LCB-CV-UNet: Enhanced Detector for High Dynamic Range Radar Signals

Wang, Yanbin, Chen, Xingyu, Wang, Yumiao, Wang, Xiang, Zang, Chuanfei, Cui, Guolong, Liu, Jiahuan

arXiv.org Artificial Intelligence 

We propose the LCB-CV-UNet to tackle performance degradation caused by High Dynamic Range (HDR) radar signals. Initially, a hardware-efficient, plug-and-play module named Logarithmic Connect Block (LCB) is proposed as a phase coherence preserving solution to address the inherent challenges in handling HDR features. Then, we propose the Dual Hybrid Dataset Construction method to generate a semi-synthetic dataset, approximating typical HDR signal scenarios with adjustable target distributions. Simulation results show about 1% total detection probability improvement with under 0.9% computational complexity added compared with the baseline. Furthermore, it excels 5% over the baseline at the range in 11-13 dB signal-to-noise ratio typical for urban targets. Finally, the real experiment validates the practicality of our model.

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