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Stay up-to-date on specials, price and availability- Introduction
- What Is a Spectrum Analyzer?
- Types of Spectrum Analyzers
- What Aspects To Look For in a Spectrum Analyzer
- Frequency Range
- Resolution Bandwidth
- Video Bandwidth
- Span
- Phase Noise Performance
- Amplitude Range
- Input Power
- Why Buy Premium Used?
- Closing Thoughts From Keysight
- Whenever you’re ready, here are 4 ways we can help you
- FAQ
When purchasing a spectrum analyzer, choosing the right model for the correct application can be challenging. Not all spectrum analyzers are the same. The frequency range, level of accuracy, and measurement types can vary significantly from one model to the next.
Understanding the different spectrum analyzers available and their functions is essential to ensure you purchase the right one for your needs. We know you don’t want to waste your time and money, so we created this guide to walk you through the basics of spectrum analyzers. Knowledge equals power, the power to make an informed purchase!
What questions will we answer, and what information will we consider?
- What is a spectrum analyzer?
- What do you use a spectrum analyzer for?
- Types of spectrum analyzers
- What aspects to look for in a spectrum analyzer
What Is a Spectrum Analyzer?
A spectrum analyzer is a tool used to visualize and analyze the spectral content of signals. It accomplishes this by measuring the magnitude of the input signal versus its frequency over the entire frequency range.
Think of this as a means to see a signal's "frequency fingerprint." This fingerprint will help you determine the signal power of an instrument and how that signal makes up different frequency components.
Spectrum analyzers usually consist of a display, a sweep generator, and a filter.
- The display shows the strength of the signal at each frequency. You can then determine the contents of a signal and identify any problems that may be present.
- The sweep generator produces a signal that sweeps across the desired frequency range.
- The filter only allows the portion of the signal within the desired range to pass through to the display. This process works in conjunction with digital signal processing.
Thanks to technological advances, modern spectrum analyzers are smaller and more affordable than ever. They are also more accurate and have more features than their predecessors.
Whether you are an engineer or a hobbyist experimenting with electronics, a spectrum analyzer is a valuable tool to have.
An engineer would use a spectrum analyzer to run tests on electronic equipment like cell phones, radios, and TV towers to ensure they function as intended with no interference from other devices. A hobbyist might use a spectrum analyzer to check the quality of an audio signal or track down interference sources.
Spectrum Analyzers vs. Oscilloscopes
While spectrum analyzers and oscilloscopes are both essential for understanding the behavior of electronic signals, they work in different ways.
- Oscilloscopes measure the shape or amplitude of a signal over time. They are best suited for analyzing time-varying signals, such as those produced by transistors and motors. They also observe the rise and fall of voltage levels and the shape of waveforms.
- Spectrum analyzers measure the amplitude of a signal over a wide range of frequencies. They are better suited for analyzing complex signals that contain multiple frequencies. You can also use a spectrum analyzer to find harmonics and other frequency elements that might be problematic.
Combining the two devices gives a more accurate picture of what is happening with a signal. So, in many cases, a spectrum analyzer and oscilloscope are necessary to fully understand a signal's behavior.
What Do You Use a Spectrum Analyzer For?
A spectrum analyzer has many applications. You can use a spectrum analyzer for radio, wireless communication, and audio engineering. They will also help troubleshoot electronic equipment andoptimize wireless systems.
Standard signal analysis applications include
- The frequency spectrum of a signal. Spectrum analyzers help to identify the source of interference on a particular frequency. They will display a graph of a signal's amplitude (y-axis) versus frequency (x-axis). While dBm (decibels per milliwatt) typically measures amplitude, MHz (megahertz) generally measures frequency.
- Voice and data communications. Spectrum analyzers will identify the source of a signal's interference or inability to meet performance requirements. Identification of the problem helps to mitigate the problem, optimize system performance, and ensure compliance with regulatory standards.
- Video broadcast. Spectrum analyzers ensure that the transmitted signal is strong enough to reach its intended destination. The signal splits into constituent frequencies, and each frequency is subsequently measured. The results of these measurements will help evaluate the overall strength of the signal. If the signal is too weak, it can result in poor picture quality or dropped connections. Spectrum analyzers are essential in ensuring video broadcast signals are of the highest quality.
