提升高动态雷达信号检测精度，兼顾效率与真实场景适用性。
LCB-CV-UNet: Enhanced Detector for High Dynamic Range Radar Signals
- 引入对数连接模块，保留相位信息以应对高动态信号挑战。
- 构建半合成数据集，可调节目标分布模拟城市环境典型信噪比。
- 实测验证有效，信噪比11-13 dB时检测率提升5%，计算开销增加不足0.9%。
针对高动态范围（HDR）雷达信号导致的检测性能下降问题，本文提出LCB-CV-UNet。首先设计了一种硬件高效、即插即用的对数连接块（Logarithmic Connect Block, LCB），作为保持相位一致性的解决方案，以应对处理HDR特征的固有挑战。其次，提出双混合数据集构建方法，生成半合成数据集，可调节目标分布以近似典型HDR信号场景。仿真结果表明，相比基线模型，总检测概率提升约1%，计算复杂度增加低于0.9%；在城市目标典型的11-13 dB信噪比范围内，检测性能优于基线5%。最后，通过真实实验验证了模型的实际可行性。
原文摘要 · Abstract (English)
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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