摘要
时间交替模数转换器(TIADC)中存在的偏置、增益和时间误差严重影响了系统的信噪比(SNR)和有效位数(ENOB)。该文提出了数理统计和频谱分析的误差校正方法。数理统计用于偏置误差的校正,通过对各个子ADC的采样数据进行数理统计,得到各个子ADC偏置误差的估计,进而完成误差校正,并使用一种二次校正的方法,提高了校正精度;频谱分析用于增益误差和时间误差的校正,由存在误差时特定频点的幅度和相位值得到误差估计,从而实现增益误差和时间误差的校正。校正前后信号频谱的对比证明了该校正算法的有效性。实验结果表明,该算法简单容易实现,将TIADC系统的SNR提高到了41.019 4 dB,ENOB提高到了6.52 bit,校正效果达到或者优于正弦拟合算法。
Offset error, gain error and time error greatly degrade the signal-to-noise ratio （SNR） and effective number of bits （ENOB） in time-interleaved analog to digital converter （ADC） systems. This paper discusses mathematical statistics and spectrum analysis calibration method for time-interleaved ADC systems. Mathematical statistics is used for offset error, through mathematical statistics of the sampled data of each sub ADC, the estimation of the offset error can be obtained, and the calibration can be carried out. Meanwhile, a second time calibration is applied to improve the calibration accuracy, the spectrum analysis is used for gain error and time error. The gain error and time error can be estimated by the magnitude and phase of the specific frequency point, so the calibration can be achieved. The comparison of the signal spectrums before and after calibration proves the effectiveness of the calibration algorithm. The algorithm is simple and easy to implement. The experiment result shows that the SNR can reach to 41.019 4 dB, and ENOB to 6.52 bit. Moreover, the results is equal or better than the sine fitting algorithm.
出处
《电子科技大学学报》
EI
CAS
CSCD
北大核心
2018年第1期43-50,共8页
Journal of University of Electronic Science and Technology of China
基金
国家自然科学基金(61301263
61501087)
中央高校基本科研基金(ZYGX2015KYQD074)
关键词
数据采集
误差校正
数理统计
频谱分析
时间交替模数转换器
data acquisition
error calibration
mathematical statistics
spectrum analysis
time-interleaved analog to digital converter （TIADC）
