In part 3 of this series, we used the inverse fast Fourier transform (IFFT) to create 100-Hz time-domain waveforms of various amplitudes and phases. We can also use the IFFT to create waveforms containing multiple frequencies. If you look closely at Figure 1 in part 1 of this series, you’ll notice that the time-domain waveform […]
Analyzer
How to calculate and apply the inverse discrete Fourier transform: part 3
The inverse transform can create a time-domain waveform where no waveform has been before. In part 2 of this series, we used the discrete Fourier transform to convert a waveform from the time domain to the frequency domain, operated on the frequency-domain data, and used the inverse transform to reconstruct the altered time-domain waveform. That’s […]
How to calculate and apply an inverse FFT: part 2
In part 1 of this series, we looked at the formula for the inverse discrete Fourier transform and manually calculated the inverse transform for a four-point dataset. Then, we used Excel’s implementation of the inverse fast Fourier transform (IFFT) to verify our work. Could we try something more realistic? Sure. We can take a signal […]
How to determine noise figure: part 4
Two incompatible definitions of noise factor can lead to confusion, which you can alleviate by understanding where the differences lie.
How to determine noise figure: part 3
Noise factor and noise figure as defined in an IEEE standard can be derived from a two-port device’s equivalent noise temperature. In part 1 and part 2 of this series we discussed several ways to indicate the noise performance of a device under test (DUT). We first introduced the concept of noise factor based on […]
How to determine noise figure: part 2
The relationship between noise and temperature prompted a precursor of the IEEE to promulgate an alternative definition of noise figure in 1959. In part 1 of this series, we described the work of the Danish-American radio engineer Harald Friis, who described noise factor F of a device or system as the ratio of the input-power […]
How to interpret a QAM display: part 1
A constellation diagram plots a quadrature amplitude modulation (QAM) signal’s in-phase and quadrature components. The EE World article “Should I use a spectrum, signal, or vector network analyzer?” in part 3 mentioned that vector-signal analyzers (VSAs) can display modulation-domain and frequency-domain information. Other instruments incorporating digital signal processing (DSP) capabilities, including oscilloscopes, can provide insights into […]
Should I use a spectrum analyzer, signal analyzer, or vector network analyzer? Part 4
A vector network analyzer can fully characterize components by deriving their scattering parameters. In earlier parts of this series, we looked at analog spectrum analyzers (part 1 and part 2) and vector signal analyzers (part 3), both of which monitor unknown signals, whether emanating from a system, device under test (DUT), or an enemy’s transmitter […]
Should I use a spectrum, signal, or vector network analyzer? part 3
In part 2 of this series, we looked at a swept-tuned spectrum analyzer and how it could sweep a frequency span of interest from 1 MHz to 1.1 MHz with a sweep time of 50 msec. As Figure 1 shows, the analyzer readily identifies a signal at 1.03 MHz but misses the intermittent signals shown […]
Should I use a spectrum, signal, or vector network analyzer? part 2
An analog spectrum analyzer’s sweep time can hide intermittent unwanted signals. In part 1 of this series, we examined a simplified block diagram of a traditional analog spectrum analyzer, which includes an RF frontend, mixer, voltage-controlled oscillator (VCO), intermediate-frequency (IF) stage, sweep generator, envelope detector, and display. We also looked at resolution bandwidth (RBW), the […]