A spectrum analyzer is a test and measurement instrument used to measure the magnitude of an input RF and Microwave signal versus frequency within the frequency operation range of the instrument.
Spectrum analyzers are mostly used for the measure of electrical (Radio and microwave Frequency) signals however, spectrum analyzers are also used to measure waves such as acoustic pressure waves and optical light waves using an appropriate transducer.
Using a spectrum analyzer a test engineer can analyze the frequency, power, bandwidth, distortion, harmonics, spurious, noise level, etc of an input signal. These electrical parameters of the RF and microwave signal are useful in the characterization of wireless transceivers.
To learn more about RF and Microwave systems, we recommend you to check the following Books.
To understand the spectrum Analyzer operation in a better way, we recommend understanding the following components, which are prime components used along with the spectrum analyzers for testing applications.
In this RF and Microwave spectrum Analyzer article, we will cover,
The spectrum analyzer displayed the frequency on the horizontal axis and the received signal amplitude on the vertical axis. A spectrum analyzer looks like an oscilloscope, but all the measurements are in the frequency domain, for an oscilloscope all the measurements are in the time domain.
Spectrum analyzers are distinguished by the methods used to obtain the spectrum of a signal (swept-tuned and fast Fourier transform (FFT)) and on the base of the form factors like Benchtop, Handheld Portable, and Networked type, etc.
Spectrum analyzers are classified as swept-tuned and fast Fourier transforms (FFT) on the basis of methods used to obtain the spectrum.
In a swept-tuned spectrum analyzer, superheterodyne receivers are used to down-convert a portion of the received input signal spectrum into the tuned center frequency. The instantaneous output power is measured as a function of time. By sweeping over the entire receiver's frequency using a VCO, the output is displayed as a function of frequency.
An FFT spectrum analyzer uses a particular mathematical algorithm to process and measure the received signal. FFT analyzer consists of a receiver and analog-to-digital converter. The receiver reduces the center-frequency of the received signal into tuned center frequency, it will help to reduce the sampling rate, that the FFT analyzer must contend with. For the converted digital samples, the FFT analyzer will process and display the measurements on the screen.
Spectrum analyzers are classified into four form factors mainly, Benchtop, portable, handheld, and networked-based spectrum analyzer.
Benchtop spectrum analyzers are generally AC power operated instruments, mainly used in a lab environment of R&D, production, manufacturing area. Benchtop spectrum analyzers offer better measurement specifications than portable-type units.
Spectrum analyzers with battery packs are called Portable spectrum analyzers, these batteries allow them to be used any ware away from AC power. Portable spectrum analyzers are designed to take outside fields to make measurements or along with any other real-time systems for the random check in the field.
Handheld spectrum analyzers are very light weighted and small in size with battery operation capability. Handheld analyzers usually have very limited measurement capability compared to benchtop analyzers. Prime features of handheld spectrum analyzer include:
Networked spectrum analyzers are designed to enable geographically-distributed spectrum analysis and monitoring applications by connecting the devices across a network over the Ethernet or wireless transceiver. Mostly these types of spectrum analyzers will not have a local monitor, data analysis and monitoring will happen in remote locations. These spectrum analyzers are mainly used to remotely monitor the interference in licensed spectral bands.
While most of the spectrum analyzers form factors to have an Ethernet port for control, they are typically lacking data transfer efficiency. Key attributes of networked spectrum analyzer include:
Different types of Spectrum Analyzer have different theories of operation, few are listed below.
A swept-tuned spectrum analyzer, down-convert a portion of the input Radiofrequency signal to the center frequency by sweeping the voltage-controlled oscillator over the range of frequencies. The bandwidth of the used band-pass filter dictates the resolution bandwidth of the spectrum analyzer. This sampled signal output power is measured using a detector as a function of time and sweeping over the entire receiver's frequency range to display the measurement as a function of frequency.
In FFT based spectrum analyzer, an analog signal will convert to a digital signal and use a digital signal processor for the Fourier transform on the input sample digital signal. A Fourier transform will produce a full spectrum containing all frequencies from zero. FFT-based spectrum analyzers have limitations in the frequency range of operation.
Hybrid Superheterodyne-FFT is a combined swept and FFT analysis for wide and narrow spans analysis. This technique allows for faster sweep time. In this method first, the signal is down-converted using a down convertor to an intermediate frequency and then digitized using FFT techniques to acquire the spectrum.
A real-time spectrum analyzer will sample the incoming RF spectrum in the time domain and using the FFT process in parallel convert the measured information to the frequency domain.
This spectrum analyzer will sample data online and fast enough to satisfy the Nyquist Sampling theorem and in real-time it will store the data into its memory for later offline processing.
When selecting a Spectrum Analyzer analyzer for the testing of RF and microwave signals, the following are the main parameters that need to consider.
The frequency coverage range of the spectrum analyzer including the lower frequency from with it can start and up to what frequency it can measure. Following are the prime parameter related to frequency need to consider.
Start frequency: Frequency from with spectrum analyzer can start measure in MHz.
Stop frequency: Frequency up to which spectrum analyzer can measure in GHz.
Center frequency: The frequency mid-way between the start and stop frequencies is known as the center frequency. The center frequency will be an actual frequency of measurement of interest. It will be in the middle of the frequency axis.
Span: The frequency range between the start and stop frequencies. Span setting help to enhance the visibility of the frequency spectrum measured in a spectrum analyzer.
Resolution bandwidth or RBW filter is an IF bandpass filter in the IF path before the detector. Resolution bandwidth determines the RF noise floor and it shows how close two frequency signals can be resolved by the analyzer.
The video bandwidth filter is a low-pass filter after the envelope detector. Averaging or peak detection of the detector takes several samples per time step and stores only either the average or the highest of the samples.
VBW will remove noise in the detector output and smooth the display. If the VBW is less than the RBW, it will affect the sweep time of the display.
Detectors are used to detect the peak and average of the signal and adequately map the correct signal power to the respective frequency point on the display. There are three types of detectors: sample, peak, and average.
Sample detection: Sample detection simply uses the midpoint of a given frequency interval as the display point value.
Peak detection: Peak detection uses to detect the maximum measured point in the given interval of display points. Peak detection ensures that the maximum or the peak of the sinusoid is measured within the interval. peak detection will not give a perfect representation of random noise.
Average detection: Average detection uses power (RMS) averaging, voltage averaging, of all the data points within the interval to display point value.
Displayed Average Noise Level will display the average noise level on the analyzer with a specific resolution bandwidth. Average noise level is the sensitivity of the spectrum analyzer ( Minimum signal a spectrum analyzer can be measured). If the received signal level becomes equal to the average noise level it will be difficult to detect and display the measurements.
Spectrum analyzer is one of the prime test and measurement instruments in the RF and microwave industry. Spectrum analyzers are available as a dedicated instrument with different additional test features like time-domain measurement, power measurement, cable fault locating, etc as well as being a part of other instruments like radio communication analyzers, vector network analyzers, etc.
Below are the top spectrum analyzers manufacturers, who can offer a suitable instrument for your LAB and field test requirements.
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