Types and Applications of Spectrum Analyzers

Spectrum Analyzer is mainly used to display the spectrum characteristics of the frequency domain input signal, so it is an indispensable measuring instrument for signal analysis. Spectrum analyzer analyzes and studies signals through the frequency domain, and is also applied to more different fields, such as wireless signal transceivers, signal interference detection, spectrum monitoring, and component characteristics analysis. It is a common tool for electronic product research and development, production, and inspection. It is especially necessary for the measurement of wireless communication signals. Its application is very wide, so some engineers call it a multimeter for RF measurement. Its main functions include: frequency setting, reference level setting, tracking generator setting, tracking control setting, using the marker function to measure return loss, as well as bandwidth, sweep time and trigger control settings.

For time domain signal measurement, an oscilloscope is a very important and efficient measuring instrument that can directly display the response changes of signal amplitude, frequency, period, waveform and phase. Generally speaking, an oscilloscope must have a dual-track output display device and built-in IEEE-488, IEEE-1394 or RS-232 interface functions to connect with drawing instruments, which is conducive to subsequent measurement display information output and drawing research and comparison. However, the disadvantage of an oscilloscope is that it is limited to low-frequency signals, and the analysis of high-frequency signals becomes a big challenge.

The advantage of a spectrum analyzer is that it makes up for the shortcomings of an oscilloscope in analyzing high-frequency signals. It can simultaneously present multi-frequency signals in the frequency domain, making it easier to identify power devices at different frequencies and display the characteristics of the signal in the frequency domain.

Figure 1 The difference between time domain measurement and frequency domain measurement

Spectrum Analyzer Types

Spectrum Analyzer is mainly used to display the spectrum characteristics of the frequency domain input signal. It is divided into two types according to the difference in signal processing methods, namely real-time spectrum analyzer and sweep-tuned spectrum analyzer.

A real-time spectrum analyzer can display the signal amplitude in the frequency domain at the same time. Its working principle is to set corresponding filters and detectors for different frequency signals, and output the signals to the screen through a synchronous multiplexed scanner. Its advantage is that it can display the instantaneous response of periodic random waves, but its disadvantage is that it is expensive, and the bandwidth range, number of filters and maximum multiplexed switching time will limit its performance.

The swept tuned spectrum analyzer is the most commonly used type of spectrum analyzer. Its basic structure is similar to that of a superheterodyne receiver. Its main working principle is that the input signal is directly added to the mixer through an attenuator. The adjustable local oscillator generates an oscillation frequency that changes linearly with time through a scan generator synchronized with the CRT screen. The mixer and the input signal are mixed to produce a down-converted intermediate frequency (IF) signal, which is then amplified, filtered, and detected and transmitted to the CRT screen. Therefore, the vertical axis of the CRT screen will show the relative relationship between the signal amplitude and frequency.

As mentioned above, the key factor affecting the signal response is the filter bandwidth. The function affected by the Gaussian-Shaped Filter is the resolution bandwidth (RBW) commonly seen in measurements. RBW represents the minimum bandwidth difference between two different frequency signals that can be clearly distinguished. Therefore, if the bandwidth of two different frequency signals is lower than the resolution bandwidth of the spectrum analyzer, the two signals will overlap and cannot be distinguished. Such a seemingly lower RBW will help to distinguish and measure different frequency signals, but too low RBW may filter out higher frequency signals, resulting in distortion when the signal is displayed. A higher RBW will certainly help to measure broadband signals, but it may increase the noise floor, reduce measurement sensitivity, and easily hinder the detection of low-intensity signals. The distortion value is closely related to the set RBW, so setting the appropriate RBW width is an important concept for the correct use of the spectrum analyzer.

In addition, the front-end circuit of a traditional spectrum analyzer is a receiver that can be tuned within a certain bandwidth. When the input signal is converted by the frequency converter, it is output by the low-pass filter. The value output by the filter is the vertical component, and the frequency is the horizontal component. The coordinate diagram displayed on the screen is the input signal spectrum diagram. Since the frequency converter can reach a very wide frequency (such as from 30Hz to 30GHz), it can be increased to more than 100GHz in conjunction with an external mixer. Therefore, the spectrum analyzer is one of the measuring instruments with the widest frequency coverage. Whether it is measuring continuous signals or modulated signals, the spectrum analyzer is an ideal measurement tool. The only disadvantage of the traditional spectrum analyzer is that it can only measure the amplitude of the frequency, but lacks phase information. Therefore, it is a scalar instrument rather than a vector instrument in nature.

