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

TL;DR

This paper introduces LCB-CV-UNet, a novel HDR radar signal detector that combines a hardware-efficient module and a semi-synthetic dataset, achieving improved detection performance with minimal added complexity.

Contribution

The paper presents the Logarithmic Connect Block and a Dual Hybrid Dataset Construction method, enhancing HDR radar detection accuracy and robustness.

Findings

1% increase in total detection probability

Less than 0.9% additional computational complexity

5% improvement at 11-13 dB SNR in urban scenarios

Abstract

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.