- Radar. Spectrum analyzers send out a pulse of electromagnetic energy and measure the reflected energy. This helps determine the range, velocity, and direction when tracking an object or navigating. Analyzing the spectrum of the reflected energy also makes it possible to obtain information to identify the composition or nature of targets.
- Wireless technology. Spectrum analyzers will identify the best channel for a wireless router or access point when Wi-Fi testing. Measuring the strength of the signal on each channel will help identify any interference. In addition, spectrum analyzers will diagnose wireless connectivity problems, identifying whether the issue is with the router or the client's device.
Types of Spectrum Analyzers
Each type of spectrum analyzer has unique features. For example, some are better suited for analyzing radio signals, while others are more adept at measuring audio frequencies. The desired application will determine suitability.
Now that we have identified some key fundamentals of spectrum analyzers, let's take a look at some of the different types on the market. We will consider vector signal analyzers, swept spectrum analyzers, and real-time spectrum analyzers.
Vector Signal Analyzers
Vector Signal Analyzers (VSAs) allow you to design, validate, and debug communication systems. They provide insight into the behavior of these systems by providing measurements of the signal's amplitude, phase, and frequency.
VSAs also offer advanced analysis capabilities, such as
- Time-domain analysis
- Eye diagram analysis
- Modulation analysis
These capabilities make VSAs invaluable for ensuring communication systems meet their performance requirements. VSAs are available in various forms, including benchtop units, modular units, and hand-held units.
| Vector Signal Analyzer Pros | Vector Signal Analyzer Cons |
|---|---|
| Measure the magnitude and phase of a signal. This is important because many real-world signals are not sinusoidal and have different amplitudes at varying frequencies. | Limited frequency range. They can only measure signals at a specific frequency. |
| Characterize complex signals. A complex signal can be a combination of multiple sinusoidal signals with different amplitudes, phases, and frequencies. | Limited dynamic range. They can only accurately measure signals within a certain range of amplitudes. Combined with their restricted frequency range, this may be limiting for some applications. |
| The ability to generate eye diagrams. These are graphical representations of how well an electrical signal conforms to certain standards. Eye diagrams are commonly used in digital communications systems to assess signal quality. | Typically have a much higher learning curve than their traditional counterparts. New users may find it challenging to become proficient in their use. |
Swept Spectrum Analyzers
Swept spectrum analyzers sweep a sinusoidal signal across a frequency range RF (radio frequency) spectrum and measure the system's response under test at each frequency. A graph typically displays the results, with amplitude (y-axis) versus frequency (x-axis).
By observing the shape of the response curve, you can determine the system's center frequency, bandwidth, gain, and noise floor.
Swept spectrum analyzers troubleshoot and monitor RF systems, such as cellular communications, WiFi networks, satellite systems, and radar systems. They also measure the performance of RF components, such as filters, amplifiers, and antennas.
| Swept Spectrum Analyzer Pros | Swept Spectrum Analyzer Cons |
|---|---|
| Faster and easier to use. They take measurements in just a few seconds, while traditional spectrum analyzers can take several minutes. | Generally less sensitive than Fourier transform-based analyzers, making them less suitable for low-noise applications. |
| More accurate. Swept spectrum analyzers combine multiple measurements taken at different frequencies to create a more precise picture of the signal's power. Traditional spectrum analyzers measure the power of a signal at each frequency within its bandwidth. The strength of a signal can vary significantly from one frequency to another, resulting in an inaccurate measurement. | Subject to distortion due to how the signal spreads out over the frequency spectrum. |
| Less expensive. As they use fewer components than a traditional analyzer, a swept spectrum analyzer is an excellent choice if you need an affordable analyzer that is accurate and easy to use. | Requires a stable local oscillator. This can be challenging to generate for some frequencies. |
Real-Time Spectrum Analyzers
Real-time Spectrum Analyzers (RSA) are electronic devices that measure a signal's strength and frequency domain. They use a process called Fast Fourier Transform (FFT), which converts the signal into a series of numbers representing the amplitude of each frequency component.
