Reducing Human Effort of the Optical Tracking of Anti-Tank Guided Missile Targets via Embedded Tracking System Design

Bahaaeldin Gamal Abdelaty; Mohamed Abdallah Soliman; Ahmed Nasr Ouda

doi:doi:10.11648/j.ajai.20180202.13

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Reducing Human Effort of the Optical Tracking of Anti-Tank Guided Missile Targets via Embedded Tracking System Design

Bahaaeldin Gamal Abdelaty, Mohamed Abdallah Soliman, Ahmed Nasr Ouda

Published in American Journal of Artificial Intelligence (Volume 2, Issue 2)

Received: 23 September 2018 Accepted: 8 October 2018 Published: 7 November 2018

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Abstract

Human role reduction in the firing process in the physical military systems is the way to improve the overall system performance and achieve the requirement of operation, especially for the anti-tank guided missile (ATGM). In the second-generation ATGM system, the human operator is responsible for following the target until the missile clash the target (Manual Target Tracking). Achieving an acceptable flight trajectory with getting a minimum miss distance, which is a distance between the center of the target and the impact point, is the factor that used to measure the ATGM performance. This paper is dedicated to designing and implementation of an embedded tracking system capable of dealing with the slow-moving objects, which is carried out as a step to reduce the human operator role during the operation, in addition, upgrade the second-generation anti-tank guided missile system to third generation ATGM system (Automatic target tracking). The present work seeks to take benefits of a System on Chip (SoC) technology, including embedded Linux systems, in the real-time computer vision applications. The nonlinear flight simulation model of the intended missile system is presented in a MATLAB environment. The tracking algorithm is described using Python programing language with the aid of OpenCV library and implemented based on embedded Raspberry Pi system (RPI). Hardware-in-Loop experimental test is carried out to evaluate and validate the methodology of the proposed work to achieve the overall system requirement with an acceptable flight trajectory and minimum miss-distance.

Published in	American Journal of Artificial Intelligence (Volume 2, Issue 2)
DOI	10.11648/j.ajai.20180202.13
Page(s)	30-35
Creative Commons	This is an Open Access article, distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution and reproduction in any medium or format, provided the original work is properly cited.
Copyright	Copyright © The Author(s), 2018. Published by Science Publishing Group

Keywords

Raspberry Pi, Guided Missile, Hardware-in-The Loop, Tracking Algorithm, Computer Vision

References

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[2]	P. Zarchan, "Tactical and strategic missile guidance," Progress in astronautics and aeronautics, 2002.
[3]	A. Hampapur, J. Li, S. Pankanti, and C. A. Otto, "Detection and tracking of moving objects," ed: Google Patents, 2015.
[4]	A. Kampker, M. Sefati, A. A. Rachman, K. Kreisköther, and P. Campoy, "Towards Multi-Object Detection and Tracking in Urban Scenario under Uncertainties," arXiv preprint arXiv:1801.02686, 2018.
[5]	P. A. Shinde and Y. Mane, "Advanced vehicle monitoring and tracking system based on Raspberry Pi," in Intelligent Systems and Control (ISCO), 2015 IEEE 9th International Conference on, 2015, pp. 1-6.
[6]	L. S. Martins-Filho, A. C. Santana, R. O. Duarte, and G. A. Junior, "Processor-in-the-Loop Simulations Applied to the Design and Evaluation of a Satellite Attitude Control," 2014.
[7]	P. A. Shinde, Y. Mane, and P. H. Tarange, "Real time vehicle monitoring and tracking system based on embedded Linux board and android application," in Circuit, Power and Computing Technologies (ICCPCT), 2015 International Conference on, 2015, pp. 1-7.
[8]	S. Yamanoor and S. Yamanoor, Raspberry Pi Mechatronics Projects HOTSHOT: Packt Publishing Ltd, 2015.
[9]	A. N. El-Din, "Performance Investigation of Adaptive Guidance Algorithms and its Effectiveness," PHD, Chair of Guidance, Military Technical College, Cairo, 2012.
[10]	V. Kravtchenko, "Tracking color objects in real time," University of British Columbia, 1999.
[11]	S. P. Patil, "Techniques and Methods for Detection and Tracking of Moving Object in a Video," 2015.
[12]	P. Singh, B. Deepak, T. Sethi, and M. D. P. Murthy, "Real-time object detection and tracking using color feature and motion," in Communications and Signal Processing (ICCSP), 2015 International Conference on, 2015, pp. 1236-1241.
[13]	J. Axelson, Serial Port Complete: The Developer's Guide: Lakeview Research LLC, 2007.
[14]	R. M. Baby and R. R. Ahamed, "Optical Flow Motion Detection on Raspberry Pi," in Advances in Computing and Communications (ICACC), 2014 Fourth International Conference on, 2014, pp. 151-152.
[15]	S. Jilani and G. Manasa, "Raspberry Pi Based Color Speaker."
[16]	J. Manasa, J. Pramod, S. Jilani, and M. S. J. Hussain, "Real Time Object Counting using Raspberry pi."
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[18]	L. Zhang, F. Deng, J. Chen, Y. Bi, S. K. Phang, X. Chen, et al., "Vision-Based Target Three-Dimensional Geolocation Using Unmanned Aerial Vehicles," IEEE TRANSACTIONS ON INDUSTRIAL ELECTRONICS, vol. 65, 2018.

