Branch-and-Bound Method for Just-in-Time Optimization of Radar Search Patterns

Briheche, Yann; Barbaresco, Frédéric; Bennis, Fouad; Chablat, Damien

doi:10.1007/978-3-030-26458-1_25

Nature-Inspired Methods for Metaheuristics Optimization

2020

DOI: 10.1007/978-3-030-26458-1_25

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Branch-and-Bound Method for Just-in-Time Optimization of Radar Search Patterns

Yann Briheche

Frédéric Barbaresco

Fouad Bennis

et al.

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Cited by 3 publications

(1 citation statement)

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“…This necessitates the development of adaptive RRM techniques, which vary with the target and interference environment that the vessel is encountering at any given time. RRM techniques have the potential to enhance radar performance compared to non-adaptive techniques, but further study of performance, complexity and robustness needs to be carried out [21,2,12,1,4,3,23].…”

mentioning

confidence: 99%

Multi-criteria Performance Assessment of Adaptive Radar Resources Management: Application to Naval Scenario

Labreuche

Buron

Moo

et al. 2019

2019 20th International Radar Symposium (IRS)

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Multifunction radars (MFR) must achieve their capability requirements in an increasingly complex environment, populated with diverse and hostile targets (e.g. low Radar Cross-Section, low speed targets in clutter or high speed, ballistic targets) in saturating scenarios (due to e.g. RF interference or threats). These radar systems are increasingly exploiting active electronically scanned array (AESA) technology to dynamically schedule the use of multiple functions in a short duration. However, the increasing complexity and adaptive nature of MFR radar makes it very difficult to specify their performance in a way

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mentioning

confidence: 99%

Multi-criteria Performance Assessment of Adaptive Radar Resources Management: Application to Naval Scenario

Labreuche

Buron

Moo

et al. 2019

2019 20th International Radar Symposium (IRS)

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AI-Augmented Multi Function Radar Engineering with Digital Twin: Towards Proactivity

Klein

Carpentier

Jeanclaude

et al. 2020

2020 IEEE Radar Conference (RadarConf20)

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Thales new generation digital multi-missions radars, fully-digital and software-defined, like the Sea Fire and Ground Fire radars, benefit from a considerable increase of accessible degrees of freedoms to optimally design their operational modes. To effectively leverage these design choices and turn them into operational capabilities, it is necessary to develop new engineering tools, using artificial intelligence. Innovative optimization algorithms in the discrete and continuous domains, coupled with a radar Digital Twins, allowed construction of a generic tool for "search" mode design (beam synthesis, waveform and volume grid) compliant with the available radar time budget. The high computation speeds of these algorithms suggest tool application in a "Proactive Radar" configuration, which would dynamically propose to the operator, operational modes better adapted to environment, threats and the equipment failure conditions.

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Efficiently Evaluating Radar Performance Models Using Upper Bounds

Vollweiter

2023

2023 26th International Conference on Information Fusion (FUSION)

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Branch-and-Bound Method for Just-in-Time Optimization of Radar Search Patterns

Cited by 3 publications

References 6 publications

Multi-criteria Performance Assessment of Adaptive Radar Resources Management: Application to Naval Scenario

Multi-criteria Performance Assessment of Adaptive Radar Resources Management: Application to Naval Scenario

AI-Augmented Multi Function Radar Engineering with Digital Twin: Towards Proactivity

Efficiently Evaluating Radar Performance Models Using Upper Bounds

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