In multiple target tracking, one of the crucial techniques is how to estimate unknown initiation points of tracks by incorporating a set of measurements under noisy and cluttered environment. Due to unknown data association and false alarms, all possible track initiation points need to be evaluated, which suffers from computational complexity. In this paper, we propose a computationally efficient track initiation method for multi-static multi-frequency passive coherent localization systems, where bistatic measurements from different illuminators are incorporated at a receiver to find the most probable track initiation points. By the proposed likelihood utility function, our method resolves unknown data association between measurements and targets to reduce computational complexity. In addition, the proposed method can be extended to process a set of multi-scan measurements in association-free manner, which results in improved estimation accuracy. Simulation results are provided to validate the performance of our proposed method.

This article proposes the design of a dual-band coupled-fed dipole antenna for passive coherent location (PCL) systems in the very high frequency (VHF) band. The proposed indirect coupled feed mechanism, which is often employed in microstrip patch antennas, is first applied to VHF band dipole elements for dual-band matching. To confirm the effectiveness of the proposed design, we fabricate the coupled-fed dipole element and measure antenna characteristics, such as the voltage standing wave ratio (VSWR) and the antenna gain. The proposed antenna element is then applied to an eight-element circular array to form the reference and surveillance beams for PCL systems. Finally, the target location is estimated by constructing amplitude-range doppler (ARD) maps for one frequency modulation (FM) and two terrain digital multimedia broadcasting (T-DMB) illuminators in the Seoul-Gyunggi urban area. The results confirm that the proposed element is suitable for dual-band PCL systems in the VHF band compared to a conventional dipole antenna.

한국전자파학회논문지 (The Journal of Korean Institute of Electromagnetic Engineering and Science)

Most of classifiers implicitly assume that data samples belong to at least one class among predefined classes. However, all data patterns may not be known at the time of data collection or a new pattern can be emerging over time. Hence ideal classifiers need to be able to recognize an emerging pattern. In this paper, we explore the performances and limitations of the existing classification systems in detecting a new class. Also a new method is proposed that can monitor the change in class distribution and detect an emerging class. It works under the supervised learning model where along with classification an emerging class with new characteristic is detected so that classification model can be adapted systematically. For detection of an emerging class, we design statistical significance testing for signaling change of class distribution. When the alarm for new class generation is set on, candidates for new class members are retrieved for close examination by experts. Our experimental results demonstrate competent performances of the proposed method.

한국전자파학회논문지 (The Journal of Korean Institute of Electromagnetic Engineering and Science)

한국전자파학회논문지 (The Journal of Korean Institute of Electromagnetic Engineering and Science)