The new generation of spectrum analyzers are measuring instruments based on fast Fourier transform (FFT). The measured signal is decomposed into discrete frequency components through Fourier operation, thereby achieving the same results as traditional spectrum analyzers. The new spectrum analyzer uses a digital method, directly sampling the input signal through an analog/digital converter (ADC), and then obtains a spectrum distribution diagram after Fourier operation processing.

In today's measurement, no matter what signal it is, it can be measured in many ways. The most basic instrument usually used is an oscilloscope, which observes the waveform, frequency and amplitude of the signal. However, due to the complexity of signal changes, many information cannot be detected by an oscilloscope. For example, if you want to analyze a non-sinusoidal signal, theoretically, it is composed of vectors of different frequencies and voltages. From the perspective of analysis, the horizontal axis of the oscilloscope represents time, the vertical axis is the voltage amplitude, and the curve represents the voltage waveform that changes with time. This is a time domain measurement method. If you want to observe its frequency composition, you must use the frequency domain method, with the horizontal axis being the frequency and the vertical axis being the power amplitude. In this way, you can see the distribution of power amplitude at different frequency points, and you can understand the spectrum of these signals. With the spectrum of these single signals, you can continue to reproduce and copy complex signals, which is very important for signal analysis.

When a digital signal contains many image and sound signals, its spectrum distribution will be quite complex. In satellite monitoring, these signals must obtain the required parameters from the perspective of spectrum analysis. There are currently two methods to analyze signal frequencies. The first is to collect the signal in the time domain, and then perform Fourier transform on it to convert it into a frequency domain signal. This method is called dynamic signal analysis. The characteristics are relatively fast, with a higher sampling rate and higher resolution. Even if two signals are very close, they can be distinguished by Fourier transform. However, since digital sampling analysis is used, the highest frequency of the signal that can be analyzed is affected by its sampling rate, which limits the analysis of high-frequency signals. Therefore, the current highest analysis frequency is only around 10MHz, and such a measurement range belongs to vector analysis. This analysis method is generally used for the analysis of low-frequency signals, such as sound and vibration. The principle of the other method relies on hardware circuit implementation rather than conversion through mathematical equations. It can directly receive signals. This type of analysis instrument is called a superheterodyne receiving direct scanning tuned analyzer, which is the scanning tuned spectrum analyzer mentioned above.

Spectrum Analyzer Applications

The main function of a spectrum analyzer is to measure the size or amplitude of a signal. Its application range is very wide, including system maintenance, signal measurement, component frequency gain and material quality control, etc.

Measurement of amplifier gain, frequency response and passive component characteristics

Cable TV and communication systems use a large number of passive components such as amplifiers, taps, connectors, and coaxial cables. The quality of the components will affect the characteristics of the signal, so prior screening helps to ensure the quality of the signal. For example, the frequency response characteristics of the device under test (DUT) can be evaluated through the tracking generator of the spectrum analyzer, and the measurement results can be output by the plotter to obtain data. The range of the measurement frequency can be set once in advance, and the corresponding relationship curve can be obtained at once, which will greatly reduce the complicated operation procedures that must be measured point by point at different frequencies through oscilloscopes and function generators in the past.

The tracking generator function of the spectrum analyzer is used to generate a scanning signal which is transmitted through the DUT to the RF receiver of the spectrum analyzer. By comparing the frequency response of the DUT and the measured response of the short-circuit, the insertion loss of the DUT can be obtained. The frequency response measurement values ​​of other related components can be obtained in the same way.

From the Fourier equation, we can know that in addition to the undistorted resonant wave (sine wave), any waveform besides the fundamental wave also includes high harmonic components, such as the periodic sawtooth wave. When expanded according to the Fourier equation, the corresponding mathematical formula shows an infinite number of harmonics, and the harmonic components can be clearly displayed in the spectrum analyzer.

An oscilloscope cannot measure the distortion of a signal, it can only display the relationship between the signal waveform and time, but a spectrum analyzer can accurately evaluate the harmonic signal and amplitude of the signal from the corresponding harmonic spectrum, and thus evaluate the degree of distortion. [page]

Communication monitoring

Due to regulations on spectrum usage, wireless communications must use high frequencies and send and receive signals via antennas. Using a spectrum analyzer with an antenna, it is easy to detect the strength of the current communication signal and the frequency of the carrier. For example, using a directional antenna, two sets of measuring equipment can find the source of the signal. This is also the main detection technology used by relevant units to crack down on illegal radio waves (such as illegal underground radio stations).

