• 한국군사과학기술학회지
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• 제23권3호
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• pp.204-212
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• 2020

For general target tracking works by receiving a set of measurements from sensor. However, if the SNR(Signal to Noise Ratio) is low due to small RCS(Radar Cross Section), caused by remote small targets, the target's information can be lost during signal processing. TBD(Track Before Detect) is an algorithm that performs target tracking without threshold for detection. That is, all sensor data is sent to the tracking system, which prevents the loss of the target's information by thresholding the signal intensity. On the other hand, using all sensor data inevitably leads to computational problems that can severely limit the application. In this paper, we propose an iterative Joint Integrated Probabilistic Data Association as a practical target tracking technique suitable for a low SNR multi-target environment with real time operation capability, and verify its performance through simulation studies.

• 전자공학회논문지
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• 제52권5호
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• pp.115-123
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• 2015

점진 학습은 비교적 높은 얼굴 추적 성능을 보이지만, 환경적인 변화로 인해 추적에 오차가 발생하면 그 이후의 추적에 오차가 전파되어 추적 성능이 감소한다는 단점이 있다. 본 논문에서는, 다양한 변이 조건에서 강인하게 동작할 수 있는 선택적인 점진 학습 방법을 제안한다. 먼저, 개별 프레임에 대해 LBP(Local Binary Pattern) 특징을 추출하여 사용함으로써 조명 변이에 보다 강인하게 동작 할수 있고, Staggered Multi-Scale LBP를 사용하여 점진 학습에 사용할 패치(patch)를 선택하여 이전 프레임에서의 오차가 전파되는 것을 방지하였다. 실험을 통해, 제안한 방법이 조명 변이와 같은 환경적 변이가 존재하는 비디오 영상에 대해서도 기존의 추적 방법들보다 우수한 얼굴 추적 성능을 보이는 것을 확인할 수 있었다.

• 디지털산업정보학회논문지
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• 제10권3호
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• pp.127-141
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• 2014

A Vehicle Tracking System consists of GPS tracking device which fits into the vehicle and captures the GPS location information at regular intervals to a central GIS server, and GIS tracking server providing three major responsibilities: receiving data from the GPS tracking unit, securely storing it, and serving this information on demand of the user. GPS based tracking systems supporting a multi-session processing among RMA, RM, and RCP can make a quick response to various services including other vehicle information between RSU and OBU on demand of the user. In this paper we design RSU lower layers and RCP applications in OBU for a multisession processing simulation and test message processing transactions among RMA-RM and RM-RCP. Furthermore, we implement the additional functions of handling access commands simultaneously on multiple service resources which are appropriate for the experimental testing conditions. In order to make a multi-session processing test, it reads 30 resource data,0002/0001 ~ 0002/0030, in total and then occurs 30 session data transmissions simultaneously. We insert a sequence number field into a special header of dummy data as a corresponding response to check that the messages are received correctly. Thus, we find that GIS service system with a multi-session processing is able to provide additional 30 services in a same speed of screen presentation loading while identifying the number of session processing of Web GIS service, the number of OBU service, and the speed of screen presentation loading by comparing a single session and a multi-session of GIS service system.

• 대한전기학회논문지
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• 제41권4호
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• pp.411-421
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• 1992

In the conventional track while scan (TWS) system, there are two major functions to be performed : detection and tracking. These two functions are normally designed and optimised independently. So TWS algorithm ignores the available decision features that can help in resolving the plot-to-track association ambiguity. Therefore conventional TWS system cna't track the targets in a densed multi-target environment. This paper presents a new TWS algorithm for multi-target track to solve the existing TWS system problem in clutter environment. The algorithm proposed in this paper is derived by modifying the part of joint probabilistic data association (JPDA) algotithm to get the one to one correspondence instead of multiple correspondence and combined with maneuvering detection logic so that it could also track the low maneuvering targets. Simulations to confirm the performance are done in crossing, parallel and maneuvering target. The proposed algorithm was successfully tracking targets above target situations.

