This disclosure relates to an arbitrary waveform and function generator, more specifically, an arbitrary waveform and function generator that de-embeds the effects of a coaxial cable upon the measurement and/or monitoring of the output waveform without any knowledge of the device under test.
Arbitrary Waveform and Function Generator (AFG) instruments are widely utilized for generating continuous/burst user-defined mathematical function waveform signals for electronic circuit design and testing. Typically, an AFG instrument has an output impedance of 50 ohms over its operating frequency range. The load impedance of a device under test (DUT) impacts the actual output signal of an AFG instrument.
During a typical operation, a low insertion-loss cable is generally used to connect the AFG to a DUT. For low frequencies and matching loads, the waveform monitoring function of the AFG works well with a minor cable attenuation that is easy to compensate. However, at high frequencies, i.e., when the cable length is comparable to the signal wave length and the load impedance of a DUT is mismatched with the AFG output impedance, the measurement results in the local output point of the AFG might be quite different than the actual signals loaded to the remote point of the DUT, due to the impedance transformation of the transmission line, which will be called the cable effect hereinafter.
Some embodiments of the disclosed technology include a method for determining a waveform expected to be received by a device under test, the method including outputting a waveform generated by a waveform generation section of an arbitrary waveform and function generator at an output of the arbitrary waveform and function generator; sending the waveform generated by the waveform generation section to the device under test through a cable; monitoring a waveform at the output by a waveform monitoring section of the arbitrary waveform and function generator; and determining by the waveform monitoring section a transformed waveform expected to be received at the device under test based on the generated waveform being modified by the cable.
Some embodiments of the disclosed technology include an arbitrary waveform and function generator, including a waveform generation section configured to generate a waveform at an output; and a waveform monitoring section configured to monitor the waveform at the output. The waveform monitoring section includes a waveform de-embedding processor configured to determine a transformed waveform expected to be received at the device under test based on the generated waveform being modified by the cable, and a display configured to display the transformed waveform.
In the drawings, which are not necessarily to scale, like or corresponding elements of the disclosed systems and methods are denoted by the same reference numerals.
In the signal generation section 101, a waveform signal, such as a sine function waveform signal or a user-defined arbitrary waveform signal, is digitized at a specific time/phase interval and a specific vertical resolution, and is saved to the Digitized Waveform Memory 108. The Time/Phase to Address Mapper 106 functions at a specific clock, received from the System Clock 116, to access the Digitized Waveform Memory 108 to output a digitized waveform at the correct time/phase intervals for achieving the user-specified signal waveform frequency.
The digitized waveform is then output from the Digitized Waveform Memory 108 to a Digital-to-Analog Converter (DAC) 110 to convert the digitized waveform to an analog signal. The analog signal is sent through a waveform reconstruction filter 112 and output to an amplifier 114 to scale the analog signal to a user-required amplitude. This analog signal is sent through the output 104 to a remote DUT location through a coaxial cable.
As mentioned above, the waveform monitoring section 102 monitors the signal generated by the signal generation section 101 at a local test point on the output 104 on the AFG.
The high impedance amplifier 118 may vary its gain/attenuation to produce an appropriate output signal amplitude. Then, an anti-aliasing filter 120 removes the high frequency noise beyond the bandwidth of the Analog-to-Digital Converter (ADC) 122. The ADC 122 converts the analog signal received to a digitized waveform. The digitized waveform is acquired by a Waveform Acquisition Controller 124 and stored in the Waveform Acquisition Memory 126. Synchronization block 130 generates a trigger signal 132 to ensure that the acquisition is accomplished in a complete signal period. The acquired digitized waveform stored in the Waveform Acquisition Memory 126 is sent to the Waveform Display Controller 128 for waveform display and/or monitoring on the AFG.
For example, using the configuration of the AFG shown in
According to embodiments of the present invention, as seen in
Using the AFG 200 depicted in
Initially, when an AFG is setup with a specific cable and DUT, the measurements to de-embed the cable effect goes through two steps. First, a calibration is run, and second, the de-embedding of the cable effect for the various signals.
Initially, when the AFG is setup with a specific cable and DUT, a calibration is run. In operation 300, the voltage at the output 104 is measured for a sine signal of the frequency of f with a coaxial cable that is terminated with a matching load, i.e., with a load equal to the characteristic impedance ZC of the coaxial cable. This measurement provides the complex measurement result of the nominal output Vmea_nom of the AFG 200 through synchronous acquisition, i.e. Vmea_nom can be expressed in a complex format as shown in equation (1):
Vmea_nom=Abs(Vmea_nom)ejAngle(V
where the synchronous trigger signal is used as a reference phase.
