Feature-aided Multi-Target Tracking Method in Sea Clutter Using Scanning Radar Data

• Published in: 2021 IEEE 6th International Conference on Signal and Image Processing (ICSIP) pp. 615 - 619
• Main Authors: Zhu, Yingpei, Wang, Zhen, Yin, Yupei, Chen, Weidong
• Format: Conference Proceeding
• Language: English
• Published: IEEE 22.10.2021
• Subjects: extended target tracking (ETT); Fluctuations; gamma Gaussian inverse Wishart-probability hypothesis density (GGIW-PHD); multiple target tracking (MTT); Radar; Radar clutter; Radar measurements; Radar tracking; scanning radar data; Sea measurements; Target tracking
• DOI: 10.1109/ICSIP52628.2021.9688716

Maritime multi-target tracking (MTT) is an important application scenario of radar target tracking technology, but it still faces huge challenges such as the interference of sea clutter and the fluctuation of target echoes, which leading to the trajectory fragmentation. Additionally, due to radar scanning, targets are extended in azimuth and cannot be regarded as point targets. In this paper, we construct the feature vector by combining the radar echo data with the extension estimation of targets obtained by gamma Gaussian inverse Wishart-probability hypothesis density (GGIW-PHD) filter. Then, the echo features of targets are introduced into MHT framework and trajectory management module, aiming to reduce trajectory fragmentation and improve the integrity of target trajectory. Finally, the effectiveness of the proposed method is verified by measured data.