Spatial-temporal joint constraints based tracking method for infrared UAV

Xueli Xie; Jianxiang Xi; Ruitao Lu; Xiaogang Yang; Wenxin Xia

doi:10.1117/12.3006233

18 December 2023 Spatial-temporal joint constraints based tracking method for infrared UAV

Xueli Xie, Jianxiang Xi, Ruitao Lu, Xiaogang Yang, Wenxin Xia

Proceedings Volume 12960, AOPC 2023: Infrared Devices and Infrared Technology; and Terahertz Technology and Applications; 129600A (2023) https://doi.org/10.1117/12.3006233
Event: Applied Optics and Photonics China 2023 (AOPC2023), 2023, Beijing, China

Abstract

The misuse of UAVs has spurred the development of Anti-UAV technology. Infrared detector-based UAV tracking technology has become a research hotspot in the field of the Anti-UAV technology, but still faces the problem of tracking failure caused by background interference. To improve the accuracy and stability of infrared UAV tracking in the complex environments, a spatial-temporal joint constraints based infrared UAV tracking algorithm is proposed. First, a feature pyramid-based Siamese backbone is constructed to enhance the capability of feature extraction for infrared UAVs through cross-scale feature fusion. Next, a region proposal network based on spatio-temporal joint constraints is proposed. Under the constraints of template appearance features and target motion information, the location probability distribution of the infrared UAV is predicted in the entire image, and the prior anchor box is guided to focus on the candidate regions, realizing a soft adaptive search region selection mechanism. By focusing the search area, the anti-background interference capability of the local search strategy and the recapture capability of global search strategy are fused, which effectively mitigates the negative sample interference brought by global search and further enhances the discriminability of target features. Finally, the proposed algorithm is evaluated on the Anti-UAV dataset, achieving precision, success rate, and average precision of 89.5%, 64.9%, and 65.6%, respectively, with a tracking speed of 18.5 FPS. Compared with other advanced tracking algorithms, the proposed algorithm obtains better tracking performance and superior tracking performance in complex scenarios such as fast motion, thermal crossover and distractors interference.

(2023) Published by SPIE. Downloading of the abstract is permitted for personal use only.

Citation Download Citation

Xueli Xie, Jianxiang Xi, Ruitao Lu, Xiaogang Yang, and Wenxin Xia "Spatial-temporal joint constraints based tracking method for infrared UAV", Proc. SPIE 12960, AOPC 2023: Infrared Devices and Infrared Technology; and Terahertz Technology and Applications, 129600A (18 December 2023); https://doi.org/10.1117/12.3006233

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KEYWORDS

Detection and tracking algorithms

Unmanned aerial vehicles

Infrared radiation

Infrared search and track

Infrared imaging

Feature extraction

Convolution

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