Rotor–Body Echo Separation Using a Cyclic-Power-Guided Soft Mask from UAV Radar Signals

TL;DR

This paper introduces a new method to separate rotor and body signals in UAV radar data using a soft mask based on cyclic power patterns.

Contribution

The novel Cyclic-Power-Guided Soft Mask (CPGSM) framework improves rotor–body separation in UAV radar signals.

Findings

CPGSM improves micro-Doppler continuity and reduces body leakage in low SNR conditions.

The method provides stable performance across 5–30 dB SNR and consistent rotor-speed estimates.

CPGSM outperforms hard DC isolation and EMD/VMD in separating rotor and body components.

Abstract

Rotor-induced micro-Doppler signatures are essential for radar-based characterization of rotary-wing UAVs, but practical echoes are often dominated by a strong quasi-static body return concentrated near zero Doppler. In hovering or low-speed scenarios, rotor-induced components may intermittently overlap this near-zero region, where hard DC suppression discards informative rotor content and fragments micro-Doppler structures. Data-driven decompositions such as EMD and VMD avoid fixed cutoffs, yet without explicit constraints on rotor periodicity they are vulnerable to mode mixing and residual leakage under low-SNR conditions. This paper proposes a Cyclic-Power-Guided Soft Mask (CPGSM) framework that exploits cyclostationary periodicity as a physically grounded prior for rotor–body separation. A CPS-guided soft masking procedure consisting of a DC-dominant overlap band is first identified from quasi-static dominance; within this band, cyclic power spectrum analysis yields a continuous rotor-consistency score that guides smooth time–frequency soft allocation, while deterministic assignment is applied elsewhere. Simulations demonstrate improved micro-Doppler continuity, reduced body leakage, and more stable performance from 5–30 dB SNR compared with hard DC isolation and EMD/VMD, together with consistent rotor-speed estimates across sensing configurations.

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