TIADC mismatch error calibrating method based on adaptive filtering and Taylor series

Abstract

The invention discloses a TIADC mismatch error calibrating method based on adaptive filtering and a Taylor series. The TIADC mismatch error calibrating method comprises the steps of collecting signals of channels, estimating a biased error of a sampled signal of the channel 1, calibrating the biased error of the channel 1, performing fractional delay filtering, estimating a gain error and a time phase error of the channel 1 by employing an adaptive filter, and calibrating the gain error and the time phase error of the channel 1. The TIADC mismatch error calibrating method has the characteristics of few points that needs to be sampled, less calculated amount and the like, and is applied to a portable collection device such as a portable oscillometer, etc.

Description

technical field [0001] The invention relates to a TIADC mismatch error calibration method, in particular to a TIADC mismatch error calibration method based on adaptive filtering and Taylor series, and belongs to the field of instruments and meters. Background technique [0002] Parallel sampling system (TIADC) will produce offset error, gain error, and time phase error due to the non-ideal characteristics of the device. The dual-channel TIADC model is as follows figure 1 As shown, the sampling rate is f s , the sampling period is T s . parameter g 0 ,o 0 ,Δt 0 are the gain error, offset error and time phase error of channel 0 respectively, the parameter g 1 ,o 1 ,Δt 1 are the gain error, offset error, and time phase error of channel 1, respectively. In actual work, channel 0 is used as the reference channel, and the gain error, offset error and time phase error g of channel 1 need to be calculated 1 ,o 1 ,Δt 1 Estimate and correct, and finally make g 1 =g 0 ,o...

AI Technical Summary

Problems solved by technology

Although blind estimation and correction algorithms do not need to regularly inject excitation signals into the acquisition system, the existing blind estimation and correction algorithms require a very large number of sampling points

The number of sampling points required for an estimation and correction process is mostly more than 10,000 and the amount of calculation is complex, which imposes high requirements on the calculation and storage of the acquisition system, and is not suitable for use in portable instruments such as handheld oscilloscopes

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