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首页> 外文期刊>Circuits, systems, and signal processing >Exponential-Reproducing-Kernel-Based Sparse Sampling Method for Finite Rate of Innovation Signal with Arbitrary Pulse Echo Position
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Exponential-Reproducing-Kernel-Based Sparse Sampling Method for Finite Rate of Innovation Signal with Arbitrary Pulse Echo Position

机译：任意脉冲回波位置创新信号有限速率的基于核指数核的稀疏采样方法

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摘要

An exponential reproducing kernel (ERK) has been applied to data sparse sampling for finite rate of innovation (FRI) signals with the characteristic of flexible parameter setting in contrast to other sampling kernels. However, the signal reconstruction process may fail if a pulse echo is present in certain positions. To solve this problem, a novel ERK sparse sampling method was developed for arbitrary pulse echo positions. A constraint relationship between the pulse echo position and reproduced-exponent area was deduced, revealing the cause of invalid signal reconstruction from sparse sampling data. A new sampling time interval calculation algorithm is presented in this paper. Through the proposed method, FRI signals can be reconstructed accurately with a pulse echo present at arbitrary positions without increasing the quantity of sparse sampling data. The signal reconstruction effectiveness and accuracy were verified through simulation experiments. The proposed technique can be used to improve the flexibility of the ERK sparse sampling method in actual applications.
机译：指数重现内核（ERK）已应用于有限创新速率（FRI）信号的数据稀疏采样，与其他采样内核相比，它具有灵活的参数设置特性。但是，如果在某些位置存在脉冲回波，则信号重建过程可能会失败。为了解决这个问题，针对任意脉冲回波位置开发了一种新颖的ERK稀疏采样方法。推导了脉冲回波位置与再现指数区域之间的约束关系，揭示了稀疏采样数据重构无效信号的原因。提出了一种新的采样时间间隔计算算法。通过提出的方法，在不增加稀疏采样数据量的情况下，可以在任意位置存在脉冲回波的情况下准确重建FRI信号。通过仿真实验验证了信号重建的有效性和准确性。所提出的技术可用于提高实际应用中ERK稀疏采样方法的灵活性。

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