| 摘要: |
| 随着新时代科技的发展,无人机的应用越来越多,对无人机的检测与管理逐渐受到重视。针对传统算法对悬停无人机检测效果不理想的问题,本文提出一种基于转速补偿的时频域积累检测算法。首先,通过经验模态分解(Empirical Mode Decomposition,EMD)和快速傅里叶变换(Fast Fourier Transform,FFT)相结合的方法估计多个旋翼的转速。进而,构造对应的补偿函数对各个旋翼回波信号进行补偿,使得旋翼的微多普勒频率集中在一个多普勒单元内。随后,再将补偿后的回波信号进行短时傅里叶变换(Short-Time Fourier Transform,STFT),将各个旋翼的时频域信号相加再通过FFT进行相参积累,以达到改善对悬停无人机检测性能的目的。仿真实验表明,该方法可以有效实现对悬停无人机的目标检测和转速估计。 |
| 关键词: 悬停无人机 微多普勒 经验模态分解(EMD) 短时傅里叶变换(STFT) 时频域积累检测 |
| DOI： |
| 分类号:TN95 |
| 基金项目:国家自然科学基金(No.62161029) |
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| A Time-Frequency Domain Accumulation Detection Algorithm for Hovering UVA Based on Rotational Speed Compensation |
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饶烜
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| Abstract: |
| As the new era of technology advances, the use ofunmanned aerial vehicles (UVA) is becoming more widespread, leading to a growingemphasis on the monitoring and regulation of these UVA. To address the inadequacies of conventional algorithms in detecting hovering UVA, this study introduces an innovative time-frequency domain accumulation detection algorithm that incorporates rotational speed compensation. Firstly, the rotational speeds of multiple rotors are estimated by combining Empirical Mode Decomposition (EMD) and Fast Fourier Transform (FFT). Subsequently, corresponding compensation functions are constructed to adjust the echo signals of each rotor, ensuring that the micro-Doppler frequencies of the rotors are concentrated within a single doppler unit. Following this, the compensated echo signals are subjected to Short-Time Fourier Transform (STFT). The time-frequency domain signals from each rotor are then summed and processed through a FFT for coherent accumulation, with the aim of enhancing the detection performance for hovering drones. Simulation experiments indicate that this method can effectively achieve target detection and rotational speed estimation for hovering UVA. |
| Key words: hovering unmanned aerial vehicles (UVA) micro-Doppler empirical mode decomposition (EMD) short-time Fourier transform (STFT) time-frequency domain accumulation detection[ ] |