The instant application claims priority to Italian Patent Application No. MI2013A001273, filed 30 Jul. 2013, which application is incorporated herein by reference in its entirety.
This disclosure relates to analog-to-digital conversion and more particularly to a method and a related device for generating with great precision a digital signal corresponding to an analog signal.
High-precision amplification chains for analog signal processing usually employ multiples acquisitions and averaging to increase resolution and reduce noise. A drawback of this approach is that linearity errors due to a nonlinearity interval of the input/output characteristic of the used analog-to-digital converter (ADC) are emphasized. The main cause of nonlinearity is the matching of analog components (for example, capacitor-bank matching in case of a switched-capacitor-based ADC). Therefore, a method to improve accuracy of analog-to-digital conversion, when the input/output characteristic of the used ADC may contain one or more nonlinearity intervals centered on an unknown point of the characteristic, is requested.
According to a technique proposed by B. Provost and E. Sanchez-Sinencio, “A practical self-calibration scheme implementation for pipeline ADC” IEEE Transactions on Instrumentation and Measurement 2004, which is incorporated by reference, a highly linear analog ramp (generated on-chip or off-chip during testing) is used, an integral nonlinearity (INL) measurement is performed and compensation coefficients are extracted. According to this technique, a calibration is substantially performed in the digital domain.
Other techniques compensate for the ADC linearity errors by using an additional programmable digital-to-analog converter (DAC), such as for example the one proposed by X.-L. Huang et al, “A self-testing and calibration method for embedded successive approximation register ADC”—16th Asia and South Pacific Design Automation Conference (ASP-DAC) 2011, which is incorporated by reference. The basic idea is to estimate the ADC linearity by measuring the major carrier transitions (MOTs) of the array of capacitors of the DAC. During calibration procedures, the array of capacitors of the DAC is controlled to generate the MOTs, which are then compensated by using an additional differential DAC. During the functioning, a compensation code is subtracted from the ADC output to obtain more accurate digital replicas of input signals to be converted.
a shows an exemplary output error characteristic of the conversion device of
The highlighted step variation and DNL peak in the input/output error characteristic of the ADC produces discontinuities in the input/output characteristic of the analog-to-digital conversion. These discontinuities produce accuracy errors which are often unacceptable in high-precision amplification chains for analog signal processing.
An embodiment of an innovative method of converting an analog signal to digital allows enhancing significantly the error characteristic of the conversion even when using an analog-to-digital converter with an input/output characteristic that may contain a nonlinearity interval.
An embodiment of this method, implemented in a related device, includes the steps of:
adding, to the analog input signal, a periodic signal having a main frequency smaller than half of a sampling frequency of the analog-to-digital converter and an amplitude greater than an estimated amplitude of the nonlinearity interval generating thereby a sum signal;
converting into digital form the sum signal with the analog-to-digital converter, generating thereby a corresponding digital sum signal;
filtering the digital sum signal with a digital filter, the frequency response of which has zeroes in correspondence of all pulses of the frequency spectrum of the digital sum signal due to the periodic signal, generating the digital output signal as a filtered replica of the digital sum signal.
The periodic signal may be for example a triangular signal, or a square-wave signal, or a sinusoidal signal.
a shows the effects of the presence of a nonlinearity interval with missing codes in the error characteristic of the conversion device of
b shows the effects of the presence of a nonlinearity interval with a DNL positive peak in the error characteristic of the conversion device of
a and 5b illustrate a simulated functioning of the conversion device of
The herein proposed technique can improve the ADC linearity error by adding a periodic signal with a null DC value before the conversion in the digital domain. This periodic signal is added to the ADC input and is then filtered, for example through an averaging process, in the digital domain. The approach does not require any modification to the original analog/digital section and does not require any additional calibration procedure.
A block diagram of a conversion device according to an embodiment is depicted in
The periodic signal needs not to be mandatorily an analog signal. For example, if the amplifier AMP is a discrete time amplifier, the periodic signal may be a discrete time signal and the ADC may be a digital-to-analog converter (DAC). That is, an embodiment of the technique described herein can reduce errors caused by the nonlinearity of a DAC.
