• 제어로봇시스템학회:학술대회논문집
• /
• 2001.10a
• /
• pp.134.5-134
• /
• 2001

The capability of environment recognition is very important for mobile robot. Especially, a function of target tracking is necessary in monitoring and watching an object using mobile robot. In general, vision sensors such as CCD camera and laser range finder were used for tracking of a moving target. However, they are not only affected by intensity of illumination in environment but also require high performance processors to process large amount of data. Therefore, in this paper, we propose the construction of target tracking system for mobile robot using only ultrasonic sensors to cope with these problems.

• 제어로봇시스템학회:학술대회논문집
• /
• 1992.10a
• /
• pp.558-563
• /
• 1992

Bearing information of target is used critically for target tracking in underwater environment. In passive sonar, target bearing measurements are obtained by processing the acoustic signal emanating from the target. PDA tracking algorithm is usually applied in this case since bearing measurements have several peaks due to interference with other acoustic sources or reflections from underwater media. In this paper, we propose a modified PDA algorithm adopting new probabilistic distributions of the number, position, and amplitude of peaks based on the analysis of real data. This algorithm is tested on real and artificially generated data. The computer simulation result shows improvement of the tracking performance.

• Journal of Institute of Control, Robotics and Systems
• /
• v.20 no.3
• /
• pp.313-322
• /
• 2014

This paper is to survey and put in perspective the working methods of multi-target tracking in clutter. This paper includes theories and practices for data association and related filter structures and is motivated by increasing interest in the area of target tracking, security, surveillance, and multi-sensor data fusion. It is hoped that it will be useful in view of taking into consideration a full understanding of existing techniques before using them in practice.

• Proceedings of the IEEK Conference
• /
• 2009.05a
• /
• pp.210-212
• /
• 2009

In object tracking based on the particle filter algorithm controlling the proper distribution of the samples is essential to accurately track the target. If the samples are spread too wide compared to the target size, the tracking accuracy may degrade as some samples can be caught by background clutters that is similar to the target. On the other hands if the samples are spread too narrow, the particle filter may fail to track the abrupt motion of the target. To solve this problem we propose an improved particle filter that adopts "re-weighting" technique at the observe step. We estimate the distribution of the weights of the current samples by its mean and variance. Then the samples are re-weighted so that the appropriate distribution of the samples in proportional to the target scale is obtained at the next select step. The proposed tracking method can avoid convergence to local mean and improve the accuracy of the estimated target state.

• 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.

• Journal of the Korean Institute of Telematics and Electronics S
• /
• v.36S no.7
• /
• pp.34-42
• /
• 1999

Multi-target tracking system is defined as tracking several targets simultaneously. Kalman filter is widely used for target tracking problems. Kalman filter is known to be extremely useful as an optimal estimator but has a shortcoming of computational complexity. So a simplified estimator model which had less computational burden is proposed for a real-time implementation of multi-target tracking systems. In this paper, Kalman filter is applied to implement a real-time tracking system with a simplified target model. The proposed Kalman filter model is simpler compared with those of conventional ones, greatly reducing computation time, yet keeping the tracking abilities of the optimal Kalman filter. Through both simulations and experiments with real environments, it is demonstrated that the proposed simplified model works good in real situation with multiple to be tracked.

• Journal of the Korea Institute of Military Science and Technology
• /
• v.9 no.2 s.25
• /
• pp.77-86
• /
• 2006

Usually, a tracking-gate of the tracker is used to track the target radar signal in the active ECM system. In this paper, we propose the feed-back tracking-gate filtering method. The designed method applies a tracking-gate of the tacker to the ECM system's receiver as a rejection or pass filter selected by the receiver's purpose, and the specific target signals can be passed or rejected though this tracking-gate filter. Thus, the number of input signals within the receiver's search band is minimized owing to this filter except the target signals. In conclusion, the EW equipment's reaction time can be reduced and the error value about the target signals can be lower than the previous methods'.

• Journal of Korea Society of Digital Industry and Information Management
• /
• v.8 no.2
• /
• pp.95-104
• /
• 2012

In this paper, an estimation of person height and 3D location of a moving person by using the pan/tilt-embedded stereo tracking system is suggested and implemented. In the proposed system, face coordinates of a target person is detected from the sequential input stereo image pairs by using the YCbCr color model and phase-type correlation methods and then, using this data as well as the geometric information of the stereo tracking system, distance to the target from the stereo camera and 3-dimensional location information of a target person are extracted. Basing on these extracted data the pan/tilt system embedded in the stereo camera is controlled to adaptively track a moving person and as a result, moving trajectory of a target person can be obtained. From some experiments using 780 frames of the sequential stereo image pairs, it is analyzed that standard deviation of the position displacement of the target in the horizontal and vertical directions after tracking is kept to be very low value of 1.5, 0.42 for 780 frames on average, and error ratio between the measured and computed 3D coordinate values of the target is also kept to be very low value of 0.5% on average. These good experimental results suggest a possibility of implementation of a new stereo target tracking system having a high degree of accuracy and a very fast response time with this proposed algorithm.

• Aerospace Engineering and Technology
• /
• v.11 no.2
• /
• pp.171-181
• /
• 2012

As a sub-system of an air traffic control system, SDP(Surveillance Data Processor) provides with the system tracks of aircraft using the surveillance sensor data from various air traffic surveillance sensors, such as radars. Therefore, the high accuracy of tracking results is a crucial requirement for safe flights, and verification of the required system performance of SDP is an essential step in development. Moreover, the quantitative evaluation of target tracking accuracy is important for newly developed SDP, since there are several tracking methods for Multi-Sensor Multi-Target Tracking, such as MRT(Multi Radar Tracking), inevitably required as the main function of SDP. In this study, definition of required system performances, establishment of test environment, and test results for MRT performance evaluation of SDP, which is being developed in KARI(Korea Airspace Research Institute) are presented.