Spectrum Analysis Basics: What is a Spectrum Analyzer? 

Spectrum Analysis Basics What is a Spectrum Analyzer
Spectrum Analysis Basics:What is a Spectrum Analyzer?

The concept of signal spectrum and spectrum analysis can be a bit intimidating if one is not aware of the basics. There is a lot that goes on when working with a spectrum analyzer, such as simple amplitude, frequency measurements, to more complex aspects such as application-specific measurements. There are a lot of things to keep in mind! For now, let us talk about the basics of spectrum analyzers and signal spectrums just to build a base of understanding. 

Defining Signal Spectrum 

The distribution of signal power across different frequencies is called signal spectrum. This provides information on the frequencies in a signal sent out and their power levels, also called amplitudes. 

What are Spectrum Analyzers Online? 

The tool used to measure and see the signal spectrum is known as a Spectrum Analyzer. At a basic level, a spectrum analyzer online acts as a frequency-selective, peak-responding voltmeter adjusted to show the root-mean-square (or RMS) value of a sine wave. Unlike a power meter, a spectrum analyzer scans for and analyzes digital signals with the capability to dive a bit deeper into the signals. 

Different Types of Spectrum Analyzers 

In the early days, Spectrum Analyzers only measured the amplitude of a wave. As the communications industry evolved over time, so did the swept-tuned and super heterodyne spectrum analyzers of that time. When the need to take phrase measurements became a thing, signal analyzers took over the more basic parts of the analyzers, offering more complex and accurate readings. Spectrum analyzers measure the magnitude of an input against the frequency of a signal. Vector signal analyzers are capable of measuring the magnitude and phase of an input signal at a single frequency. Modern signal analyzers online combine the functionality of the earlier evolutions such as the analog, vector, and fast Fourier transform (FFT) measurements. Alongside these high-functioning new signal analyzers, there are other more compact options as well. Even though the terms signal analyzers and spectrum analyzers are not replaceable, they do represent the same measurements and concepts at times. A lot of people use the word spectrum analyzer to talk about signal analyzers. 

Difference Between Frequency Domain and Time Domain 

When a signal analyzer is measuring and visualizing the signal spectrum, including the complex signals, and is helping the user in understanding the functionality of the device under test (DUT), then what is the difference between a signal analyzer and an oscilloscope? The oscilloscope takes measurements in time, using units such as Volts /sec. This allows the user to view values of an electrical event as a function of time instantly. 

The users can be moved from the time domain to the frequency domain using a Fourier transform. This theory tells us that any time-domain phenomenon has one or more sine waves of the appropriate phase, frequency, and amplitude. The domain of the frequency then reveals new information about the signals, such as the amount of energy present at each calculated frequency. The using of the frequency domain then helps the user to view every sinusoidal wave separately, or spectral components and see how they are contributing to the response of the user. 

Measuring in the Frequency Domain 

Complex signals in the time domain look highly different from the frequency domain. The figure below shows that the time domain measurement shows a sine wave which is impure. The sources and frequency of the second harmonic wave remains unknown without measuring waves in the frequency waves. Spectrum analysis can uncover sources of interference by displaying the spectral components of a wave independently. Information such as the pulse rise and fall times of a signal can still be provided by the time domain, but the frequency domain allows the user to determine the harmonic content of a signal, such as out-of-band emissions and distortion.

Measuring in the Frequency Domain 

The Application of Signal Analyzers 

Once we know why signal analyzers are used, let us dive a bit into why they are used. Spectrum analysis can be applied across many parts of engineering. Talking about an application, engineers need to check cellular radio systems for the harmonics of the carrier signal to prevent interference between several systems operating at similar frequencies. The distortion of a message set onto a carrier also needs spectrum analysis, as seen in the figure below. Third-order intermodulation, a troublesome issue, comes into play when two tones from a complex signal modulate one another. The distortion components resulting from this phenomenon can fall into the band of interest, which means that they are unremovable with a simple filter.

Measuring in the Frequency Domain 

Government agencies are also known to utilize spectrum analysis to keep an eye on the usage of allocated spectrum. Different bands of frequency are reserved for different activities, such as Wi-Fi, emergency communication, mobile phones, and many others. If the transmitters do not stay within their frequency bands allocated to them, signal energy can enter other channels, causing interference as seen below.

spectrum analysis

EMI (electromagnetic interference), which is another type of interference, damages the operation of other systems. EMI is the unwanted radiation or emissions conducted, such as emissions from an electronic device or power lines. It is compulsory for all electronic devices to undergo EMI compliance testing to make sure they stick to the standard regulations set by the Government or industry. Some signal analyzers feature EMI pre-compliance testing to make sure that DUTs pass their compliance tests as shown below.

unwanted variations

A signal also analyzed commonly is noise. Noise means random and unwanted variations in your signal amplitude or disturbances in it. Noise distorts the original signal and is capable of masking and overtaking the entire signal as well. Measurements such as the noise figure seen below, signal-to-noise (SNR) ratio, and phase noise can help engineers understand the performance of a device or the overall system.

small percentage

The applications described here represent just a small percentage of what spectrum analysis allows engineers to do in today’s world.

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