• Journal of the Korea Institute of Military Science and Technology
• /
• v.23 no.3
• /
• pp.204-212
• /
• 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.

• Proceedings of the KIEE Conference
• /
• 2001.07d
• /
• pp.1958-1960
• /
• 2001

In this paper, we propose the design methodology of target tracking system using the identification of TS fuzzy model based on genetic algorithm(GA) and RLS algorithm. In general, the objective of target tracking is to estimate the future trajectory of the target based on the past position of the target obtained from the sensor. In the conventional and mathematical nonlinear filtering method such as extended Kalman filter(EKF), the performance of the system may be deteriorated in highly nonlinear situation. In this paper, to resolve these problems of nonlinear filtering technique, the error of EKF by nonlinearity is compensated by identifying TS fuzzy model. In the proposed method, after composing training datum from the parameters of EKF, by identifying the premise and consequent parameters and the rule numbers of TS fuzzy model using GA, and by tuning finely the consequent parameters of TS fuzzy model using recursive least square(RLS) algorithm, the error of EKF is compensated. Finally, the proposed method is applied to three dimensional tracking problem, and the simulation results shows that the tracking performance is improved by the proposed method.

• The Journal of Korean Institute of Electromagnetic Engineering and Science
• /
• v.26 no.6
• /
• pp.572-580
• /
• 2015

RF skin tracking of instrumentation RADAR cannot acquire stable track data, because of effect of multipath interference especially elevation direction. In this paper, low altitude target tracking method using laser tracking system is suggested to overcome this restriction. The effect of multipath can be reduced by increasing angle resolution with laser characteristics of very short pulse and narrow beamwidth. RF skin track, beacon track and laser track data for the integrated calibration target on the ground and target ship on the sea are gathered. And they are compared and analyzed to confirm the performance of laser tracking system. As a result, it shows that the suggested laser track method has better performance than RF skin track under multipath conditions.

• Proceedings of the IEEK Conference
• /
• 2005.11a
• /
• pp.1269-1272
• /
• 2005

In this paper, a new intelligent moving target tracking and surveillance system basing on the pan/tilt-embedded stereo camera system is suggested and implemented. In the proposed system, once the face area of a target is detected from the input stereo image by using a YCbCr color model and then, using this data as well as the geometric information of the tracking system, the distance and 3D information of the target are effectively extracted in real-time.

• Journal of Institute of Control, Robotics and Systems
• /
• v.14 no.10
• /
• pp.1053-1061
• /
• 2008

In this paper, a moving target tracking using a binocular vision for an omni-directional mobile robot is addressed. In the binocular vision, three dimensional information on the target is extracted by vision processes including calibration, image correspondence, and 3D reconstruction. The robot controller is constituted with SPI(serial peripheral interface) to communicate effectively between robot master controller and wheel controllers.

• Journal of the Korean Institute of Telematics and Electronics A
• /
• v.31A no.3
• /
• pp.1-9
• /
• 1994

In this paper as a new approach for real-time multitarget tracking, a hybrid OptoNeural multitarget tracking system based on optical BJTC and neural networks data association algorithm is suggested. In the proposed hybrid tracking system, an optical BJTC is introduced as a preprocessor to reduce the massive input target data into a few correlation peak signals and then the neural networks data association algorithm is used for the massively parallel data association between measurement signals and targets in real-time. Finally, new hybrid type OptoNeural target tracking system is constructed and then some experimental results on multitarget tracking is included. The real-time implementation method of the proposed hybrid system is also discussed.

• Proceedings of the Korean Society of Precision Engineering Conference
• /
• 2003.06a
• /
• pp.915-919
• /
• 2003

This paper presents a fuzzy-motion-control based tracking algorithm of mobile robots, which uses the geometrical information derived from the active stereo-vision system mounted on the mobile robot. The active stereo-vision system consists of two color cameras that rotates in two angular dimensions. With the stereo-vision system, the center position and depth information of the target object can be calculated. The proposed fuzzy motion controller is used to calculate the tracking velocity and angular position of the mobile robot, which makes the mobile robot keep following the object with a constant distance and orientation.

• The Transactions of The Korean Institute of Electrical Engineers
• /
• v.60 no.6
• /
• pp.1245-1254
• /
• 2011

This paper proposes a target tracking algorithm for wheeled mobile robots using in various fields. For the stable tracking, we apply a vision system to a mobile robot which can extract targets through image processing algorithms. Furthermore, this paper presents an algorithm to position the mobile robot at the desired location from the target by estimating its relative position and attitude. We show the problem in the tracking method using the Position-Based Visual Servo(PBVS) control, and propose a tracking method, which can achieve the stable tracking performance by combining the PBVS control with Image-Based Visual Servo(IBVS) control. When the target is located around the outskirt of the camera image, the target can disappear from the field of view. Thus the proposed algorithm combines the control inputs with of the hyperbolic form the switching function to solve this problem. Through both simulations and experiments for the mobile robot we have confirmed that the proposed visual servo control method is able to enhance the stability compared to of the method using only either PBVS or IBVS control method.

• Journal of Institute of Control, Robotics and Systems
• /
• v.16 no.11
• /
• pp.1044-1052
• /
• 2010

In this paper, a new realtime algorithm called the RTPBTD-HPDAF (Recursive Temporal Profile Base Target Detection with Highest Probability Data Association Filter) is presented for tracking fast moving small targets with IIR (Imaging Infrared) sensor systems. Spatial filter algorithms are mainly used for target in IIR sensor system detection and tracking however they often generate high density clutter due to various shapes of cloud. The TPBTD (Temporal Profile Base Target Detection) algorithm based on the analysis of temporal behavior of individual pixels is known to have good performance for detection and tracking of fast moving target with suppressing clutter. However it is not suitable to detect stationary and abruptly maneuvering targets. Moreover its computational load may not be negligible. The PTPBTD-HPDAF algorithm proposed in this paper for real-time target detection and tracking is shown to be computationally cheap while it has benefit of tracking targets with abrupt maneuvers. The performance of the proposed RTPBTD-HPDAF algorithm is tested and compared with the spatial filter with HPDAF algorithm for run-time and track initiation at real IIR video.

• Proceedings of the KIEE Conference
• /
• 2011.07a
• /
• pp.1738-1739
• /
• 2011

In this paper, the range difference based the moving target tracking problem using multiple UAVs is solved within the new framework of linear robust state estimation. To do this, the relative kinematics is modeled as an uncertain linear system containing stochastic parametric uncertainties in its measurement matrix. Applying the non-conservative robust Kalman filter for the uncertain system, a quasi-optimal linear target tracking filter is designed. For its recursive linear filter structure, the proposed method can ensure the fast convergence and reliable target tracking performance. Moreover, it is suitable for real-time applications using multiple UAVs.