CN107124183B - Double-channel TIADC system mismatch error blind correction method - Google Patents

Abstract

The invention discloses a double-channel TIADC system mismatch error blind correction method which comprises the steps of obtaining sampling data of each channel, calibrating data of a channel 1, calculating a cross-correlation function of the sampling data of the channel 0 and first calibration data of the channel 1, calculating a cross-correlation function of the sampling data of the channel 0 and output data of each fractional delay filter, establishing a functional relation, estimating mismatch time and filtering mismatch time. The method estimates the three mismatch errors of the system in a mode without using a closed loop, realizes the calibration of error parameters without additional hardware, and does not need additional calibration signals.

Description

Double-channel TIADC system mismatch error blind correction method

Technical Field

The invention relates to a blind correction method for mismatch errors of a TIADC system, in particular to a blind correction method for mismatch errors of a dual-channel TIADC system, and belongs to the technical field of communication.

Background

TIADC (parallel sampling system) may generate offset error, gain error, time phase error due to non-ideal characteristics of the device. The correction techniques for the three main errors in TIADC (parallel sampling system) focus on two large directions, namely the non-blind estimation and correction algorithm and the blind estimation and correction algorithm for mismatch errors. The non-blind estimation and correction algorithm of mismatch errors needs to inject excitation signals into the acquisition system periodically to obtain error parameters of the system, and the non-blind estimation and correction algorithm influences the real-time performance of the operation of the acquisition system. The blind estimation and correction algorithm does not need to inject excitation signals into the acquisition system regularly, and the estimation and correction of system error parameters are completed while the acquisition system measures the measured signals.

As shown in FIG. 1, parameter g in a two-channel TIADC₀,o₀,Δt₀Gain error, bias error, and time phase error, respectively, of channel 0, parameter g₁,o₁,Δt₁Respectively, gain error, bias error, and time phase error for channel 1. In practice, with channel 0 as the reference channel, the gain error, offset error, and time phase error g for channel 1 are required₁,o₁,Δt₁Estimated and corrected to finally be equal to the corresponding parameter of channel 0, i.e. g₁＝g₀,o₁＝o₀And Δ t₁＝Δt₀Thereby completing the mismatch error correction for the entire system.

The existing two-channel TIADC blind estimation and correction method adopts a closed loop mode to estimate parameters in the estimation process of three main errors. Some mismatch error estimation and correction methods require additional hardware to correct the mismatch error parameters.

Disclosure of Invention

The invention aims to provide a double-channel TIADC system mismatch error blind correction method.

In order to solve the technical problems, the invention adopts the technical scheme that:

a double-channel TIADC system mismatch error blind correction method comprises the following steps:

step 1: acquiring sampling data of each channel: acquiring sampling data X of channel 0 and channel 1 respectively₀(k) And X₁(k) And calculating the mean and mean square values E [ X ] of the sampled data of channel 0 and channel 1₀(k)]、E[X₁(k)]、

Sampling data X for channel 0 and channel 1₀(k) And X₁(k) Expressed as:

wherein, Δ t₁For mismatch time, | Δ t of the system₁|≤0.1；g₁Is the gain error of channel 1, o₁Is the offset error of channel 1; the calculation method comprises the following steps:

step 2: data for calibration channel 1: using the gain error g of channel 1₁And biasError o₁Calibrating the sampled data of channel 1 to obtain the first calibration data of channel 1

And step 3: compute channel 0 sample data X₀(k) And first calibration data for channel 1

Cross correlation function of

And 4, step 4: calculate the cross-correlation function of the sampled data for channel 0 and the output data of each fractional delay filter: sampling data X of channel 0₀(k) Sending the data into a fractional delay filter bank with n fractional delay filters, and calculating the cross-correlation function R of the output data of each fractional delay filter of the channel 0 and the sampling data of the channel 0_x0(Δx_i),i∈[1,n](ii) a Delay Deltax of ith fractional delay filter_iComprises the following steps:

and 5: establishing a functional relation: cross correlation function R of channel 0 sampled data and channel 0 fractional delay filter output data_x0(Δx_i) As an argument x, delay Δ x of each fractional delay filter_iEstablishing a functional relation for the dependent variable y;

step 6: estimating the mismatch time: estimating the mismatch time at of the system using the functional relationship established in step 5₁；

And 7:filter mismatch time: performing Δ t on the time phase error estimated in step 6 using a fractional delay filter₁And (3) delay filtering processing, wherein the formula is as follows:

wherein:

equation (6)' represents a convolution operation,. DELTA.t₁Calculated in step (6).

In step 5, a polynomial regression method is used for establishing the functional relation:

y＝a₀+a₁x+a₂x². (8)

wherein the coefficient a₀,a₁,a₂The calculation method comprises the following steps:

wherein x_i＝R_x0(Δx_i)，y_i＝Δx_iAnd n is the number of fractional delay filters.

The technical effect obtained by adopting the technical scheme is as follows: the method estimates the three mismatch errors of the system in a mode without using a closed loop, realizes the calibration of error parameters without additional hardware, and does not need additional calibration signals.

Drawings

The present invention will be described in further detail with reference to the accompanying drawings and specific embodiments.

