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Subspace-based estimation of time delays and Doppler shifts

机译:基于子空间的时延和多普勒频移估计

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This paper considers the problem of estimating the time delays and Doppler shifts of a known waveform received via several distinct paths by an array of antennas. The general maximum likelihood estimator is presented, and is shown to require a 2d-dimensional nonlinear minimization, where d is the number of received signal reflections. Two alternative solutions based on signal and noise subspace fitting are proposed, requiring only a d-dimensional minimization. In particular, we show how to decouple the required search into a two-step procedure, where the delays are estimated and the Dopplers solved for explicitly. Initial conditions for the time delay search can be obtained by applying generalizations of the MUSIC and ESPRIT algorithms, which are also outlined in the paper. Simulation examples are included to illustrate the algorithms' performance relative to the Cramer-Rao bound.
机译:本文考虑了估计天线阵列通过几个不同路径接收到的已知波形的时间延迟和多普勒频移的问题。给出了一般的最大似然估计器,并表明它需要二维非线性最小化,其中d是接收信号反射的次数。提出了两种基于信号和噪声子空间拟合的替代解决方案,仅要求d维最小化。特别是,我们展示了如何将所需的搜索解耦到两步过程中,在该过程中估计延迟并明确解决多普勒问题。可以通过应用MUSIC和ESPRIT算法的概括来获得延时搜索的初始条件,本文也对此进行了概述。包括仿真示例,以说明算法相对于Cramer-Rao界线的性能。

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