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基于记忆多项式的时间交织模数转换器自适应非线性失配校正方法

刘素娟 张仲侯

刘素娟, 张仲侯. 基于记忆多项式的时间交织模数转换器自适应非线性失配校正方法[J]. 电子与信息学报, 2021, 43(12): 3718-3726. doi: 10.11999/JEIT200885
引用本文: 刘素娟, 张仲侯. 基于记忆多项式的时间交织模数转换器自适应非线性失配校正方法[J]. 电子与信息学报, 2021, 43(12): 3718-3726. doi: 10.11999/JEIT200885
Sujuan LIU, Zhonghou ZHANG. Adaptive Nonlinear Mismatch Calibration Technique for TIADC Based on Memory Polynomial Model[J]. Journal of Electronics & Information Technology, 2021, 43(12): 3718-3726. doi: 10.11999/JEIT200885
Citation: Sujuan LIU, Zhonghou ZHANG. Adaptive Nonlinear Mismatch Calibration Technique for TIADC Based on Memory Polynomial Model[J]. Journal of Electronics & Information Technology, 2021, 43(12): 3718-3726. doi: 10.11999/JEIT200885

基于记忆多项式的时间交织模数转换器自适应非线性失配校正方法

doi: 10.11999/JEIT200885
基金项目: 国家自然科学基金(62074010),北京市教委科技项目(KM201810005022)
详细信息
    作者简介:

    刘素娟:女,1978年生,副教授,研究方向为模数混合集成电路设计

    张仲侯:男,1995年生,硕士生,研究方向为模数混合集成电路设计

    通讯作者:

    刘素娟 liusujuan@bjut.edu.cn

  • 中图分类号: TN911.72

Adaptive Nonlinear Mismatch Calibration Technique for TIADC Based on Memory Polynomial Model

Funds: The National Natural Science Foundation of China (62074010), The Scientific Research Project of Beijing Educational Committee (KM201810005022)
  • 摘要: 为了提高时间交织模数转换器(TIADC)的有效分辨率,需要对其通道之间的线性/非线性失配误差进行估计和补偿。该文针对M通道TIADC的带有记忆效应的非线性失配误差提出了一种自适应盲校正算法。通过子通道重构结构(SCR)重构非线性误差信号,并通过滤波降采样最小均方(FDLMS)算法估计非线性失配误差系数。实验仿真结果表明,该方法可以有效校正带有记忆效应的非线性失配误差,并且可以大大降低实现难度和硬件资源消耗。
  • 图  1  TIADC结构示意图

    图  2  带有记忆效应的非线性失配误差的子ADC的离散模型

    图  3  带有记忆效应的非线性失配误差的TIADC的离散模型

    图  4  M通道TIADC带有记忆效应的非线性误差校正原理结构图

    图  5  含有2阶非线性误差的四通道TIADC输入无关频带示意图[7]

    图  6  基于FDLMS算法的M通道自适应盲校正算法结构示意图

    图  7  多频点输入信号校正效果示意图

    图  8  多频点输入信号情况下误差收敛曲线

    图  9  低通白噪声输入信号校正效果示意图

    图  10  低通白噪声输入信号情况下误差收敛曲线

    图  11  计算复杂度对比

    表  1  计算复杂度的对比

    本文文献[16]文献[17]
    误差类型带有记忆效应静态静态
    通道数MM=1, 2, ···M=1, 2, ···M=1, 2, 4, 8, ···
    乘法器/每次采样2(P–1)Q+Nf/2+1(2M+1)(P–1)+Nf/2+1(M+1)(P–1)+Nf/2+1
    调制器/每次采样0(2M+1)(P–1)(M+1)(P–1)
    M:TIADC通道数;P:非线性误差最高阶;Q:记忆长度;Nf:高通FIR滤波器阶数
    下载: 导出CSV
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出版历程
  • 收稿日期:  2020-10-16
  • 修回日期:  2021-06-07
  • 网络出版日期:  2021-07-15
  • 刊出日期:  2021-12-21

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