Multi-altitude, multimodal maritime surveillance system

Markchom, T. ORCID: https://orcid.org/0000-0002-2685-0738, Kourounioti, O., Marturini, M., Bratskas, R., Wohlleben, K., Boyle, J. ORCID: https://orcid.org/0000-0002-5785-8046, Chen, L., Voskopoulos, G., Kontopoulos, C., Veigl, S., Opitz, A., Gkamaris, A., Papachristos, D., Lunic, D., Ferryman, J., Kriechbaum-Zabini, A. and Leventakis, G. (2026) Multi-altitude, multimodal maritime surveillance system. IEEE Sensors Journal, 26 (5). 7101 -7119. ISSN 1558-1748 doi: 10.1109/JSEN.2025.3649549

Abstract/Summary

Maritime surveillance plays a vital role in protecting coastal and maritime environments. However, traditional maritime surveillance systems that rely on singlealtitude, single-modality sensors suffer from limited coverage and sensitivity to weather conditions. To address these limitations, this article presents a comprehensive maritime surveillance system that integrates multialtitude, multimodal sensor platforms, including ground-based sensors, lowaltitude uncrewed aerial vehicles (UAVs), and satellites, for maritime threat detection. Each platform is equipped with dedicated modules for object detection, tracking, and geolocation, leveraging its unique sensing capabilities to contribute to a coordinated surveillance system. Moreover, a novel multialtitude, multimodal maritime surveillance (MAMMS) dataset is introduced. This dataset includes data from these sensor types, enabling rigorous benchmarking across varying operational conditions. The experimental results indicate that the system achieved an average mAP of 50.5% across all sensors in object detection, surpassing state-of-the-art models in most cases. For object tracking, the system achieved an average ID F1-Score (IDF1) of 0.263 and a higher order tracking accuracy (HOTA) of 0.297, comparable to state-of-the-art methods, while exhibiting substantially fewer average ID switches (IDSWs) (75.46) compared to the strongest baseline (301.46). For geolocation approximation, the system achieved an error of less than 11 m in certain scenarios. A case study was also conducted to assess the sensor platforms when integrated into a multisensor fusion system. The case study showed that complementary information from different platforms can help reduce false alarms and improve object geolocation accuracy. The dataset is available at https://zenodo.org/records/17979190

Item Type	Article
URI	https://centaur.reading.ac.uk/id/eprint/127545
Identification Number/DOI	10.1109/JSEN.2025.3649549
Refereed	Yes
Divisions	Science > School of Mathematical, Physical and Computational Sciences > Department of Computer Science
Publisher	IEEE
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