UAV Recognition Confidence: A Key Evaluation Metric for UAV Recognition Performance

Radar plays a pivotal role throughout the entire Counter-Unmanned Aerial Vehicle (C-UAV) process, and there is an urgent need for radar technologies capable of effectively detecting and recognizing non-cooperative Unmanned Aerial Vehicles (UAVs). However, the commonly emphasized UAV True Positive Ratio (TPR) fails to adequately reflect radar performance in environments with high bird density. Frequent bird activity leads to numerous false UAV alarms and unreliable recognition results. To address this issue, this paper introduces the concept of UAV Recognition Confidence (URC), a comprehensive metric that quantifies the credibility of UAV recognition by jointly considering recognition performance indicators and environmental factors. Simulations and field measurements employ a bird random walk model and real-time trajectory statistics to represent the dynamic population variations of birds. Both simulation and X-band radar experimental results verify that the proposed URC framework can effectively characterize the recognition capability of radar systems by capturing the complex interactions between the UAV and surrounding avian activities.

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Publication Details

Journal
Drones
Published
2026-03-26
DOI
https://doi.org/10.3390/drones10040239
Primary Topic
Advanced SAR Imaging Techniques
Type
article
Field-Weighted Citation Impact
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article

UAV Recognition Confidence: A Key Evaluation Metric for UAV Recognition Performance

Deyong Kong, Zhongbo Su, Jiangkun Gong, Di Li et al.
Drones
Advanced SAR Imaging Techniques
article

UAV Recognition Confidence: A Key Evaluation Metric for UAV Recognition Performance

Deyong Kong, Zhongbo Su, Jiangkun Gong, Di Li, Weitao Zong, Jun Yan
article en

Abstract

Radar plays a pivotal role throughout the entire Counter-Unmanned Aerial Vehicle (C-UAV) process, and there is an urgent need for radar technologies capable of effectively detecting and recognizing non-cooperative Unmanned Aerial Vehicles (UAVs). However, the commonly emphasized UAV True Positive Ratio (TPR) fails to adequately reflect radar performance in environments with high bird density. Frequent bird activity leads to numerous false UAV alarms and unreliable recognition results. To address this issue, this paper introduces the concept of UAV Recognition Confidence (URC), a comprehensive metric that quantifies the credibility of UAV recognition by jointly considering recognition performance indicators and environmental factors. Simulations and field measurements employ a bird random walk model and real-time trajectory statistics to represent the dynamic population variations of birds. Both simulation and X-band radar experimental results verify that the proposed URC framework can effectively characterize the recognition capability of radar systems by capturing the complex interactions between the UAV and surrounding avian activities.

DronesVol. 10(4)
Wuhan University (CN), Hubei University Of Economics (CN), State Key Laboratory of Information Engineering in Surveying Mapping and Remote Sensing (CN), Guangzhou HKUST Fok Ying Tung Research Institute (CN)
Openalex Percentile: Top 6%
Advanced SAR Imaging Techniques
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UAV Recognition Confidence: A Key Evaluation Metric for UAV Recognition Performance — Deyong Kong, Zhongbo Su, et al. · Drones (2026) | TGRS Research Map | TGRS