摘要：对于传统的ADC测试方法,若要得到动、静态性能指标,需通过两次测试测得,所需时间较长.文章首先采用移动平均滤波器对静态测试时的直方图算法进行时间优化,然后对静态测试采集的测试点进行抽取,并消除增益误差后,基于参数提取算法通过傅里叶变化得到所有的ADC动态参数.实验结果表明,文章所提算法所得的最大INL估算误差为0.186 LSB,SINAD、ENOB、THD、SFDR估算误差分别为0.211 dB、0.035、0.159 dB、0.119 dB.与原估算算法相比,优化算法所得SINAD和ENOB的估算精度提高了0.411 dB和0.057.与传统ADC测试方法相比,在保证测试精度的前提下,测试时间减少了50.769%.%As for traditional test method of ADC,it needs twice tests to obtain the static parameters and dynamic parameters. To obtain the whole parameters, it spends a long time, and the cost is very high. Firstly, the time of histogram algorithm is optimized by moving average filter. Then the test point of static test collection is extracted. After eliminating the errors of gain,all the dynamic parameters of ADC are obtained by fourier transform based on the parameter extraction algorithm. The experimental results show that the estimate errors of maximum INL,SINAD, ENOB,THD and SFDR are 0.168 LSB,0.211 dB,0.035,0.159 dB and 0.119 dB by using the optimized algorithm. Compared with the original algorithm,the estimating accuracy of SINAD and ENOB is increased by 0.411 dB and 0.057 dB. Compared with the traditional method,the test time is reduced by 50.769% on the promise of the test precision.