An Applied Method for Clustering Extended Targets With UHF Radar

Chunming Kuang,Caijun Wang,Weimin Huang,Biyang Wen

doi:10.1109/access.2020.2997560

Chunming Kuang, Caijun Wang + Show 2 more

Open Access

https://doi.org/10.1109/access.2020.2997560

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Abstract

In this paper, the application of coherent ultra-high frequency (UHF) Doppler radar for ship target detection over river is investigated. Due to the wide beam and high resolution of UHF radar, ship target echoes are usually significantly extended in both the range and Doppler dimensions of the radar Range-Doppler (R-D) spectrum. The range and radial velocity of the extended target are difficult to be determined using a constant false alarm rate (CFAR) detector, especially for the low-radial-velocity case in which the detection performance of CFAR detector is deteriorated due to strong river clutter. To solve this problem, an applied clustering method is proposed to detect and classify multiple targets and obtain corresponding target centers from the CFAR outputs. The target extension characteristics, which are used for clustering, are modeled and employed in segments for different range. The effectiveness of the proposed method is validated using both simulated and field data and the clustering method can classify extended targets without the need of knowing the number of targets beforehand.

Highlights

Detecting and monitoring vessels on inland river are vital to improve efficiency and safety of inland navigation [1], [2]
Due to its high resolution, the ship echoes are significantly extended in both the range and Doppler dimensions of the R-D spectrum
The target extension characteristics are firstly analyzed in terms of the target range, and an applied clustering method is proposed

Summary

INTRODUCTION

Detecting and monitoring vessels on inland river are vital to improve efficiency and safety of inland navigation [1], [2]. The target parameters such as range and radial velocity can be estimated from the output of the clustering algorithm Such a method is able to detect and identify extended target in strong river clutter. Targets 1, 2, and 3 are in the clutter region, where some missed alarms and false alarms from the CFAR detector are observed, the error is slightly larger These 3 targets are correctly classified in the end, the proposed clustering method works well even with river clutter. No target point is detected when SCNR is less than 12 dB, whereas more

PRACTICAL APPLICATION

Findings

CONCLUSION