FIG. 1 is a functional block diagram of a dual channel TIADC;

FIG. 2 is a flow chart of the present invention;

fig. 3 is a schematic block diagram of a fractional delay filter bank of embodiment 1.

Detailed Description

Example 1:

a double-channel TIADC system mismatch error blind correction method comprises the following steps:

step 1: acquiring sampling data X of channel 0 and channel 1 respectively₀(k) And X₁(k) And calculating the mean and mean square values E [ X ] of the sampled data of channel 0 and channel 1₀(k)]、E[X₁(k)]、

Sampling data X for channel 0 and channel 1₀(k) And X₁(k) Expressed as:

wherein, Δ t₁For mismatch time, | Δ t of the system₁|≤0.1；g₁Is the gain error of channel 1, o₁Is the offset error of channel 1; step 2: estimating the gain error g of channel 1₁And offset error o₁The calculation method comprises the following steps:

step 2: using the gain error g of channel 1₁And offset error o₁Calibrating the sampled data of channel 1 to obtain the first calibration data of channel 1

And step 3: compute channel 0 sample data X₀(k) And first calibration data for channel 1

Cross correlation function of

And 4, step 4: sampling data X of channel 0₀(k) Into a fractional delay filter bank having n fractional delay filters. In the actual use process, the absolute value of the deviation of the time phase error of the TIADC system with good hardware design does not exceed 0.1, and according to the formula 4 in the step 3, the sampling data and the first calibration data of the channel 0 are easily known under the condition that the system has no time mismatch error

The cross-correlation between the calculated values is

This means that the value range of equation (4) is

Sampling data X of channel 0₀(k) Feeding the signal into a fractional delay filter bank with n fractional delay filters, wherein the delay of the ith fractional delay filter is as follows:

calculating a cross-correlation function R of the fractional delay filter output data of channel 0 and the sampled data of channel 0_x0(Δx_i),i∈[1,n]；

And 5: cross correlation function R of channel 0 sampled data and channel 0 fractional delay filter output data_x0(Δx_i) As an argument x, delay Δ x of each fractional delay filter_iEstablishing a functional relation for the dependent variable y;

in step 5, a polynomial regression method is used for establishing the functional relation:

y＝a₀+a₁x+a₂x². (6)

wherein the coefficient a₀,a₁,a₂The calculation method comprises the following steps:

wherein x_i＝R_x0(Δx_i)，y_i＝Δx_iAnd n is the number of fractional delay filters.

Determining the coefficient a via equation (7)₀,a₁,a₂The time phase error of the post TIADC system can be calculated by:

step 6: estimating the mismatch time at of the system using the functional relationship established in step 5₁。

And 7: filtering the time phase error estimated in step 6 by deltat using a fractional delay filter₁And (6) processing.

Claims (2)

1. A double-channel TIADC system mismatch error blind correction method is characterized in that: a channel 0 in the dual-channel TIADC system is used as a reference channel, and a channel 1 is used as a measurement channel; the measured signal X (t) input in the dual-channel TIADC system is a wide stationary random process; the method comprises the following steps:

step 1: acquiring sampling data of each channel: acquiring sampling data X of channel 0 and channel 1 respectively₀(k) And X₁(k) And calculating the mean and mean square values E [ X ] of the sampled data of channel 0 and channel 1₀(k)]、E[X₁(k)]、

Sampling data X for channel 0 and channel 1₀(k) And X₁(k) Expressed as:

wherein, Δ t₁For mismatch time, | Δ t of the system₁|≤0.1；g₁Is the gain error of channel 1, o₁Is the offset error of channel 1; the calculation method comprises the following steps:

step 2: data for calibration channel 1: using the gain error g of channel 1₁And offset error o₁Calibrating the sampled data of channel 1 to obtain the first calibration data of channel 1

And step 3: compute channel 0 sample data X₀(k) And first calibration data for channel 1

Cross correlation function of

And 4, step 4: calculate the cross-correlation function of the sampled data for channel 0 and the output data of each fractional delay filter: sampling data X of channel 0₀(k) Sending the data into a fractional delay filter bank with n fractional delay filters, and calculating the cross-correlation function R of the output data of each fractional delay filter of the channel 0 and the sampling data of the channel 0_x0(Δx_i),i∈[1,n](ii) a Delay Deltax of ith fractional delay filter_iComprises the following steps:

and 5: establishing a functional relation: cross correlation function R of channel 0 sampled data and channel 0 fractional delay filter output data_x0(Δx_i) As an argument x, delay Δ x of each fractional delay filter_iEstablishing a functional relation for the dependent variable y;

step 6: estimating the mismatch time: estimating the mismatch time at of the system using the functional relationship established in step 5₁；

And 7: filter mismatch time: performing Δ t on the time phase error estimated in step 6 using a fractional delay filter₁And (5) delay filtering processing.

2. The two-channel TIADC system mismatch error blind correction method of claim 1, wherein: in step 5, a polynomial regression method is used for establishing the functional relation:

y＝a₀+a₁x+a₂x². (6)

wherein the coefficient a₀,a₁,a₂The calculation method comprises the following steps:

wherein x_i＝R_x0(Δx_i)，y_i＝Δx_iAnd n is the number of fractional delay filters.

Images