信号处理2026，Vol.42Issue(6)：843-856,14.DOI:10.12466/xhcl.2026.06.006
基于TELSET的低慢小无人机旋翼参数估计
Rotor Parameter Estimation of Low,Slow,and Small Unmanned Aerial Vehicles Based on TELSET
摘要
Abstract
With the widespread use of low-altitude,slow-speed,and small unmanned aerial vehicles(UAVs)across various applications,the associated airspace security risks have become increasingly significant.Consequently,the de-velopment of high-precision and reliable UAV identification technologies has become essential for effective low-altitude risk management and airspace safety assurance.Physical parameters such as rotor speed and blade length play an impor-tant role in UAV identification.Therefore,this study focuses on accurately estimating these parameters through time-frequency analysis of UAV echo signals.However,conventional parameter estimation methods based on traditional time-frequency analysis often suffer from spectral leakage and cross-term interference when processing the complex echoes of multi-rotor UAVs.These limitations lead to blurred micro-Doppler signatures and prevent the estimation accuracy from meeting practical application requirements.To address these issues,a feature extraction method based on the threshold energy local maximum synchronous extraction transform(TELSET)is proposed.The proposed method determines an adaptive energy threshold according to the background energy distribution in the time-frequency domain,effectively sup-pressing energy diffusion caused by fixed windowing and reducing cross-term interference in multi-rotor echo signals.In addition,the time-frequency ridge extraction strategy of the local maximum synchronous extraction transform(LSET)is further improved by applying Gaussian sliding averaging along the time axis,which enhances the energy concentra-tion of rotor micro-motion features.Validation experiments using measured millimeter-wave radar data and a public L-band dataset demonstrate that the TELSET method achieves both high time-frequency resolution and accurate rotor pa-rameter estimation.Compared with the short time Fourier transform(STFT),the proposed method reduces entropy by 2.86 dB,decreases the rotor speed estimation error to 0.86%,and improves blade length estimation accuracy by an aver-age of 6.17%.These results demonstrate that the proposed method provides a reliable technical approach for UAV identi-fication in low-altitude environments.关键词
毫米波雷达/旋翼参数估计/微多普勒特性/能量阈值局部极大值同步提取变换Key words
millimeter-wave radar/rotor parameter estimation/micro-Doppler characteristics/threshold energy local maximum synchronous extraction transform分类
信息技术与安全科学引用本文复制引用
陈啸凯,王向荣,黄晓红..基于TELSET的低慢小无人机旋翼参数估计[J].信号处理,2026,42(6):843-856,14.基金项目
华北理工大学研究生创新项目(2026S33) （2026S33）
华北理工大学国防科研项目(ZD-GF-202428) Innovation Project for Postgraduates of North China University of Science and Technology(2026S33) （ZD-GF-202428）
National Defense Research Project of North China University of Science and Technology(ZD-GF-202428) （ZD-GF-202428）