• 대한전자공학회:학술대회논문집
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• 대한전자공학회 2001년도 하계종합학술대회 논문집(4)
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• pp.159-162
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• 2001

In this Paper, a new multi-sensor single-target tracking method in cluttered environment is proposed. Unlike the established methods such as probabilistic data association filter (PDAF), the proposed method intends to reflect the information in detection phase into parameters in tracking so as to reduce uncertainty due to clutter. This is achieved by first modifying the Bayes risk in Bayesian detection criterion to incorporate the likelihood of measurements from multiple sensors. The final estimate is then computed by taking a linear combination of the likelihood and the estimate of measurements. We develop the procedure and discuss the results from representative simulations.

• 제어로봇시스템학회논문지
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• 제22권6호
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• pp.477-482
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• 2016

This paper presents a simple approximation-based design approach for consensus tracking of heterogeneous second-order nonlinear systems under a directed network. All nonlinearities of followers are assumed to be unknown and non-identical. In the controller design procedure, graph-independent error surfaces are used and an unimplementable intermediate controller for each follower is designed at the first design step. Then, by adding and subtracting a graph-based term at the second step, the actual controller for each follower is designed by using one neural network employed to estimate a lumped and distributed nonlinearity. Therefore, the proposed local controller for each follower has a simpler structure than existing approximation-based consensus tracking controllers for multi-agent systems with unmatched nonlinearities.

• Journal of international Conference on Electrical Machines and Systems
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• 제3권1호
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• pp.88-92
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• 2014

This paper presents an application of a multiphase interleaved converter in tracking maximum power points (MPPs) of a photovoltaic (PV) panel regardless of environmental variations. Maximum power from the panel was extracted by means of the well-known the perturb-and-observe (P&O) method. The switching control technique used an interleaving scheme based on multi-unit synchronization. The converter performed harmonic attenuation without affecting the tracking speed. This approach is straightforward, reliable and inexpensive, and could be applied to any higher number of switching cells without difficulty.

• 대한전기학회논문지
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• 제39권5호
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• pp.470-477
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• 1990

Singh's multi-level method is extended to the optimal tracking control of a large interconnected dynamical system which has coupled states and coupled inputs. The steady-state tracking error and a convergence condition for the extended multi-level method are derived analytically and the results show that the steady-state tracking error and a convergence rate have to be compromised. Also, a new multi-level method which is advantageous over the Singh's method in steady-state tracking error and computational burden is proposed by introducing nominal inputs into the performance index. The resulting feedback gain matrix and the compensation vector are optimal for all initial conditions so that eventual on-line computation is minimal.

• 대한기계학회논문집A
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• 제29권1호
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• pp.139-144
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• 2005

A vehicle cruise control algorithm using an Interacting Multiple Model (IMM)-based Multi-Target Tracking (MTT) method has been presented in this paper. The vehicle cruise control algorithm consists of three parts; track estimator using IMM-Probabilistic Data Association Filter (PDAF), a primary target vehicle determination algorithm and a single-target adaptive cruise control algorithm. Three motion models; uniform motion, lane-change motion and acceleration motion. have been adopted to distinguish large lateral motions from longitudinal motions. The models have been validated using simulated and experimental data. The improvement in the state estimation performance when using three models is verified in target tracking simulations. The performance and safety benefits of a multi-model-based MTT-ACC system is investigated via simulations using real driving radar sensor data. These simulations show system response that is more realistic and reflective of actual human driving behavior.

• KSII Transactions on Internet and Information Systems (TIIS)
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• 제10권10호
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• pp.5095-5111
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• 2016

The Probability Hypothesis Density (PHD) filter is a suboptimal approximation and tractable alternative to the multi-target Bayesian filter based on random finite sets. However, the PHD filter fails to track newborn targets when the target birth intensity is unknown prior to tracking. In this paper, a dual detection-guided newborn target intensity PHD algorithm is developed to solve the problem, where two schemes, namely, a newborn target intensity estimation scheme and improved measurement-driven scheme, are proposed. First, the newborn target intensity estimation scheme, consisting of the Dirichlet distribution with the negative exponent parameter and target velocity feature, is used to recursively estimate the target birth intensity. Then, an improved measurement-driven scheme is introduced to reduce the errors of the estimated number of targets and computational load. Simulation results demonstrate that the proposed algorithm can achieve good performance in terms of target states, target number and computational load when the newborn target intensity is not predefined in multi-target tracking systems.