The scanning bandwidth of the spectrum analyzer can be adjusted appropriately as needed, such as reducing or enlarging, and making subtle adjustments to evaluate the interference signal conditions in the tested area. This method can be used as a reference for designing a regional communication station or various mobile communication system base stations. The highest signal amplitude measured by the adjustment amount of the directional antenna can determine the direction of the signal source according to the directionality of the antenna. If it is combined with another set of monitoring devices nearby, the location of the signal source can be obtained from the intersection of the two sets of antenna directions, and the location of the transmitting source can be detected immediately. In this way, the transmitting source can be accurately obtained through more sets of measurements.

Measurement of Cable TV Video Information

Cable television (CATV) transmits video to users' homes via coaxial cables or optical cables. With the development of technology, in order to reduce the construction difficulty of digging roads to bury cables and reduce costs, some manufacturers have proposed to open microwave transmission or transmit signals to users' homes in a spot manner via satellite. Currently, a service provider in North America has launched satellite signals with 150 video channels for users in Northern California. Therefore, cable, microwave and satellite video transmission methods have coexisted and applied in the market, providing viewers with more diversified choices.

The main function of the CATV system is to transmit video programs and data, and to maintain the normal operation of the system, transmit about 100 or more channels of video, and provide two-way interactive services such as timely response to user terminal data retrieval control signals. The CATV system includes a wide variety of video signals, such as voltage and current amplitude, gain, frequency and power, among which gain and power are mostly expressed in logarithmic values. The amplitude and frequency of the RF signal can be measured by general instruments (such as oscilloscopes), and the signal phase is measured by a vector oscilloscope. The so-called vector oscilloscope is an oscilloscope with an extremely stable circular time base, which can be used to check the time delay between two signals. The spectrum analyzer is an indispensable electronic device for CATV signal measurement.

Antenna Characteristics Measurement

In addition to measuring the signal strength amplitude in the air, spectrum analyzers can also measure return loss when used with a bridger. Due to the popularity of mobile phones, there are a large number of base stations in cities. Since the concerns about electromagnetic radiation damage have always troubled users, the measurement of electromagnetic wave strength has gradually attracted everyone's attention. Spectrum analyzers can also measure antenna radiation intensity or electromagnetic intensity in any space.

Use of spectrum analyzer

Whether the measurement can be measured or not depends entirely on the settings of the spectrum analyzer. This includes the settings of the attenuator, frequency range and resolution bandwidth. The settings of the spectrum analyzer include frequency range, resolution and dynamic range. The dynamic range involves the maximum input power, i.e. the burnout power. Gain compression causes errors to occur once the input signal less than 1W exceeds the linear working area. In addition, sensitivity is also the key to whether the spectrum analyzer can measure the input signal.

The parameter frequency range should be observed from two aspects. First, whether the frequency range is set narrow enough to have sufficient frequency resolution, that is, a narrow enough sweep width. Second, whether the frequency range is wide enough to measure the second and third harmonics. When using a spectrum analyzer to measure the harmonic distortion of an amplifier, if the amplifier is 1GHz, its third harmonic is 3GHz, which is the maximum measurable width of the frequency range to be considered. If the spectrum analyzer is 1.8GHz, it cannot be measured. If the spectrum analyzer is 26.5GHz, its third and fourth harmonics can be measured.

Resolution is also a very important parameter setting in the spectrum analyzer. Resolution means that when the power of two frequencies is different, they must be distinguished. The IF bandwidth is set to three different widths. The following is the curve seen when this bandwidth is set. The narrower the IF bandwidth, the higher the resolution, and the wider the IF bandwidth, the lower the resolution. The resolution bandwidth directly affects the ability to identify tiny signals and the measurement results.

This article briefly introduces the application and operation of spectrum analyzers. In many application fields, spectrum analyzers are good helpers for engineers. The optimal state of a spectrum analyzer is determined by many factors and parameters, so it is necessary to consider the whole process rather than pursuing the perfection of a single indicator. Only by analyzing various basic factors and measurement types can a perfect measurement result be achieved.