Robust TDOA/FDOA estimation from emitter signals for hybrid localization using UAVs

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 (FFF),inverse FFT (IFFF) 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.     

基于脉冲串信号的无源定位系统频差估计误差CRLB分析

频差估计是无源定位系统中的关键部分,其估计精度直接决定了无源定位系统的性能。本文对单频脉冲信号频差估计误差方差的Cramer-Rao下限(CRLB)进行了理论分析研究。在建立数学模型的基础上,定量分析了频差估计误差CRLB与接收信号参数的数学关系。通过直接公式推导和数值仿真归纳,分别得出了相参/非相参单频脉冲信号频差估计误差CRLB的解析表达式,该结论可用于指导基于频差估计的无源定位系统设计。