• Journal of information and communication convergence engineering
• /
• v.8 no.2
• /
• pp.234-237
• /
• 2010

P300 component of the event-related potential(ERP) has been studied for theoretical, empirical, and clinical applications. Nowadays the 1-, 2-, and 3-stimulus oddball paradigms are used for eliciting P300 component of EEG in the auditory stimulus experiments. In this paper, we used a method to add one more stimulus to the 3-stimulus auditory paradigm. The adding stimulus has not the same volume but the same tone of the target stimulus. The 4-stimulus oddball paradigm to use two targets is used to elicit the P300 event-related potentials. In 4-stimulus oddball paradigm, an infrequent non-target (p=0.10) is presented in addition to two infrequent targets (p=0.10) and a frequent standard (p=0.70). Two target stimuli elicited a P300 component with a parietal maximum distribution. The amplitude of the P300 in target 2 was larger than that in target 1 and the latency of the P300 in target 2 was longer than that in target 1. The P300 component due to target 2 stimuli was larger than that due to target 1 stimuli. The experimental results approve that the 4-stimulus oddball paradigm can elicit P300 component clearly. The results are compared with the results of the traditional oddball paradigm.

• KSII Transactions on Internet and Information Systems (TIIS)
• /
• v.13 no.11
• /
• pp.5464-5488
• /
• 2019

The multi-population genetic algorithm in multi-target paths coverage has become a top choice for many test engineers. Also, information sharing strategy can improve the efficiency of multi-population genetic algorithm to generate multi-target test data; however, there is still space for some improvements in several aspects, which will affect the effectiveness of covering the target path set. Therefore, a multi-target paths coverage strategy is proposed by improving multi-population genetic algorithm based on individual information sharing among populations. It primarily contains three aspects. Firstly, the behavior of the sub-population covering corresponding target path is improved, so that it can continue to try to cover other sub-paths after covering the current target path, so as to take full advantage of population resources; Secondly, the populations initialized are prioritized according to the matching process, so that those sub-populations with better path coverage rate are executed firstly. Thirdly, for difficultly-covered paths, the individual chromosome features which can cover the difficultly-covered paths are extracted by utilizing the data generated, so as to screen those individuals who can cover the difficultly-covered paths. In the experiments, several benchmark programs were employed to verify the accuracy of the method from different aspects and also compare with similar methods. The experimental results show that it takes less time to cover target paths by our approach than the similar ones, and achieves more efficient test case generation process. Finally, a plug-in prototype is given to implement the approach proposed.

• Journal of Korea Multimedia Society
• /
• v.19 no.5
• /
• pp.890-900
• /
• 2016

This paper presents a multiple target tracking system using target feature information. In the proposed system, the state of target is defined as its kinematic as well as feature : the kinematic includes a location and a velocity; the feature contains the image correlation between a prior target and a current measurement. The feature information is used for generating the validation matrix and association probability of joint probabilistic data association (JPDA) algorithm. Through the Kalman filter, the target kinematic is updated. Then the tracking information is cycled by the track management algorithm. The system has been evaluated using the images obtained from Electro-Optics/ InfraRed (EO/IR) sensor. It is verified that the proposed system can reduce the complexity burden of JPDA process and can enhance the track maintenance rate.

• KSII Transactions on Internet and Information Systems (TIIS)
• /
• v.10 no.10
• /
• pp.5095-5111
• /
• 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.

• KSII Transactions on Internet and Information Systems (TIIS)
• /
• v.12 no.3
• /
• pp.1287-1300
• /
• 2018

Target-tracking algorithm based on ad hoc camera sensor networks (ACSNs) utilizes the distributed observation capability of nodes to achieve accurate target tracking. A compressed sensing-based multiple-target tracking algorithm (CSMTTA) for ACSNs is proposed in this work based on the study of camera node observation projection model and compressed sensing model. The proposed algorithm includes reconfiguration of observed signals and evaluation of target locations. It reconfigures observed signals by solving the convex optimization of L1-norm least and forecasts node group to evaluate a target location by the motion features of the target. Simulation results show that CSMTTA can recover the subtracted observation information accurately under the condition of sparse sampling to a high target-tracking accuracy and accomplish the distributed tracking task of multiple mobile targets.

• International Journal of Contents
• /
• v.3 no.4
• /
• pp.22-25
• /
• 2007

This paper presents a technology of information data fusion between radar and ELINT electronic intelligence system. adar get the information of the range, direction and velocity of targets, and ELINT system get the information of the direction and angular velocity of the same targets at the same place and at the same time. Since we have some common information data of targets from radar and ELINT system, we can find the target on radar is same or not on ELINT system using the information data fusions. If the target on the radar is verified with the same target on ELINT system, we get more information of the target. e can analysis and identify the target exactly and reduce an ambiguity error of unknown targets.

• Journal of Institute of Control, Robotics and Systems
• /
• v.22 no.7
• /
• pp.530-535
• /
• 2016

In this paper, the TTSE (Target size and Triangulation-based target Size Estimator) algorithm is proposed to estimate static target size in an imaging environment. The target size information is an important factor for accurate imaging target tracking. However, the imaging sensor cannot generate distance between the missile and target to calculate the target size. To overcome the problem, we propose the TTSE algorithm, which is based on target size and triangulation. The proposed method performance is tested in a target intercept scenario. The experiment results show that the proposed algorithm has better performance than the conventional algorithm (ET-TSE) for accurate CCD target size estimation.

• Journal of Institute of Control, Robotics and Systems
• /
• v.6 no.2
• /
• pp.173-180
• /
• 2000

During the last decade many researches have been working on multiple target tracking problem in the area of radar application, Various approaches have been proposed to solve the tracking problem and the concept of sensor fusion was established as an effort. In this paper utilization of geographic information for ground target tracking is investigated and performance comparison with the results of applying sensor fusion is described. Geographic information is used in three aspects: association masking target measurement and re-striction of removing true target. Simulation results indicate that using two sensors shows better performance with respect to tracking but a single with geographic information is a winner in reducing the number of false tracks.

• Spatial Information Research
• /
• v.15 no.2
• /
• pp.123-134
• /
• 2007

The building boundary should be registered in the cadastral map for the protection of property using the expansion of the registration items in the cadastral record and the construction of 3D-cadastral information system. In this study, the efficiency of registering the building boundary was suggested by non-target TS survey through the comparison between target TS and non-target TS survey about an accuracy and efficiency. At the result of this research, the RMSE of target TS and non-target TS survey is the X; ${\pm}0.056m$ and Y; ${\pm}0.043m$. Therefore, non-target TS survey shows the high accuracy. Also, the non-target TS survey is more efficient cost on time and personnel than target TS.

• Journal of Information Display
• /
• v.3 no.2
• /
• pp.19-25
• /
• 2002

In this paper, a new target extraction algorithm is proposed, in which the coordinates of target are obtained adaptively by using the difference image information and the optical BPEJTC(binary phase extraction joint transform correlator) with which the target object can be segmented from the input image and background noises are removed in the stereo vision system. First, the proposed algorithm extracts the target object by removing the background noises through the difference image information of the sequential left images and then controlls the pan/tilt and convergence angle of the stereo camera by using the coordinates of the target position obtained from the optical BPEJTC between the extracted target image and the input image. From some experimental results, it is found that the proposed algorithm can extract the target object from the input image with background noises and then, effectively track the target object in real time. Finally, a possibility of implementation of the adaptive stereo object tracking system by using the proposed algorithm is also suggested.