This paper considers the time difference of arrival (TDOA) and frequency difference of arrival (FDOA) estimation problem for joint localization using unmanned aerial vehicles (UAVs), involving range migration (RM) and Doppler ambiguity within observation interval. A robust estimation method based on interpolation and resampling is proposed. Specifically, the interpolation artificially increases the pulse repetition frequency (PRF). After that, the resampling eliminates the coupling between range frequency and slow time. Finally, a coherent integration step based on inverse discrete Fourier transform (IDFT) is used to achieve parameter estimation and suppress the grating lobes caused by interpolation. The proposed method could be efficiently implemented by fast Fourier transform (FFT), inverse FFT (IFFT) and non-uniform FFT (NUFFT) without parameter searching procedures. Numerical experiments indicate that the proposed method has nearly optimal anti-noise performance but much lower computational complexity than the maximum likelihood estimator, which makes it more competitive in practical applications.

本文考虑了使用无人机（UAV）进行联合定位的到达时间差（TDOA）和到达频率差（FDOA）估计问题，涉及距离偏移（RM）和观测区间内的多普勒模糊度。提出了一种基于插值和重采样的鲁棒估计方法。具体来说，插值人为地增加了脉冲重复频率 (PRF)。之后，重采样消除了距离频率和慢时间之间的耦合。最后，使用基于逆离散傅里叶变换（IDFT）的相干积分步骤来实现参数估计并抑制插值引起的栅瓣。所提出的方法可以通过快速傅里叶变换（FFT）有效地实现，没有参数搜索程序的逆 FFT (IFFT) 和非均匀 FFT (NUFFT)。数值实验表明，该方法具有近乎最优的抗噪性能，但计算复杂度远低于最大似然估计器，这使其在实际应用中更具竞争力。