Multi-Indicator Communication Quality Assessment and Multi-Modal Backup for Resilient USV Cluster Communication

Unmanned surface vehicle (USV) clusters operating in contested maritime environments face communication degradation from jamming, satellite denial, and partial node loss. Existing countermeasures either react after link failure or rely on a single signal quality indicator. A framework is presented that integrates two complementary mechanisms for resilient USV cluster communication: (1) a multi-indicator communication quality metric Qcomm that fuses signal-to-noise ratio, packet loss rate, latency, and temporal stability into a single scalar; and (2) a multi-modal backup communication chain spanning acoustic modem, optical link, and multi-hop RF(Radio Frequency) relay that provides physical-layer redundancy when primary radio frequency links are degraded. Across five representative failure scenarios simulated on a seven-vehicle cluster with 50 independent runs per configuration, the multi-indicator Qcomm metric achieves a mean of 0.521, outperforming single-indicator baselines on the composite Qcomm metric (Cohen’s d = 8.020, p < 0.0001, n = 250 per method); Qcomm is the framework’s own optimization target; this comparison is, therefore, presented as an internal consistency demonstration rather than an independent validation. The framework reduces recovery time from 113.8 s (single-indicator) to 15.3 s—an 86.6% improvement. With the backup communication chain enabled, delivery rates exceed 94% across all methods and scenarios. A direct Monte Carlo ablation (50 seeds × 5 scenarios) reveals that multi-indicator fusion is the primary driver of assessment accuracy and recovery speed, while the multi-modal backup chain is the dominant delivery driver: without it, delivery falls from 94.6% to 24.2%. A sigmoid-blended topology utility function is included as an architectural design component; its independent validation requires extended-duration threat experiments identified as future work. The contributions of this work are the validated multi-indicator fusion metric and the multi-modal backup chain architecture, which together provide a practical foundation for resilient USV communication.

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Publication Details

Journal
Drones
Published
2026-08-24
DOI
https://doi.org/10.3390/drones10090642
Primary Topic
Maritime Navigation and Safety
Type
article
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article

Multi-Indicator Communication Quality Assessment and Multi-Modal Backup for Resilient USV Cluster Communication

Xingda Li, Ling Tan, Pengfei Zhang, Yiping Liu et al.
Drones
Maritime Navigation and Safety
article

Multi-Indicator Communication Quality Assessment and Multi-Modal Backup for Resilient USV Cluster Communication

Xingda Li, Ling Tan, Pengfei Zhang, Yiping Liu, Zhikun Liu, Jianqiang Zhang
article en

Abstract

Unmanned surface vehicle (USV) clusters operating in contested maritime environments face communication degradation from jamming, satellite denial, and partial node loss. Existing countermeasures either react after link failure or rely on a single signal quality indicator. A framework is presented that integrates two complementary mechanisms for resilient USV cluster communication: (1) a multi-indicator communication quality metric Qcomm that fuses signal-to-noise ratio, packet loss rate, latency, and temporal stability into a single scalar; and (2) a multi-modal backup communication chain spanning acoustic modem, optical link, and multi-hop RF(Radio Frequency) relay that provides physical-layer redundancy when primary radio frequency links are degraded. Across five representative failure scenarios simulated on a seven-vehicle cluster with 50 independent runs per configuration, the multi-indicator Qcomm metric achieves a mean of 0.521, outperforming single-indicator baselines on the composite Qcomm metric (Cohen’s d = 8.020, p < 0.0001, n = 250 per method); Qcomm is the framework’s own optimization target; this comparison is, therefore, presented as an internal consistency demonstration rather than an independent validation. The framework reduces recovery time from 113.8 s (single-indicator) to 15.3 s—an 86.6% improvement. With the backup communication chain enabled, delivery rates exceed 94% across all methods and scenarios. A direct Monte Carlo ablation (50 seeds × 5 scenarios) reveals that multi-indicator fusion is the primary driver of assessment accuracy and recovery speed, while the multi-modal backup chain is the dominant delivery driver: without it, delivery falls from 94.6% to 24.2%. A sigmoid-blended topology utility function is included as an architectural design component; its independent validation requires extended-duration threat experiments identified as future work. The contributions of this work are the validated multi-indicator fusion metric and the multi-modal backup chain architecture, which together provide a practical foundation for resilient USV communication.

DronesVol. 10(9)
Naval University of Engineering (CN)
Life below water
Openalex Percentile: Top 13%
Maritime Navigation and Safety
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