In operation 302, the voltage at the output 104 is measured for the sine signal of the frequency f with the coaxial cable terminated with an open load through synchronous acquisition, i.e., the signal is fully reflected by the load, which provides the measurement of Vmea_open. This measurement may be used with Vmea_nom to determine the complex ratio ko, as shown in equation (2):
where α is the unknown attenuation coefficient of the coaxial cable, β the unknown waveform number of the coaxial cable, and l the unknown length of the coaxial cable.
Then in operation 304, the whole frequency range of the AFG 200 is scanned to characterize ko of coaxial cable with an open load at a specified frequency step of Δf, which is normally frequency-dependent. That is, Vmea_nom and Vmea_open are scanned over the entire frequency range at the specified frequency step. The data collections of ko(2πf) for multiple frequency points are needed for de-embedding non-sine wave signals because they occupy a frequency range rather than a single frequency point of a sine signal. These values are then stored in a coefficient table on a memory (not shown) of the AFG 200.
In operation 306, the voltage at the output 104 is measured for the sine signal of the frequency f with the coaxial cable terminated with a user load, i.e., the DUT to determine Vmea_load. The complex ratio kl is calculated then using equation (3):
where ZDUT is the unknown input impedance of DUT.
In operation 308, the whole frequency range of the AFG 200 is scanned to characterize kl at a specified frequency step of Δf, which is normally frequency-dependent. That is, Vmea_load is scanned over the entire frequency range at the specified frequency step. The data collections of kl(2πf) for multiple frequency points are needed for de-embedding non-sine wave signals because they occupy a frequency range rather than a single frequency point of sine signal. These values are then stored in a coefficient table on a memory (not shown) of the AFG 200.
After the values for ko and kl are stored in the coefficient table of the memory on the AFG, the AFG may then begin de-embedding for actual signals generated. That is, the AFG will first determine in step 310 whether a sine signal or an arbitrary signal is generated by the signal generation section 101.
In operation 312, if a sine signal is generated, then the coefficients ko and kl may be looked up at the user-set frequency point of signal generation to calculate the signal that is actually received at the DUT at the remote end of the coaxial cable, using equation (4):
i.e., VDUT is de-embedded or retrieved from the measurement results at the output 104 of AFG 200 and kd is a de-embedding coefficient which is equal to
In operation 314, if an arbitrary (non-sine) waveform signal is generated, the Fourier Transform of Vmea_nom of the time domain format is calculated to get Vmea_nom(2πf) of the frequency domain format and the measurement results may be computed in frequency domain to get VDUT(2πf). That is, the ko and kl coefficients at all frequency points over the frequency range are used. Then, the inverse Fourier Transform of VDUT (2πf) is calculated to get the actual waveform VDUT in time domain as seen in equation (5):
i.e. VDUT is de-embedded or retrieved from the measurement result at the output 104 of AFG 200 to predict the actual waveform received at the DUT through the coaxial cable using the waveform de-embedding module 202 shown in
Alternatively, it is feasible to use a well-designed pulse signal or arbitrary waveform signal to accelerate the above measurement process of frequency scanning. The procedure is almost the same except for calculating the Fourier Transform of Vmea_nom , Vmea_open and Vmea_load , ko and kl in frequency domain instead of repeating the calculations on the basis of frequency point by point while scanning the frequency range. It is noted here that this Pulse method helps to save the measurement time but at the cost of accuracy since it is more sensitive to noises.
As in operations 302 and 306, Vmea_open is divided by Vmea_nom using divider 408, and Vmea_load is divided by Vmea_nom using divider 410, to calculate ko and kl, respectively. The Waveform De-Embedding module 202 calculates kd using the equation
However, as discussed above in operations 304 and 308, the whole frequency range is scanned to characterize ko and k1 at specified frequency steps. The frequency scanning only needs to run a single time prior to waveform de-embedding for a specific setup of cable and DUT. This retrieves the frequency-dependent calibration/de-embedding function of kd(2πf) stored as a coefficient table, discussed above, in the system for later sine and arbitrary waveform monitoring/testing.