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APA Style

Bahaaeldin Gamal Abdelaty, Mohamed Abdallah Soliman, Ahmed Nasr Ouda. (2018). Reducing Human Effort of the Optical Tracking of Anti-Tank Guided Missile Targets via Embedded Tracking System Design. American Journal of Artificial Intelligence, 2(2), 30-35. https://doi.org/10.11648/j.ajai.20180202.13

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ACS Style

Bahaaeldin Gamal Abdelaty; Mohamed Abdallah Soliman; Ahmed Nasr Ouda. Reducing Human Effort of the Optical Tracking of Anti-Tank Guided Missile Targets via Embedded Tracking System Design. Am. J. Artif. Intell. 2018, 2(2), 30-35. doi: 10.11648/j.ajai.20180202.13

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AMA Style

Bahaaeldin Gamal Abdelaty, Mohamed Abdallah Soliman, Ahmed Nasr Ouda. Reducing Human Effort of the Optical Tracking of Anti-Tank Guided Missile Targets via Embedded Tracking System Design. Am J Artif Intell. 2018;2(2):30-35. doi: 10.11648/j.ajai.20180202.13

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@article{10.11648/j.ajai.20180202.13,
  author = {Bahaaeldin Gamal Abdelaty and Mohamed Abdallah Soliman and Ahmed Nasr Ouda},
  title = {Reducing Human Effort of the Optical Tracking of Anti-Tank Guided Missile Targets via Embedded Tracking System Design},
  journal = {American Journal of Artificial Intelligence},
  volume = {2},
  number = {2},
  pages = {30-35},
  doi = {10.11648/j.ajai.20180202.13},
  url = {https://doi.org/10.11648/j.ajai.20180202.13},
  eprint = {https://article.sciencepublishinggroup.com/pdf/10.11648.j.ajai.20180202.13},
  abstract = {Human role reduction in the firing process in the physical military systems is the way to improve the overall system performance and achieve the requirement of operation, especially for the anti-tank guided missile (ATGM). In the second-generation ATGM system, the human operator is responsible for following the target until the missile clash the target (Manual Target Tracking). Achieving an acceptable flight trajectory with getting a minimum miss distance, which is a distance between the center of the target and the impact point, is the factor that used to measure the ATGM performance. This paper is dedicated to designing and implementation of an embedded tracking system capable of dealing with the slow-moving objects, which is carried out as a step to reduce the human operator role during the operation, in addition, upgrade the second-generation anti-tank guided missile system to third generation ATGM system (Automatic target tracking). The present work seeks to take benefits of a System on Chip (SoC) technology, including embedded Linux systems, in the real-time computer vision applications. The nonlinear flight simulation model of the intended missile system is presented in a MATLAB environment. The tracking algorithm is described using Python programing language with the aid of OpenCV library and implemented based on embedded Raspberry Pi system (RPI). Hardware-in-Loop experimental test is carried out to evaluate and validate the methodology of the proposed work to achieve the overall system requirement with an acceptable flight trajectory and minimum miss-distance.},
 year = {2018}
}

