Cooperative search method for distributed infrared sensors based on target identity determination

Efficient cooperative search is critical to the perception capability of distributed aerial vehicles. However, passive angle-only infrared sensors have limited Fields of View (FOV), making rapid multi-node target acquisition and identity determination challenging in dense multi-target scenarios. To address this problem, this paper proposes a cooperative search method for distributed infrared sensors based on target identity determination. The task is described by a finite-horizon formulation that evaluates the pointing path of each auxiliary sensor using normalized identity-confirmed acquisition time and probabilistic coverage under identity determination constraints. The sensor that first detects the target serves as the primary sensor, whose position and two-dimensional observation are used to construct a probabilistic feasible region. For real-time implementation, a dynamic search sector constructed from proximal, central, and remote characteristic points is used to determine the search region and pointing path. After candidate targets are captured, a spatio-temporal identity determination cost is calculated using the common perpendicular distance between bearing lines and temporal consistency. The confirmed result is then used to guide the remaining sensors toward the same target. Long-range simulations achieve a minimum Identity Determination Search Precision (IDSP) of 80% under high target density and large angular measurement errors. Over 25 sensor-target configurations, the method achieves an average IDSP of 88.96%, higher than the average values of three representative multi-target association methods, while maintaining sub-millisecond association computation time. A near-range simulation based on flight-test data confirms this advantage under increased target density, and outdoor flight experiments demonstrate the end-to-end closed-loop feasibility of the proposed method under real platform constraints. These results are of practical value for improving the cooperative perception capability of distributed airborne infrared sensors.

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Publication Details

Journal
Chinese Journal of Aeronautics
Published
2026-11-01
DOI
https://doi.org/10.1016/j.cja.2026.104551
Primary Topic
Infrared Target Detection Methodologies
Type
article
Field-Weighted Citation Impact
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article

Cooperative search method for distributed infrared sensors based on target identity determination

Kaixiao Ye, Yuhang Zheng, Wenxing Fu, Tong Zhang et al.
Chinese Journal of Aeronautics
Infrared Target Detection Methodologies
article

Cooperative search method for distributed infrared sensors based on target identity determination

Kaixiao Ye, Yuhang Zheng, Wenxing Fu, Tong Zhang, Tao Yang, Hanming CHEN
article en

Abstract

Efficient cooperative search is critical to the perception capability of distributed aerial vehicles. However, passive angle-only infrared sensors have limited Fields of View (FOV), making rapid multi-node target acquisition and identity determination challenging in dense multi-target scenarios. To address this problem, this paper proposes a cooperative search method for distributed infrared sensors based on target identity determination. The task is described by a finite-horizon formulation that evaluates the pointing path of each auxiliary sensor using normalized identity-confirmed acquisition time and probabilistic coverage under identity determination constraints. The sensor that first detects the target serves as the primary sensor, whose position and two-dimensional observation are used to construct a probabilistic feasible region. For real-time implementation, a dynamic search sector constructed from proximal, central, and remote characteristic points is used to determine the search region and pointing path. After candidate targets are captured, a spatio-temporal identity determination cost is calculated using the common perpendicular distance between bearing lines and temporal consistency. The confirmed result is then used to guide the remaining sensors toward the same target. Long-range simulations achieve a minimum Identity Determination Search Precision (IDSP) of 80% under high target density and large angular measurement errors. Over 25 sensor-target configurations, the method achieves an average IDSP of 88.96%, higher than the average values of three representative multi-target association methods, while maintaining sub-millisecond association computation time. A near-range simulation based on flight-test data confirms this advantage under increased target density, and outdoor flight experiments demonstrate the end-to-end closed-loop feasibility of the proposed method under real platform constraints. These results are of practical value for improving the cooperative perception capability of distributed airborne infrared sensors.

Chinese Journal of Aeronautics
Northwestern Polytechnical University (CN)
Openalex Percentile: Top 19%
Infrared Target Detection Methodologies
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