is proposed. The considered sensor network is composed of one active type source and multiple receivers. It is assumed that the heterogeneous network is capable of acquiring both passive and active information simultaneously. By means of fusion of the acquired heterogeneous data, the proposed method estimates the candidate region of target location. Then, position of the object is estimated by Maximum Likelihood Estimation. In the experimental results, the performance of the proposed method is demonstrated in terms of deployment strategy of the heterogeneous sensor network.

Man-Made Radio Frequency Interference Suppression for Compact HF Surface Wave Radar

High-frequency surface wave radar (HFSWR) suffers from a man-made interference because its amplitude is high enough to mask the Bragg scattering signal. Although several methods have been proposed for resolving this problem, they are inapplicable to compact HFSWR due to their antenna structures. This letter proposes an effective method of suppressing man-made radio frequency interference for compact HFSWR. The proposed method is composed of man-made interference detection and suppression by using regression based on probabilistic signal model. The proposed method is demonstrated in comparison with conventional methods in terms of root-mean-square error in experiments using synthetic and real data. The results show that the proposed method outperforms other methods in both simulated and practical situations.

Bayesian Estimator Based Target Localization in Ship Monitoring System Using Multiple Compact High Frequency Surface Wave Radars

Recently, the usage of high frequency surface wave radars has been expanded to monitoring of ships within observable region because it can always observe wide target region with low power consumption. However, ship monitoring systems using high frequency radars suffer from the fact that a detection position is far away from true position. To resolve this problem, the proposed method determines final location by applying Bayesian estimator to detection results from each ship monitoring system in high frequency radar network. According to Bayesian theory, a posterior distribution is factorized into likelihood and prior distributions, and both distributions are modeled by using each detection results and auto-identification system data, respectively. Effectiveness of the proposed method is demonstrated through appropriate synthetic and real data. From the results, location accuracy can be improved when the proposed method is applied to location estimation.

Coastal ship monitoring based on multiple compact high frequency surface wave radars

Recently, due to wide observable range as well as low power consumption, the usage of high frequency radars has been expanded to ship detection for both harbor management and national security. However, range and angular resolutions are typically low in high frequency radars due to environmental and physical constraints. Thus, a target location detected on a high frequency radar system is far away from its real position. To reduce the error of detection, a location estimation method is proposed based on multiple high frequency radars. With use of the Bayesian approach, a more accurate final location can be determined by posterior mean. For this work, both likelihood and prior probability are modelled. Effectiveness of the proposed method is shown through appropriate simulation that was conducted according to signal to clutter plus noise ratio. Results are shown to verify the proposed method improves both locating and detecting performances.

Robust localization of moving object via fusion of TDOA and detection range measurements of acoustic sensors

In this paper, an area based method to estimate the position of unidentified moving objects by fusion of heterogeneous sensor data collected from a distributed acoustic sensor network is proposed. The surveillance region considered is composed of a couple of transmitters and multiple binary sensors which are assumed to be located in lattice formation. Each binary sensor may only determine whether or not an object was detected and the time difference of arrival (TDOA) between transmitting signals and object reflected signals. The proposed method estimates the candidate regions in which the object may be located from these two types of data and progressively fuses the regions into a single common region. Then with this common candidate region, the position of the object is estimated by Maximum Likelihood Estimation (MLE). The relevant experimental results demonstrate that the performance and effectiveness of the proposed method are superior compared with the conventional approaches.