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TY  - JOUR
T1  - Reducing Human Effort of the Optical Tracking of Anti-Tank Guided Missile Targets via Embedded Tracking System Design
AU  - Bahaaeldin Gamal Abdelaty
AU  - Mohamed Abdallah Soliman
AU  - Ahmed Nasr Ouda
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PY  - 2018
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DO  - 10.11648/j.ajai.20180202.13
T2  - American Journal of Artificial Intelligence
JF  - American Journal of Artificial Intelligence
JO  - American Journal of Artificial Intelligence
SP  - 30
EP  - 35
PB  - Science Publishing Group
SN  - 2639-9733
UR  - https://doi.org/10.11648/j.ajai.20180202.13
AB  - Human role reduction in the firing process in the physical military systems is the way to improve the overall system performance and achieve the requirement of operation, especially for the anti-tank guided missile (ATGM). In the second-generation ATGM system, the human operator is responsible for following the target until the missile clash the target (Manual Target Tracking). Achieving an acceptable flight trajectory with getting a minimum miss distance, which is a distance between the center of the target and the impact point, is the factor that used to measure the ATGM performance. This paper is dedicated to designing and implementation of an embedded tracking system capable of dealing with the slow-moving objects, which is carried out as a step to reduce the human operator role during the operation, in addition, upgrade the second-generation anti-tank guided missile system to third generation ATGM system (Automatic target tracking). The present work seeks to take benefits of a System on Chip (SoC) technology, including embedded Linux systems, in the real-time computer vision applications. The nonlinear flight simulation model of the intended missile system is presented in a MATLAB environment. The tracking algorithm is described using Python programing language with the aid of OpenCV library and implemented based on embedded Raspberry Pi system (RPI). Hardware-in-Loop experimental test is carried out to evaluate and validate the methodology of the proposed work to achieve the overall system requirement with an acceptable flight trajectory and minimum miss-distance.
VL  - 2
IS  - 2
ER  -

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Author Information

Bahaaeldin Gamal Abdelaty

Electrical Engineering Department, Technical Research Center, Cairo, Egypt
Mohamed Abdallah Soliman

Electrical Engineering Department, Technical Research Center, Cairo, Egypt
Ahmed Nasr Ouda

Electrical Engineering Department, Technical Research Center, Cairo, Egypt

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APA Style

Bahaaeldin Gamal Abdelaty, Mohamed Abdallah Soliman, Ahmed Nasr Ouda. (2018). Reducing Human Effort of the Optical Tracking of Anti-Tank Guided Missile Targets via Embedded Tracking System Design. American Journal of Artificial Intelligence, 2(2), 30-35. https://doi.org/10.11648/j.ajai.20180202.13

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ACS Style

Bahaaeldin Gamal Abdelaty; Mohamed Abdallah Soliman; Ahmed Nasr Ouda. Reducing Human Effort of the Optical Tracking of Anti-Tank Guided Missile Targets via Embedded Tracking System Design. Am. J. Artif. Intell. 2018, 2(2), 30-35. doi: 10.11648/j.ajai.20180202.13

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AMA Style

Bahaaeldin Gamal Abdelaty, Mohamed Abdallah Soliman, Ahmed Nasr Ouda. Reducing Human Effort of the Optical Tracking of Anti-Tank Guided Missile Targets via Embedded Tracking System Design. Am J Artif Intell. 2018;2(2):30-35. doi: 10.11648/j.ajai.20180202.13

