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Modified arithmetic optimization algorithm for drones measurements and tracks assignment problem

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Abstract

This paper presents efforts to solve the multi-track measurement assignment problem in drone detection and tracking. In many cases, several radars are collectively used to track drones efficiently, generating measurements and several tracks under different circumstances. In this work, several measurements are simulated during a time frame accompanied by the generation of several tracks using the Linear Kalman Filter. The focus is on finding an optimum measurements/track assignment for the simulated measurements and track values. The measurements and track generation are simulated using Stone Soup software. On the other hand, the optimization of the problem is implemented using several evolutionary-based metaheuristic algorithms. This optimization problem is known to be computationally explosive, especially if long time frames are considered. In particular, a new modified method based on the Arithmetic Optimization Algorithm is proposed. The optimization is applied to a formulated cost function that considers uncertainty, false alarms, and existing clutters. Simulations and comparisons show the ability of those evolutionary-based algorithms to solve this kind of problem efficiently. The proposed method obtained promising results compared to other comparative methods used to solve this drone’s measurements and track assignment problem.

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Data availability

Data are available from the authors upon reasonable request.

Notes

  1. Personal Communication with Clement Pira, Thales LAS, France.

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Acknowledgements

This research is supported by the Thales Chair of Excellence Project, Sorbonne Center of Artificial Intelligence, Sorbonne University-Abu Dhabi, UAE.

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Authors and Affiliations

  1. SCAI, Sorbonne University, Abu Dhabi, UAE

    Raed Abu Zitar

  2. Prince Hussein Bin Abdullah College for Information Technology, Al Al-Bayt University, Mafraq, 130040, Jordan

    Laith Abualigah

  3. Hourani Center for Applied Scientific Research, Al-Ahliyya Amman University, Amman, 19328, Jordan

    Laith Abualigah

  4. SCAI, Abu Dhabi, UAE

    Laith Abualigah

  5. Thales Land and Air Systems, Paris, France

    Frederic Barbaresco

  6. Mohammed VI Polytechnic University- Ai movement, Rabat, Morocco

    Amal ElFallah Seghrouchni

  7. Sorbonne University, Paris, France

    Amal ElFallah Seghrouchni

  8. Center for Engineering Application & Technology Solutions, Ho Chi Minh City Open University, Ho Chi Minh, Viet Nam

    Laith Abualigah

  9. Faculty of Information Technology, Middle East University, Amman, 11831, Jordan

    Laith Abualigah

  10. Applied science research center, Applied science private university, Amman, 11931, Jordan

    Laith Abualigah

  11. School of Computer Sciences, Universiti Sains Malaysia, Pulau Pinang, 11800, Malaysia

    Laith Abualigah

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  1. Raed Abu Zitar
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Zitar, R.A., Abualigah, L., Barbaresco, F. et al. Modified arithmetic optimization algorithm for drones measurements and tracks assignment problem. Neural Comput & Applic 35, 10421–10447 (2023). https://doi.org/10.1007/s00521-023-08242-4

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