It will be shown hereinafter that this technique allows reducing the number of acquisitions carried out in correspondence of input levels corresponding to any eventual nonlinearity interval of the input/output characteristic of the ADC at which the output signal is affected by a relatively great DNL error.
The periodic signal may be any continuous or discrete time periodic signal whose main frequency fs/N (wherein fs is the ADC sampling frequency and N is an integer number) and all harmonic frequency tones coincide with zeroes of the frequency response of the digital filter (contained in the DSP) that generates the output digital signal by filtering the digital signal generated by the analog-to-digital converter. If, for example, the digital filter is a FIR (Finite Impulse Response) and the number of samples from the ADC used for the filtering is equal to M, the output signal is given by
y[n]=Σk=0M−1bk·x[n−k] (1)
and the frequency response of the digital filter is given by
H(ω)=H(z)|z=e
Any periodic signal, whose frequency spectrum only includes tones centered on the zeroes of equation (2), is filtered out by the FIR.
If the DC value of the periodic signal is not zero, then the output signal will be affected by an offset component that may be easily removed.
Considering, as an example, that the digital filter is a moving average filter, the frequency response of the digital filter is
and the frequency response for three values of M is depicted in
For a moving average filter the frequency response presents the following zeros
for k/M less than or equal to ½.
Let's suppose that the DSP unit integrates a moving average filter which generates each value of the output signal by averaging 512 points of the ADC output, that means M=512, and that the periodic signal is a periodic triangular waveform with a frequency equal to fs/8, that means N=8. In this considered exemplary case, the periodic signal modulates the ADC output as shown in
Within the Nyquist frequency fs/2, the considered triangular waveform frequency spectrum has two tones at fs/8 and at 3*fs/8, which coincide with zeroes of the frequency response of the moving average filter (for M=512). As a consequence, the triangular waveform does not affect the digital output signal because it is cancelled by the filter.
Supposing that the input value corresponding to 10380 LSB is a high DNL error value, thanks to the modulation imposed by the triangular waveform only one sample out of four will be evaluated at around 10380 LSB. In other words, when the ADC input corresponds to a high DNL error level, then a reduced number of conversions will be done at this input level and consequently the weight of the linearity error is decreased. In the proposed example the DNL error is reduced by four times, that is N/2 times.
Comparable results are obtained using a sinusoidal periodic signal, as shown in
An embodiment of the proposed technique provides a DNL error attenuation equal to N/2, thus the integer number N (i.e., the ratio between the sampling frequency fs and the frequency of the periodic signal) is chosen to be as great as possible. The maximum value of N is N=M, in which M is the number of points used for the digital filter averaging.
However, the maximum value of N should be determined to take into account also the following issues:
the amplitude of the periodic signal limits the maximum amplitude of the analog input signal that may be converted, because the ADC has a saturated conversion characteristic;
in order to distribute the ADC samples on different levels, the distance between two consecutive samples of the periodic signal, which is tied to the amplitude of the periodic signal and to the number N and which is about 50 LSB in the example of
if the peak-to-peak amplitude of the periodic signal, which is about 200 LSB in the example of
With the above indications, one may choose the sampling frequency fs, the amplitude of the periodic signal, and the ADC to be used depending upon the maximum amplitude of an input signal to be converted, and then he may select an allowable number N in order to meet all the above objectives.
Furthermore, the circuit of
From the foregoing it will be appreciated that, although specific embodiments have been described herein for purposes of illustration, various modifications may be made without deviating from the spirit and scope of the disclosure. Furthermore, where an alternative is disclosed for a particular embodiment, this alternative may also apply to other embodiments even if not specifically stated.
Number | Date | Country | Kind |
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M12013A1273 | Jul 2013 | IT | national |
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Entry |
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Search Report for Italian patent application No. MI20131273, Hague, Holland, Oct. 9, 2013, 2 pages. |
“A self-testing and calibration method for embedded successive approximation register ADC”—16th Asia and South Pacific Design Automation Conference (ASP-DAC) 2011. |
“A practical self-calibration scheme implementation for pipeline ADC” IEEE Transactions on Instrumentation and Measurement 2004. |
Number | Date | Country | |
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20150035691 A1 | Feb 2015 | US |