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@article{10.11648/j.ajai.20180202.13,
  author = {Bahaaeldin Gamal Abdelaty and Mohamed Abdallah Soliman and Ahmed Nasr Ouda},
  title = {Reducing Human Effort of the Optical Tracking of Anti-Tank Guided Missile Targets via Embedded Tracking System Design},
  journal = {American Journal of Artificial Intelligence},
  volume = {2},
  number = {2},
  pages = {30-35},
  doi = {10.11648/j.ajai.20180202.13},
  url = {https://doi.org/10.11648/j.ajai.20180202.13},
  eprint = {https://article.sciencepublishinggroup.com/pdf/10.11648.j.ajai.20180202.13},
  abstract = {Human role reduction in the firing process in the physical military systems is the way to improve the overall system performance and achieve the requirement of operation, especially for the anti-tank guided missile (ATGM). In the second-generation ATGM system, the human operator is responsible for following the target until the missile clash the target (Manual Target Tracking). Achieving an acceptable flight trajectory with getting a minimum miss distance, which is a distance between the center of the target and the impact point, is the factor that used to measure the ATGM performance. This paper is dedicated to designing and implementation of an embedded tracking system capable of dealing with the slow-moving objects, which is carried out as a step to reduce the human operator role during the operation, in addition, upgrade the second-generation anti-tank guided missile system to third generation ATGM system (Automatic target tracking). The present work seeks to take benefits of a System on Chip (SoC) technology, including embedded Linux systems, in the real-time computer vision applications. The nonlinear flight simulation model of the intended missile system is presented in a MATLAB environment. The tracking algorithm is described using Python programing language with the aid of OpenCV library and implemented based on embedded Raspberry Pi system (RPI). Hardware-in-Loop experimental test is carried out to evaluate and validate the methodology of the proposed work to achieve the overall system requirement with an acceptable flight trajectory and minimum miss-distance.},
 year = {2018}
}

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TY  - JOUR
T1  - Reducing Human Effort of the Optical Tracking of Anti-Tank Guided Missile Targets via Embedded Tracking System Design
AU  - Bahaaeldin Gamal Abdelaty
AU  - Mohamed Abdallah Soliman
AU  - Ahmed Nasr Ouda
Y1  - 2018/11/07
PY  - 2018
N1  - https://doi.org/10.11648/j.ajai.20180202.13
DO  - 10.11648/j.ajai.20180202.13
T2  - American Journal of Artificial Intelligence
JF  - American Journal of Artificial Intelligence
JO  - American Journal of Artificial Intelligence
SP  - 30
EP  - 35
PB  - Science Publishing Group
SN  - 2639-9733
UR  - https://doi.org/10.11648/j.ajai.20180202.13
AB  - Human role reduction in the firing process in the physical military systems is the way to improve the overall system performance and achieve the requirement of operation, especially for the anti-tank guided missile (ATGM). In the second-generation ATGM system, the human operator is responsible for following the target until the missile clash the target (Manual Target Tracking). Achieving an acceptable flight trajectory with getting a minimum miss distance, which is a distance between the center of the target and the impact point, is the factor that used to measure the ATGM performance. This paper is dedicated to designing and implementation of an embedded tracking system capable of dealing with the slow-moving objects, which is carried out as a step to reduce the human operator role during the operation, in addition, upgrade the second-generation anti-tank guided missile system to third generation ATGM system (Automatic target tracking). The present work seeks to take benefits of a System on Chip (SoC) technology, including embedded Linux systems, in the real-time computer vision applications. The nonlinear flight simulation model of the intended missile system is presented in a MATLAB environment. The tracking algorithm is described using Python programing language with the aid of OpenCV library and implemented based on embedded Raspberry Pi system (RPI). Hardware-in-Loop experimental test is carried out to evaluate and validate the methodology of the proposed work to achieve the overall system requirement with an acceptable flight trajectory and minimum miss-distance.
VL  - 2
IS  - 2
ER  -

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