As its name suggests, time domain signals depend on time, whereas frequency domain signals rely on frequency. The Fourier transform enables signal transformation from one domain to another, connecting the two. The time and frequency domains are effective analytical techniques that offer crucial information about signal properties.
The RSA displays the domain information on a graph, which will help identify any problems with the signal. For example, too much noise or distortion will appear on the graph. Real-time analysis is mainly used in research and development settings as it is essential for characterizing signals and testing new equipment.
| Real-time Spectrum Analyzer Pros | Real-time Spectrum Analyzer Cons |
|---|---|
| Provides a more accurate picture of the signal environment. RSAs do not rely on taking samples of the signal at discrete points in time. Instead, they analyze the signal continuously, providing a “true” representation of the signal's behavior. | Often have reduced frequency resolution. This makes it difficult to identify subtle signal abnormalities. |
| Faster measurement setups and easier identification of signal anomalies. | Typically require more time to set up and configure than conventional models. |
| Easily configured to display only the information that is important to you. They offer great flexibility and insight into your signal environment. | Real-time analysis is less suited for analyzing very low-frequency signals. |
What Aspects To Look For in a Spectrum Analyzer
There are different aspects you will need to consider when shopping for a spectrum analyzer; from the resolution bandwidth to the phase noise performance and amplitude range. Let's take a look at seven of these main aspects.
Frequency Range
The frequency range is an important factor to consider because different spectrum analyzers measure different ranges of frequencies.
For example, some spectrum analyzers measure audio frequencies (20 Hz – 20 kHz), while others measure radio frequencies (10 MHz – 10 GHz). Before buying a spectrum analyzer, it is important to figure out what range of frequencies you need to measure. Once you know this, you can narrow your search to a spectrum analyzer that suits your needs.
Resolution Bandwidth
The resolution bandwidth determines the minimum width of a signal that a spectrum analyzer can resolve, typically expressed in Hertz (Hz).
A high-resolution bandwidth measurement allows for more accurate readings of narrow signals, while a low-resolution bandwidth measurement is suited for reading broad signals. When choosing a resolution bandwidth, it is vital to consider the application for which you will use the spectrum analyzer.
For example, a high-resolution bandwidth will be necessary if your goal is to measure very narrow signals, such as those generated by RF transistors. If your goal is simply to measure the overall power of a signal, then a lower resolution bandwidth will suffice.
Video Bandwidth
The video bandwidth is the width of the frequency range an analyzer can process. The wider the bandwidth, the more information the analyzer can take in. This is crucial when working with complex signals such as those generated by digital devices.
Digital devices often generate signals with very sharp edges, called transients. A wider video bandwidth allows the spectrum analyzer to take more of these transients into account, leading to more accurate measurements and minimizing signal distortion. If you plan on using your spectrum analyzer to measure digital signals, ensure it has a wide enough video bandwidth to accommodate them.
Many spectrum analyzer models offer different bandwidths, so you can be sure to find one that is perfect for what you require.
Span
The span refers to the range of frequencies an analyzer can measure. A wider span means the analyzer can measure a larger range of frequencies, which is helpful for troubleshooting or measuring signals with a wide frequency range. A good rule of thumb is to choose an analyzer with a span that is at least twice the bandwidth of the signal you want to measure.
The influence span has on the sweep time of a signal is also significant. Sweep time refers to the time it takes for the micron beam to travel once across the sample under test. Span directly affects the signal's bandwidth and the amount of information captured in each sweep.
A wider influence span means more information captured per sweep. When selecting a spectrum analyzer, you should consider the amount of data that needs capturing and the desired sweep time.
Phase Noise Performance
When deciding on the right spectrum analyzer, you must keep the phase noise in mind. Phase noise is the measurement of how stable the signal is over time. The type of oscillator used with a spectrum analyzer will affect phase noise, since they are the primary source of instability in a signal.
Oscillators can be either crystal-based or atomic-based. Crystal-based oscillators are less expensive but also less stable, making them more likely to produce signals with phase noise. On the other hand, atomic-based oscillators are much more stable and produce signals with minimal phase noise.