In the second path, if the de-embed switch 410 is enabled, the acquired waveform can be sent to the de-embedding calculation path through switch 414. For a sine signal, the signal goes to the multiplier 416 through the sine-selected switch 414 for amplitude scaling and phase offset for de-embedding at one single signal frequency and then goes through switches 418 and 412 to Waveform Display Controller (not shown) for display. For an arbitrary signal, the signal goes to FFT 420 for converting to the signal in frequency domain through the arbitrary-selected switch 414. Then the signal in the frequency domain format goes to the multiplier 422 for amplitude scaling and phase offset for de-embedding over the signal frequency range. And then the de-embedded signal in frequency domain goes to inverse FFT 424 for converting to the signal in time domain. Then the de-embedded signal in time domain goes through switches 418 and 412 to the Waveform Display Controller (not shown) for display.
In the final path, if the de-embed switch 410 is not enabled, then the acquired waveform can be sent to the Waveform Display Controller (not shown) for display through switch 412.
A de-embedding emulation example of the disclosed technology is shown below using an AFG having only a signal generation section and an oscilloscope.
First, a sine wave of 10 MHz, 1 Vpp, 50 Ohm termination for the AFG was set. The AFG's trigger out signal was used for triggering the oscilloscope's acquisition. A coaxial cable connected from the AFG to a termination of 50 Ohm. A high impedance probe with an oscilloscope channel was used to measure the voltage at the AFG's output, i.e. Vmea_nom (note: a test window was cut into the cable for the probe's contacting, which applies for the below discussed probe testing).
The cable was then disconnected to leave the cable as Open to measure the voltage at AFG output to determine Vmea_open through a high impedance probe with an oscilloscope channel. The cable was then connected to a DUT to measure the voltage at AFG output to determine Vmea_load and measure the actual voltage at DUT through a high impedance probe with an oscilloscope channel. Then, the de-embedded voltage at the AFG, i.e. VDUT, was calculated using the above disclosed method of
It may be concluded that the cable effect then can be de-embedded through the above disclosed technology without any knowledge of DUT and effectively make the waveform monitoring/testing virtually move to DUT from the instrument, which was called “Virtual Monitoring.” Additionally, based on the above disclosed technology, it is feasible to enhance AFG to have the capability of compensation/pre-emphasis for improving output distortions for various DUTs. That is, an accurate depiction of the test signal received at the DUT based on the signal generated by the signal generation section 101 can be viewed by a user.
According to some examples, Waveform De-embedding Module 202 may include various hardware elements, software elements, or a combination of both. Examples of hardware elements may include devices, logic devices, components, processors, microprocessors, circuits, processor circuits, circuit elements (e.g., transistors, resistors, capacitors, inductors, and so forth), integrated circuits, application specific integrated circuits (ASIC), programmable logic devices (PLD), digital signal processors (DSP), field programmable gate array (FPGA), memory units, logic gates, registers, semiconductor device, chips, microchips, chip sets, and so forth. Examples of software elements may include software components, programs, applications, computer programs, application programs, device drivers, system programs, software development programs, machine programs, operating system software, middleware, firmware, software modules, routines, subroutines, functions, methods, procedures, software interfaces, application program interfaces (API), instruction sets, computing code, computer code, code segments, computer code segments, words, values, symbols, or any combination thereof. Determining whether an example is implemented using hardware elements and/or software elements may vary in accordance with any number of factors, such as desired computational rate, power levels, heat tolerances, processing cycle budget, input data rates, output data rates, memory resources, data bus speeds and other design or performance constraints, as desired for a given example.
Having described and illustrated the principles of the disclosed technology in a preferred embodiment thereof, it should be apparent that the disclosed technology can be modified in arrangement and detail without departing from such principles. We claim all modifications and variations coming within the spirit and scope of the following claims.
Number | Date | Country | Kind |
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2015 1 0048381 | Jan 2015 | CN | national |
Number | Name | Date | Kind |
---|---|---|---|
20040027138 | Pickerd | Feb 2004 | A1 |
20050185769 | Pickerd | Aug 2005 | A1 |
20110163762 | Marchetti | Jul 2011 | A1 |
Entry |
---|
European Search Report and Written Opinion for EP Application No. 16153456.5, dated Jun. 24, 2016, 9 pages. |
Number | Date | Country | |
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20160226558 A1 | Aug 2016 | US |