小型无人机遥控器信号跳频参数估计方法

Estimation methods of frequency hopping parameters of small-scale UAV remote controllers

小型无人机遥控器信号工作带宽约为80 MHz,传统的无人机遥控器信号参数估计方法有效地完成参数估计工作的前提是采集完整频段的信号,这在加大了参数估计难度的同时提高了对信号采集设备的要求。针对这一问题,基于频域互相关运算获得相邻时隙采样信号的频域互相关特性,通过引入逻辑回归、门限自适应去噪算法估计无人机遥控器信号参数,该方法不仅避免了设定阈值,提高了参数估计性能,而且能够估计在采样频率有限场景下所采集的时域非连续无人机遥控器信号的跳频参数。基于仿真和实测数据对比分析了传统的2种跳频信号参数估计方法与所提方法的参数估计性能。实验结果表明:与传统参数估计方法相比,无论小型无人机遥控器信号能否被完整采集,所提方法在参数估计精度方面均具有较大优势。且当信噪比超过-3 dB时,所提方法的参数估计性能达到饱和。

The working bandwidth of the signals of a remote controller for a small-scale unmanned aerial vehicle(UAV)is about 80 MHz.The premise of the traditional UAV remote control signal parameter estimation method to effectively estimate the parameters lies in the acquisition of the complete frequency band signals,which increases the difficulty of parameter estimation and enhances the requirements of the signal acquisition equipment.In this view,based on frequency domain cross-correlation operation to obtain frequency domain cross-correlation characteristics of sampled signals between adjacent time intervals,this paper proposes a parameter estimation method for the signals of a UAV remote controller by introducing logical regression and the threshold self-adaption denoising algorithm.This proposed method not only eliminates the fixed threshold to improve the performance of parameter estimation,but also estimates the frequency hopping parameters of the discontinuous time-domain signals of the UAV remote controller collected in scenarios with limited sampling frequency.Based on the simulation and the measured data,performance of the frequency hopping signal parameters of the two traditional estimation methods is compared with that of the proposed method.The simulation and experimental results show that the parameter estimation accuracy of the proposed method outperforms that of its traditional counterparts,whether the signals of the UAV remote controller are completely collected or not.In addition,when the signal-to-noise ratio(SNR)is over-3 dB,the performance of the parameter estimation of the proposed method reaches the saturation performance.