• Journal of Advanced Navigation Technology
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• v.2 no.1
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• pp.34-42
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• 1998

An adaptive state and input estimator for the tracking of a target with unknown randomly switching input is developed. In modeling the unknown inputs, it is assumed that the input sequence is governed by semi-Markov process. By incorporating the semi-Markov probability concepts into the Bayesian estimation theory, an effective adaptive state and input estimator which consists of parallel Kalman-type filters is obtained. Computer simulation results reveal that the proposed adaptive estimator have improved tracking performance in spite of the unknown randomly switching input.

• Proceedings of the Korean Society of Fisheries Technology Conference
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• 2000.10a
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• pp.27-28
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• 2000

일반적으로 과학어군탐지기는 임의의 수층에서 어군에 의해 산란된 신호로부터 자원량 추정을 실시한다. 따라서, 대상 어군을 구성하는 개체어의 표적강도(Target Strength ; TS)는 가장 중요한 변수이며, 이로부터 현장에서 어군의 분포 밀도를 좀더 정확하게 추정할 수 있다. TS를 결정하는 변수는 자세각, 어체의 체장, 부레의 유무, 주파수 등이다. TS를 알기 위한 많은 국내ㆍ외의 실험들이 죽은 어체를 이용하였으며, 살아있는 어체라도 음축으로부터 어체의 위치를 정확히 파악하기 어려운 센서들을 사용하여 정확한 TS의 정보를 제공하는데는 한계가 있었다. (중략)

• Journal of Advanced Navigation Technology
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• v.10 no.1
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• pp.48-56
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• 2006

This paper proposes an efficient preprocessing technique for a binary centroid tracker in correlated image sequences. It is known that the following factors determine the performance of the binary centroid target tracker: (1) an efficient real-time preprocessing technique, (2) an exact target segmentation from cluttered background images and (3) an intelligent tracking window sizing, and etc. The proposed centroid tracker consists of an adaptive segmentation method based on novel distance features and an efficient real-time preprocessing technique in order to enhance the distinction between the objects of interest and their local background. Various tracking experiments using synthetic images as well as real Forward-Looking InfraRed (FLIR) images are performed to show the usefulness of the proposed methods.

• Journal of the Institute of Electronics Engineers of Korea SP
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• v.42 no.1
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• pp.109-117
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• 2005

Range and velocity measurement algorithm is a procedure for estimating the accurate target position by using matched filter outputs equally spaced both in range and doppler frequency domain. Especially, in measurement algorithm for multi-function radar, it is necessary to consider processing time as well as accuracy in order to track multi-targets simultaneously. In this paper, we analyze range and velocity measurement algorithm using discriminator estimation method which is a technique applied to angle measurement of monopulse radar. The applied method required constant processing time for estimation can be used in multiple target tacking. But, it is necessary to consider measurement accuracy because of using minimum channel outputs for estimation. In the simulation, we show that the applied method is superior to the traditional gravity center measurement algorithm with respect to the accuracy performance and also analyze the characteristics of the proposed technique by calculating RMS error level as the processing parameters such as pulse width , channel step, etc. change.

• Proceedings of the KIEE Conference
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• 2002.07d
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• pp.2102-2104
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• 2002

Batch estimation 알고리듬은 수집된 표적에 대한 모든 정보들을 사용하여 상태변수의 초기값을 추정하게 되며 그 구간동안 표적이 일정한 속도로 움직이고 표적 음원의 주파수는 그 값이 항상 일정하다는 가정을 했다. 본 논문에서는 이러한 가정을 위배하는 표적 음원의 주파수 변화에 대해 대처하기 위한 각도와 주파수정보를 이용하는 Batch estimation 알고리듬과 각도정보만을 사용하는 Batch estimation 알고리듬의 경우를 표적 음원의 주파수 변화를 감지하여 스위칭 할 수 있는 방법에 대해 알아본다.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.18 no.5
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• pp.99-110
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• 2017

Improving tracking performance by estimating the status of multiple targets using radar is important. In a clutter environment, a joint event occurs between the track and measurement in multiple target tracking using a tracking filter. As the number increases, the joint event increases exponentially. The problem to be considered when multiple target tracking filter design in such environments is that first, the tracking filter minimizes the rate of false track alarmsby eliminating the false track and quickly confirming the target track. The purpose is to increase the FTD performance. The second consideration is to improve the track maintenance performance by allocating each measurement to a track efficiently when an event occurs. Through two considerations, a single target tracking data association technique is extended to a multiple target tracking filter, and representative algorithms are JIPDAF and LM-IPDAF. In this study, a probabilistic evaluation of many hypotheses in the assignment of measurements was not performed, so that the computation amount does not increase nonlinearly according to the number of measurements and tracks, and the track existence probability based on the track density The LM-IPDAF algorithm was introduced. This paper also proposes a method to reduce the computational complexity by improving the clutter density estimation method for calculating the track existence probability of LM-IPDAF. The performance was verified by a comparison with the existing algorithm through simulation. As a result, it was possible to reduce the simulation processing time by approximately 20% while achieving equivalent performance on the position RMSE and Confirmed True Track.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.11 no.4
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• pp.1272-1277
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• 2010

Target detection and tracking wireless sensor network must have various signal processing ability. Wireless sensor nodes need to light weight signal processing algorithm because of energy constraints and communication bandwidth constraints. General signal processing algorithm of wireless sensor node consists of de-noising, received signal strength computation, feature extraction and signal compression. Wireless sensor network life-time and performance of target detection and classification depend on sensor node signal processing. In this paper, we propose energy efficient signal processing algorithm using wavelet transform. The proposed method estimates exact target position.

• The Journal of Korean Institute of Electromagnetic Engineering and Science
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• v.25 no.10
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• pp.1062-1068
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• 2014

In this paper, a novel approach estimating target's rotation velocity(RV) is proposed for inverse synthetic aperture radar(ISAR) cross-range scaling(CRS). Scale invariant feature transform(SIFT) is applied to two sequently generated ISAR images for extracting non-fluctuating scatterers. Considering the fact that the distance between target's rotation center(RC) and SIFT features is same, we can set a criterion for estimating RV. Then, the criterion is optimized through the proposed method based on particle swarm optimization(PSO) combined with exhaustive search method. Simulation results show that the proposed algorithm can precisely estimate RV of a scenario based maneuvering target without RC information. With the use of the estimated RV, ISAR image can be correctly re-scaled along the cross-range direction.

• Korean Journal of Remote Sensing
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• v.36 no.3
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• pp.441-448
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• 2020

GMTI (Ground Moving Target Indication) radar system can detect ground moving targets and can provide position and velocity information of each target. However, the azimuth position of target has some offset because of the hardware errors such as mechanical tolerances. In this case, an error occurs no matter how accurate the monopulse ratio is. In this paper, target position correction method in azimuth direction has been proposed. The received sum and difference signals of monopulse GMTI system are post-processed to correct the target azimuth angle error. This method is simple and adaptive for nonhomogeneous area because it can be implemented by using only software without any hardware modification or addition.

• Journal of the Korea Institute of Military Science and Technology
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• v.8 no.2 s.21
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• pp.49-57
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• 2005

The target localization using the line arrays buried in the seabed is a difficult problem due to the complex sea bottom characteristics and need to compensate the wave propagation effect to localize the target accurately Sound speed mismatch in the seabed causes a bias in the target bearing estimation and induces the localization error. In this paper we describe a target localization method with improved accuracy of target bearing and localization by calibration the sound speed in the seabed. The proposed algorithm is verified through the ocean data.