A low phase noise means the signal is more stable and less likely to have measurement errors. A stable signal is vital for:
- Capturing a clear and accurate picture in medical imaging
- Maintaining a strong connection for telecommunications
- Tracking moving targets using radar systems
Amplitude Range
The amplitude range is the difference between the largest and smallest signal a spectrum analyzer can measure. A larger amplitude range means an analyzer can measure a broader range of signal strengths and frequencies. This is crucial as it allows for accurate measurements of very weak or powerful signals at different frequencies.
There are two key specifications associated with amplitude measurements: absolute accuracy and relative accuracy.
- Absolute accuracy specifies the precision with which amplitude measurements are made. It describes how close the measured value will be to the actual value of the measured signal.
- Relative accuracy specifies the precision with which one amplitude measurement compares to another.
As with actual measurements made by a spectrum analyzer, there are always some inherent measurement errors associated with amplitude range. By understanding these two key specification types, you can select a spectrum analyzer that will be best suited to your application in terms of precision and accuracy.
Input Power
The input power is the amount of power a spectrum analyzer can accept without damaging the internal components. However, if the input power is too low, the signal will be too weak to produce accurate results. Conversely, if the input power is too high, it will damage the device. To prevent this, most spectrum analyzers have an input power protection feature that limits the amount of power that can enter the device.
It is important to note that a spectrum analyzer's input power specifications differ from the output power specifications. The output power is the amount of power the device can generate.
When choosing a spectrum analyzer, you want to select one with an appropriate input and output power for the signals you will be measuring.
Why Buy Premium Used?
If you are looking for a quality spectrum analyzer, look no further than Keysight. Our premium refurbished analyzers are the best on the market, available at a fraction of the price. We guarantee you will not have to compromise on performance and accuracy when buying from us.
If you are looking for a device that can measure a wide range of signals with precision and reliability, a Keysight premium refurbished spectrum analyzer is a perfect choice.
Closing Thoughts From Keysight
In this buying guide, we have covered the key features and uses of spectrum analyzers. This information will help you on your quest to purchase a suitable analyzer.
When shopping for an analyzer, consider factors such as phase noise, amplitude range, and input power. It is also important to keep in mind your intended use. Are you an engineer needing a spectrum analyzer to run tests on electronic equipment? Or a hobbyist wanting to check the quality of an audio signal?
Our team will help you find a premium refurbished spectrum analyzer that is right for you.
Why Should You Buy Premium Used From Keysight?
We are the only company that can provide calibration of your premium used spectrum analyzer. That means you can get straight to work using a reliable and accurate device of the highest standard.
We offer a fast two-week delivery time* for selected spectrum analyzers, which is 6-19 weeks faster than other resellers.
We provide an upgradable warranty, giving you peace of mind knowing you are getting a quality product backed by a trusted manufacturer. Call 1-800-829-4444 and ask to speak to tech support today.
See Keysights Used Equipment for the widest selection of discounted, high-quality refurbished spectrum analyzers.
(* Two weeks shipping time offer available for US customers only. Dependent on item availability and location.)
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FAQ
What is a spectrum analyzer?
A spectrum analyzer is a device that allows you to see the frequency components of a signal. It measures each component's strength and the signal's total power.
How to use a spectrum analyzer?
There are a few different ways to use a spectrum analyzer. The most common is to connect it to an oscilloscope, allowing you to see the signal's shape.
What can you do with a spectrum analyzer?
You use a spectrum analyzer to troubleshoot electronic equipment and design and test new equipment.
What is the range of spectrum analyzers?
A spectrum analyzer's frequency range varies from approximately 3 Hz to 50 GHz.
What are the time domain and frequency domain?
Time domain signals depend on time, whereas the frequency domain rely on frequency. Both domains are related to one another. These domains are effective analytical techniques that offer crucial information about signal properties.
Is a spectrum analyzer an oscilloscope?
No, a spectrum analyzer is not an oscilloscope. An oscilloscope is a device that allows you to see the shape of a signal. A spectrum analyzer visualizes and analyzes the spectral content of signals.
Can a spectrum analyzer measure power?
Yes, a spectrum analyzer measures the power of the spectrum of known and unknown signals.