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Perform automated communications measurement

Posted: 17 Dec 2012 ?? ?Print Version ?Bookmark and Share

Keywords:communications measurement? data analysis? arbitrary waveform generator?

Automating communications measurement entails more than merely creating a push-button interface to control instruments. An ideal automated system combines data analysis, instrument control, and reporting. For example, such a system might fit a model to measured data, compare model predictions to new measurement data, and summarise the results in a document. Most currently available automated systems are good at one of these tasks but not othersfor example, a solution might offer excellent instrument control but poor data analysis abilities.

This article shows how you can automate the entire measurement process in MATLAB. We will demonstrate the automation through two examples. The first shows the combination of instrument control and data analysis in a MATLAB GUI. The second shows automated data analysis and report writing, and demonstrates how to create a stand-alone executable that can be shared with end users without exposing the underlying code.

Combine instrument control and data analysis
This example shows how you can combine measurement taking, data analysis, and visualisation in one GUI-driven MATLAB application. Our goal is to model the response of an unknown circuit to a known input from an Agilent 33220A arbitrary waveform generator. Our test setup consists of an unknown circuit, an external sound card to capture the output of the unknown circuit, the waveform generator, and, of course, MATLAB (figure 1).

Figure 1: A MATLAB application controlling a waveform generator and modelling the response of an unknown circuit.

The first step is controlling test equipment from MATLAB using Instrument Control Toolbox. The tool-box enables us to control equipment via a variety of interfaces, including USB, LXI, and GPIB. It also provides instrument-specific drivers for many instruments from Agilent, Tektronix, Rohde & Schwarz, and other vendors.

Controlling an instrument involves creating and opening a session using a protocol object, writing commands to the session, and reading the instrument's response. We can connect to and control an Agilent 33220A arbitrary waveform generator via the VISA interface using the following code:

interfaceObj = visa('AGILENT', VISAaddress)
% Create a device object.
fgen = icdevice('agilent_33220a.mdd', interfaceObj)
% Connect device object to hardware.
% Set the voltage amplitude to 0.2 V

set(fgen, 'Amplitude', 0.2)

As you can see, the code is straightforward.

Next, using the GUIDE tools in MATLAB we build a GUI-based application for real-time instrument control, data analysis, and visualisation. Via the GUI, the user controls the instrument settings and starts the measurement process (figure 2).

Figure 2: Measurement, data analysis, and visualisation GUI.

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