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JCR Impact Factor: 0.699
JCR 5-Year IF: 0.674
Issues per year: 4
Current issue: Nov 2018
Next issue: Feb 2019
Avg review time: 81 days


Stefan cel Mare
University of Suceava
Faculty of Electrical Engineering and
Computer Science
13, Universitatii Street
Suceava - 720229

Print ISSN: 1582-7445
Online ISSN: 1844-7600
WorldCat: 643243560
doi: 10.4316/AECE


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Cascaded Feature Selection for Enhancing the Performance of Collaborative Recommender System, AL-SHAMRI, M. Y. H., AL-JUNIAD, A. F., QAID, T. S., AHMED, M. H. A., RAWEH, A. A.
Issue 4/2018


Direct Yaw Control of Vehicle using State Dependent Riccati Equation with Integral Terms, SANDHU, F., SELAMAT, H., MAHALLEH, V. B. S.
Issue 2/2016


Comparison of Cepstral Normalization Techniques in Whispered Speech Recognition, GROZDIC, D., JOVICIC, S., SUMARAC PAVLOVIC, D., GALIC, J., MARKOVIC, B.
Issue 1/2017


A High Optical Transmittance and Low Cost Touch Screen without Patterning, SAMADZAMINI, K., FROUNCHI, J., VELADI, H.
Issue 1/2017


Control and Optimization of UAV Trajectory for Aerial Coverage in Photogrammetry Applications, POPESCU, D., STOICAN, F., ICHIM, L.
Issue 3/2016


Signal Integrity Applications of an EBG Surface, MATEKOVITS, L., DE SABATA, A.
Issue 2/2015



Clarivate Analytics published the InCites Journal Citations Report for 2017. The JCR Impact Factor of Advances in Electrical and Computer Engineering is 0.699, and the JCR 5-Year Impact Factor is 0.674.

Thomson Reuters published the Journal Citations Report for 2016. The JCR Impact Factor of Advances in Electrical and Computer Engineering is 0.595, and the JCR 5-Year Impact Factor is 0.661.

With new technologies, such as mobile communications, internet of things, and wide applications of social media, organizations generate a huge volume of data, much faster than several years ago. Big data, characterized by high volume, diversity and velocity, increasingly drives decision making and is changing the landscape of business intelligence, from governments to private organizations, from communities to individuals. Big data analytics that discover insights from evidences has a high demand for computing efficiency, knowledge discovery, problem solving, and event prediction. We dedicate a special section of Issue 4/2017 to Big Data. Prospective authors are asked to make the submissions for this section no later than the 31st of May 2017, placing "BigData - " before the paper title in OpenConf.

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  3/2016 - 9

A Novel Target Tracking Algorithm for Simultaneous Measurements of Radar and Infrared Sensors

GHAZAL, M. See more information about GHAZAL, M. on SCOPUS See more information about GHAZAL, M. on IEEExplore See more information about GHAZAL, M. on Web of Science, DOUSTMOHAMMADI, A. See more information about DOUSTMOHAMMADI, A. on SCOPUS See more information about DOUSTMOHAMMADI, A. on SCOPUS See more information about DOUSTMOHAMMADI, A. on Web of Science
Click to see author's profile in See more information about the author on SCOPUS SCOPUS, See more information about the author on IEEE Xplore IEEE Xplore, See more information about the author on Web of Science Web of Science

Download PDF pdficon (1,169 KB) | Citation | Downloads: 281 | Views: 1,043

Author keywords
infrared sensors, radar tracking, state estimation, filtering algorithms, minimax techniques

References keywords
tracking(11), transaction(7), radar(6), estimation(6), control(6), systems(5), system(5), signal(5), sensors(5), processing(5)
Blue keywords are present in both the references section and the paper title.

About this article
Date of Publication: 2016-08-31
Volume 16, Issue 3, Year 2016, On page(s): 57 - 64
ISSN: 1582-7445, e-ISSN: 1844-7600
Digital Object Identifier: 10.4316/AECE.2016.03009
Web of Science Accession Number: 000384750000009
SCOPUS ID: 84991107981

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In this paper, a game theory filtering technique is proposed to track a maneuvering target using radar/infrared (IR) sensors. It is shown that use of game theory technique can improve filter performance in presence of model uncertainties, measurement noise, and unknown steering command of the target. The tracking problem of maneuvering target is formulated as a zero-sum dynamic game and a utility function is developed to find equilibrium point of this game in a deterministic fashion to estimate target characteristics, including its position and velocity. To improve the filter performance, a proposed linear matrix inequality is implemented to obtain the introduced parameter in utility function. The robustness of the filter is guaranteed by minimizing the utility function for the worst case region of the measurement noise and steering command. Simulation results illustrate the improved performance of the proposed filter compared to extended Kalman and cubature Kalman filters.

References | Cited By  «-- Click to see who has cited this paper

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[2] P. Jing, S. Xu, Z. Chen, "A Novel State Transition and Data Association Scheme Suitable For Asynchronous Radar and Infrared Sensors," IEEE China Summit & International Conference on Signal and Information Processing, Xi'an, China, 2014, pp. 768-771.
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[9] B. Mocanu, T. Ruxandra, T. Zaharia, "3D Object Metamorphosis with Pseudo Metameshes," Advances in Electrical and Computer Engineering, vol. 15, no. 1, pp. 115-122, 2015.
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[14] F. Valdez, P. Melin, O. Castillo "An Improved Evolutionary Method With Fuzzy Logic For Combining Particle Swarm Optimization and Genetic Algorithms," Applied Soft Computing, vol. 11, no. 2, pp. 2625-2632, 2011.
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[15] R. E. Precup, R. David, E. M. Petriu, S. Preitl, M. Radac, "Fuzzy logic-based adaptive gravitational search algorithm for optimal tuning of fuzzy controlled servo systems," IET Control Theory & Applications, vol. 7, no. 1, pp. 99-107, 2013.
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[16] I. D. Falco, E. Laskowski, R. Olejnik, U. Scafuri, E. Tarantino, M. Tudruj, "Extremal optimization applied to load balancing in execution of distributed programs," Applied Soft Computing, vol. 30, pp. 501-513, 2015.
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[17] N. Tomin, A. Zhukov, D. Sidorov, V. Kurbatsky, D. Panasetsky, V. Spiryaev, "Random forest based model for preventing large-scale emergencies in power systems," International Journal of Artificial Intelligence, vol. 13, no. 1, pp. 211-228, 2015.

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[CrossRef] [Web of Science Times Cited 39] [SCOPUS Times Cited 47]

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References Weight

Web of Science® Citations for all references: 2,511 TCR
SCOPUS® Citations for all references: 3,313 TCR

Web of Science® Average Citations per reference: 84 ACR
SCOPUS® Average Citations per reference: 110 ACR

TCR = Total Citations for References / ACR = Average Citations per Reference

We introduced in 2010 - for the first time in scientific publishing, the term "References Weight", as a quantitative indication of the quality ... Read more

Citations for references updated on 2018-12-14 13:21 in 165 seconds.

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