MobileNet-V3-based sea-land segmentation for maritime search radars

The effective perception of marine detection scenarios is essential for maritime search pulse radar to detect and track maritime targets. However, the dynamically changing and complex marine environment makes it challenging for maritime search pulse radar to accurately perceive the sea and land regions. To improve the accuracy of sea-land region perception, and reduce the computation and complexity of algorithm of the network, this paper proposes a MobileNet-V3-based maritime search pulse radar sea-land segmentation method. Firstly, a radar sea-land segmentation dataset based on PPI (Plan Position Indicator) is constructed using real measured data from different scenarios and sea conditions. Subsequently, the MobileNetV3 network is trained on this dataset to achieve sea-land segmentation for maritime search pulse radar. Experimental results demonstrate that the segmentation accuracy of the MobileNetV3-L-based radar sea-land segmentation method surpasses its competitors.