Lesson 1 - Overview of Signal Analyzer

Introduces the spectrum analyzer. A spectrum analyzer is a device that measures the amplitude of a signal as it varies by frequency. It is used to analyze the frequency content of a signal, and to troubleshoot and characterize electronic systems.

Lesson 2 - What is a Spectrum Analyzer and the Measurements You Can Make?

Discusses the measurements that can be made with a spectrum analyzer. These measurements include frequency, amplitude, width, phase, and spurious emissions. Spectrum analyzers can be used to measure a variety of signal characteristics, and there are different types of spectrum analyzers, each with its own strengths and weaknesses. The features of a spectrum analyzer depend on its type and its intended use.

Lesson 3 - Time Domain vs. Frequency Domain—What’s the Difference?

Discusses the time domain and the frequency domain. The time domain is the representation of a signal in terms of its time variation, while the frequency domain is the representation of a signal in terms of its frequency components. The Fourier transform is used to convert between the time domain and the frequency domain.

Lesson 4 - What is Spectrum and Spurious Emissions?

Spectrum is the distribution of signal power across a range of frequencies, while spurious emissions are unwanted signals that are present in a signal's spectrum. Spectrum analyzers can be used to measure spectrum and spurious emissions, which can help engineers design and troubleshoot electronic systems.

Lesson 5 - How to Increase Your Signal Analyzer's Dynamic Range to See Low Level Signals

How to increase the dynamic range of a spectrum analyzer. Dynamic range is the difference between the smallest and largest signals that can be measured by a spectrum analyzer. There are a number of techniques that can be used to increase the dynamic range, including averaging, attenuating the input signal, and using a narrow bandwidth.

Lesson 6 - What is Noise Figure and How to Measure It?

Discusses noise figure, which is a measure of how well a spectrum analyzer can distinguish between a weak signal and the noise floor. A lower noise figure indicates that the spectrum analyzer introduces less noise, which results in a higher SNR. This is important for applications such as measuring spurious emissions.