Frequency estimation of low rate non-uniformly sampled signals using neural networks

H. Alavi, M. Fadaei
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引用次数: 4

Abstract

This paper reports on the employment of low rate non-uniform sampling to increase the unambiguous bandwidth in the frequency estimation of narrowband signals. First, we explore the effect of non-uniform sampling on the spectra of the sampled signals. We then show how non-uniform sampling affects the spectral estimation, when conventional methods are used. Finally, we present an effective neural network scheme and report on some simulation results. The results show that the instantaneous frequency content of the narrow-band signals may be estimated effectively, using low rate non-uniform sampling and the proposed neural network frequency estimation method. One important application of the proposed method is in unambiguous Doppler estimation of target echoes in long range radar with staggered pulse repetition frequency.<>
基于神经网络的低速率非均匀采样信号频率估计
本文报道了在窄带信号的频率估计中,利用低速率非均匀采样来增加无二义带宽的方法。首先,我们探讨了非均匀采样对采样信号频谱的影响。然后,我们展示了当使用常规方法时,非均匀采样如何影响光谱估计。最后,我们提出了一种有效的神经网络方案,并给出了一些仿真结果。结果表明,采用低速率非均匀采样和神经网络频率估计方法可以有效地估计出窄带信号的瞬时频率含量。该方法的一个重要应用是在具有交错脉冲重复频率的远程雷达目标回波的无二义多普勒估计中。
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