A new method for parameter estimation of high-order polynomial-phase signals
A new method for parameter estimation of high-order polynomial-phase signals
复制标题
高阶多项式相位信号参数估计的新方法
DOI：
10.1016/j.sigpro.2017.06.011
复制
发表时间：
2018-01-01
影响因子：
4.4
通讯作者：
Lu, Yunlong
中科院分区：
文献类型：
--
作者：
Cao, Runqing;Li, Ming;Lu, Yunlong
研究了高阶多项式相位信号的参数估计问题。我们提出了一种方法来估计相位参数更有效和准确。在所提出的方法中，我们定义了一个称为非均匀采样降阶算子（NOMO）的操作，以减少一半的多项式相位的顺序时，PPS的顺序是偶数。通过结合使用NURO和相位微分（PD）运算符，PPS阶数被减少到一个，即，PPS退化为复正弦曲线。然后，通过联合使用快速傅立叶变换（FFT）和一维搜索，可以完成参数估计。与传统方法相比，该方法的降阶过程具有较低阶的非线性。仿真结果表明，当PPS阶数大于5时，该方法在均方误差（MSE）和阈值方面均优于混合CPF-HAF和HAF。(C)2017爱思唯尔B. V.保留所有权利。
Parameter estimation of a high-order polynomial phase signal (PPS) is considered in this paper. We propose a method to estimate phase parameters more efficiently and accurately. In the proposed method, we define an operator referred to as non-uniform sampled reducing-order operator (NURO) to reduce the order of a polynomial phase by half, when the order of PPS is even. By combined using NURO and phase differentiation (PD) operators, the PPS order is reduced to one, i.e., the PPS degenerates into a complex sinusoid. Then, the parameter estimation can be done by jointly using fast Fourier transform (FFT) and one-dimensional search. Compared with the traditional methods, the reducing-order procedure in the proposed method has lower-order nonlinearities. Simulation results show that the proposed method outperforms the hybrid CPF-HAF and HAF in both mean square error (MSE) and the threshold when the PPS order is higher than 5. (C) 2017 Elsevier B.V. All rights reserved.