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Robust direction of arrival estimation approach for unmanned aerial vehicles at low signal-to-noise ratios

机译：低信噪比下无人空中车辆的到达估计方法的鲁棒方向

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摘要

The conventional methods used to estimate the direction of arrival (DOA) of linear frequency modulated (LFM) signals at low signal-to-noise ratios (SNRs), such as the echoes reflected by a small unmanned aerial vehicle (UAV), demonstrate major performance deterioration. In order to eliminate the problem and achieve highly accurate DOA estimation for low-SNR echoes, this paper proposes a novel estimation approach that applies two accumulative methods based on fractional Fourier transform (FrFT). According to the findings of this paper, the algorithm directly accumulates the FrFT result of each echo when it is not possible to determine in advance the speed of the target. When the radial velocity of the small UAV has been estimated ahead of time, the algorithm performs phase compensation to enhance the accumulative effect. Through coherent integration, the algorithm then extracts all the peaks of the target echo waveform, which are then used for the construction of a fractional autocorrelation matrix. Thereafter, multiple signal classification is employed for DOA estimation. Furthermore, with the proposed algorithm, the DOAs of multi-target echoes can be estimated accurately. The effectiveness of the proposed algorithm was verified using Monte-Carlo simulation trials, and the root-mean-square-error of DOA estimation was close to the Cramer-Rao bound.
机译：用于估计线性频率调制（LFM）信号的到达方向（DOA）以低信噪比（SNR），例如由小无人驾驶飞行器（UAV）反射的回波，展示主要方法性能恶化。为了消除问题并实现低SNR回波的高精度DOA估计，提出了一种基于分数傅里叶变换（FRFT）的两种累积方法的新型估计方法。根据本文的研究结果，算法在不可能先确定目标的速度时，直接累积每个回波的FRFT结果。当提前估计小UV的径向速度时，该算法执行相位补偿以增强累积效果。通过相干积分，算法然后提取目标回波波形的所有峰值，然后用于构造分数自相关矩阵。此后，采用多个信号分类用于DOA估计。此外，利用所提出的算法，可以精确地估计多目标回波的DOA。使用Monte-Carlo仿真试验验证了所提出的算法的有效性，DOA估计的根均方误差接近Cramer-Rao绑定。

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