Advanced algorithm for improving the quality of filtering and tracking multiple marine targets for command and control

141 views

Authors

  • Vo Xung Ha (Corresponding Author) Institute of Radar, Academy of Military Science and Technology
  • Nguyen Trugn Kien Academy of Military Science and Technology
  • Nguyen Phung Bao Institute of System Integration, Military Technical Academy

DOI:

https://doi.org/10.54939/1859-1043.j.mst.94.2024.31-38

Keywords:

Radar image; Complex target; Binary image; Estimated coordinates.

Abstract

In this article, an advanced algorithm for improving the quality of filtering and tracking multiple marine targets for command and control based on analysing high-resolution radar images is proposed. The proposed method includes two stages. The first stage of the proposed method is used for estimating target characteristics such as: center coordinates, reflected energy, movement direction and window tracking size. These charateristics are used as inputs for the second stages. The effectiveness of the algorithm is evaluated by simulation of filtering tracking two targets moving close together using MATLAB tool. The simulation results are compared with other methods such as GNN and JPDA. The results show that the proposed algorithm limits the limitations of the GNN and JPDA methods that confuse or lose the trajectory of the above algorithms.

References

[1]. Blackman, S., and R. Popoli. “Design and Analysis of Modern Tracking Systems”. Artech House Radar Library, Boston, (1999).

[2]. Musicki, D., and R. Evans. "Joint Integrated Probabilistic Data Association: JIPDA." IEEE transactions on Aerospace and Electronic Systems. Vol. 40, Number 3, pp. 1093 –1099, (2004). DOI: https://doi.org/10.1109/TAES.2004.1337482

[3]. Werthmann, J. R.. "Step-by-Step Description of a Computationally Efficient Version of Multiple Hypothesis Tracking." In International Society for Optics and Photonics, Vol. 1698, pp. 228 – 301, (1992). DOI: https://doi.org/10.1117/12.139379

[4]. Zhou, H.; Huang, H.; Zhao, H.; Zhao, X.; Yin, X. “Adaptive Unscented Kalman Filter for Target Tracking in the Presence of Nonlinear Systems Involving Model Mismatches. Remote Sens”. 9, 657, (2017). DOI: https://doi.org/10.3390/rs9070657

[5]. Amirzadeh, A.; Karimpour, A. “An interacting Fuzzy-Fading-Memory-based Augmented Kalman Filtering method for manoeuvring target tracking”. Digit. Signal Process. 23, 1678–1685, (2013). DOI: https://doi.org/10.1016/j.dsp.2013.05.002

[6]. A´ lvarez, M. Rosa-Zurera (EURASIPMember), J. C. Nieto-Borge, and M. P. Jarabo-Amores, “Artificial Neural Network-Based Clutter Reduction Systems for ship size Estimation in Maritime Radars”, EURASIP Journal on Advances in Signal Processing, Hindawi Publishing Corporation (2010). DOI: https://doi.org/10.1155/2010/380473

[7]. Hamza Bounaceur, Ali Khenchaf, Jean-Marc Le Caillec, “Analysis of small sea-surface targets detection performance according to airborne radar parameters in abnormal weather environments”, Sensors, 22, 3263, (2022). DOI: https://doi.org/10.3390/s22093263

[8]. Xung Ha Vo, Trung Kien Nguyen, Phung Bao Nguyen, Van Minh Duong. “A Real-time Processing Algorithm for Multi-Plot Marine Targets Based on Radar Image Decomposition”. 2023 12th International Conference on Control, Automation and Information Sciences (ICCAIS), Hanoi, Vietnam, pp. 781-786, (2023), doi: 10.1109/ICCAIS59597.2023.10382401. DOI: https://doi.org/10.1109/ICCAIS59597.2023.10382401

Published

22-04-2024

How to Cite

Vo, X. H., Nguyễn Trung Kiên, and Nguyễn Phùng Bảo. “Advanced Algorithm for Improving the Quality of Filtering and Tracking Multiple Marine Targets for Command and Control”. Journal of Military Science and Technology, vol. 94, no. 94, Apr. 2024, pp. 31-38, doi:10.54939/1859-1043.j.mst.94.2024.31-38.

Issue

Section

Electronics & Automation

Categories

Most read articles by the same author(s)