Ionospheric Clutter Image Segmentation Method of High Frequency Surface Wave Radar Based on the Improved Deeplab Network

High Frequency Surface Wave Radar(HFSWR) can achieve over-the-horizon detection, which effectively detects and tracks the ships and ultra-low altitude aircrafts, as well as the acquisition of sea state information such as icebergs and ocean currents and so on. However, HFSWR is seriously affected by clutters, especially sea clutter and ionospheric clutter. In this paper, we propose a deep learning image semantic segmentation method based on optimized Deeplabv3+ network to resolve the automatic detection of ionospheric clutter that uses the Range-Doppler spectrum images of HFSWR during the typhoon as experimental data, which avoids the disadvantage of traditional segmentation methods that require a large amount of a priori experience.