一种结合高精度TDC的快速全数字锁相环

发布时间：2018-05-01 21:27

本文选题：全数字锁相环 + 时间数字转换器　；参考：《湖南大学学报(自然科学版)》2017年08期

【摘要】：针对传统全数字锁相环锁相周期长、时间数字转换电路量化误差较大等问题,提出了一种在高分辨率时间数字转换器的基础上能够快速锁相的全数字锁相环.本设计提出的相调模块将量化的相位差还原成时间序列,并在状态机的控制下加入到重构信号中,从而能够在检测到相位差之后的最多两个输入参考时钟周期内使相位一次性对齐,锁相时间控制在0.72μs之内;设计的上升沿检测电路能够在重构与参考信号同频时,准确地检测两者上升沿是否同时到来并给出相应的使能信号,从而在锁相时关闭时间数字转换电路,大大降低了电路的功耗;优化了多时钟多相位的时间数字转换器粗量化的计算方法,提高了粗量化速度,增大了计数器位宽,扩大了测量范围,并且量化误差控制在0.25ns之内.最后完成了整体设计的RTL级建模及仿真,结果证明,该全数字锁相环具有锁相速度快、量化精度高、稳定性好、功耗低、输出频率便于调整等特点.
[Abstract]:In order to solve the problems such as long period of phase lock and large quantization error of time-digital conversion circuit, an all-digital phase-locked loop based on high-resolution time-digital converter is proposed. The phase modulation module proposed in this paper restores the quantized phase difference into a time series and adds it to the reconstructed signal under the control of the state machine. Thus, the phase can be aligned at one time and the phase locked time is controlled within 0.72 渭 s during the maximum two input reference clock cycles after the phase difference is detected, and the designed rising edge detection circuit can reconstruct the same frequency as the reference signal. Accurate detection of the rising edge of both comes at the same time and the corresponding enabling signal is given so that the power consumption of the circuit is greatly reduced by closing the time digital conversion circuit when the phase is locked; The calculation method of coarse quantization of time-digital converter with multi-clock and multi-phase is optimized, the speed of coarse quantization is improved, the bit width of counter is enlarged, the measurement range is enlarged, and the quantization error is controlled within 0.25ns. Finally, the RTL modeling and simulation of the whole design is completed. The results show that the all-digital PLL has the characteristics of fast phase-locked speed, high quantization accuracy, good stability, low power consumption and easy adjustment of output frequency.
【作者单位】：中国地质大学(武汉)机械与电子信息学院;
【基金】：国家自然科学基金资助项目(41304078)~~
【分类号】：TN911.8

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