**Powder Incentive Program To better understand how real-time spectrum analyzers work and understand the valuable measurements they provide, here are a few different examples of how they differ and how they can be used.
This article will mainly introduce the working principles and main differences of swept frequency spectrum analyzers, vector signal analyzers, and real-time spectrum analyzers.
1.1 Swept frequency spectrum analyzer.
The swept spectrum analyzer is a traditional frequency domain measurement instrument, which is a traditional structure of scanning tuned superheterodyne spectrum analyzer, the emergence of swept frequency spectrum analyzer enabled engineers to perform frequency domain measurements decades ago.
A swept spectrum analyzer measures the power as a function of frequency by downconverting the signal of interest and scanning the downconverted signal through an RBW filter. The RBW filter is followed by a geophone, which calculates the amplitude of each frequency point within the selected swept width. Although this method can provide a high dynamic range, the disadvantage is that it can only calculate amplitude data for one frequency point at a time, resulting in a spectrum analyzer that takes a long time to scan over a wide sweep width, in some cases tens of seconds. Therefore, this method is based on the assumption that there is no significant change in the measured signal during multiple sweeps of the spectrum analyzer, i.e., this method requires that the input signal be relatively stable or unchanged. Swept frequency spectrum analyzers were initially constructed as analog devices and then evolved as their applications evolved. Today's swept spectrum analyzers already include a variety of digital elements, such as ADCs, DSPs, and microprocessors, but their scanning methods remain largely unchanged and are still essentially swept spectrum analyzers. For this reason, swept frequency spectrum analyzers are best suited for observing controlled static signals.
If the signal changes rapidly, the swept spectrum analyzer may miss the change in the signal. As shown in Figure 1As shown in 1, an instantaneous spectral event occurs on FB (left) when scanning to look at band FA. By the time the sweep reaches the band FB, the event has disappeared and the swept spectrum analyzer has detected no event (right).
Figure 11. Test principle of swept spectrum analyzer.
1.2 Vector Signal Analyzer.
Traditional swept frequency analysis can only take scalar measurements and provide only information about the frequency and amplitude of the input signal. The analysis of digital modulation signals is to provide frequency information, amplitude information and phase information of the signal at the same time; The addition of phase information compared to traditional swept frequency analysis makes vector signal analysis a tool specifically designed for digital modulation analysis. Figure 12 is a simplified diagram of the structure of a typical vector signal analyzer.
Figure 12.1. Block diagram of a typical vector signal analyzer structure.
The vector signal analyzer is to digitally collect the measured signal through frequency conversion processing, and obtain the amplitude information and phase information of the signal through calculation. However, the signal processing of most vector signal analyzers is done by software, and the processing speed and ability of the software are very slow compared with the high-speed signal ADC acquisition, which is bound to lead to a lot of signal data needs to be discarded, resulting in a dead zone (gap) of signal processing, which leads to an incomplete description of the characteristics of the change signal in the time domain, as shown in Figure 12.2 shown.
Figure 12.2. The spectrum test principle of the vector signal analyzer.
Vector signal analyzers are mainly used to measure the error parameters of stable modulated signals, such as the error vector magnitude (EVM), phase error or frequency error of digital modulated signals, and provide constellation diagrams and other displays.
1.3. Real-time spectrum analyzer.
Real-time spectrum analyzers are used to solve the parametric measurement of time-varying signals, and the basic concept of real-time spectrum analysis is the ability to quickly acquire and capture a variety of transient signals, seamlessly capture the signals into memory, and analyze the signals in multiple domains. Figure 13.1 is a typical block diagram of a real-time spectrum analyzer, as you can see, the basic structure of a real-time spectrum analyzer and a vector signal analyzer is similar, both are based on signal conversion and ADC sampling, and then the signal parameters are obtained through digital signal processing DSP. Most vector signal analyzers do the signal processing by software, which is slow compared to high-speed signal ADC acquisition. The signal processing part of the real-time spectrum analyzer is completed by the FPGA in the hardware mode, which greatly improves the processing speed and reduces the processing delay. The time saved can be used to complete multi-signal judgment, triggering and other processing functions. A real-time spectrum analyzer can be thought of as a "hardware-based, high-speed processing version of a vector signal analyzer".
Figure 13.1Block diagram of a typical real-time spectrum analyzer.
Figure 13.1. The block diagram of the real-time spectrum analyzer is illustrated, and the tunable RF front-end composed of input attenuator, low-pass filter, local oscillator, and downconverter is used to downconvert the input signal to a fixed intermediate frequency (IF), and the frequency of the fixed intermediate frequency is related to the maximum real-time bandwidth of the instrument. The IF signal digitizes the signal through the ADC, and then transmits it to the DSP for processing, and when the time length of the signal processing is less than the acquisition length of the signal, the continuous acquisition and continuous processing and display of the signal can be completed, which is the so-called real-time processing. Real-time spectrum analyzers increase processing speed and add real-time triggering, seamless signal capture, and time-correlated multi-domain analysis.
Figure 13.2 is an intuitive description of the spectrum processing process completed by the real-time spectrum analyzer, the real-time spectrum analyzer uses FFT to complete the spectrum test, so the real-time spectrum analysis or processing is completed within a certain frequency bandwidth, and the real-time analysis bandwidth is an important technical indicator of the real-time spectrum analyzer.
When the real-time spectrum analyzer processes the measured signal, it is easy to store time-continuous samples in memory through digital acquisition and real-time transmission, and the structure of the real-time spectrum analyzer can seamlessly capture the input signal without time intervals, which is a technical function that traditional swept spectrum analyzers do not have.
In the practical application field, the development of technology has promoted the integration of these spectrum processing technologies. Today's state-of-the-art signal analyzers have all of these signal processing functions, i.e., swept spectrum analysis, vector signal analysis, and real-time spectrum analysis, which can be implemented through different options or applications. The instrument needs to be configured according to the demand, ** and other factors. In the application, different signal processing methods are selected according to different signals under test, and Table 1 lists the technical characteristics and applicable objects of various signal spectrum testing technologies.
a) Description of the processing process of the real-time spectrum analyzer.
b) Real-time processing.
c) Non-real-time processing.
Figure 13.2. Real-time processing and non-real-time processing.
When the real-time spectrum analyzer processes the measured signal, it is easy to store time-continuous samples in memory through digital acquisition and real-time transmission, and the structure of the real-time spectrum analyzer can seamlessly capture the input signal without time intervals, which is a technical function that traditional swept spectrum analyzers do not have.
In the practical application field, the development of technology has promoted the integration of these spectrum processing technologies. Today's state-of-the-art signal analyzers have all of these signal processing functions, i.e., swept spectrum analysis, vector signal analysis, and real-time spectrum analysis, which can be implemented through different options or applications. The instrument needs to be configured according to the demand, ** and other factors. In the application, different signal processing methods are selected according to different signals under test, and Table 1 lists the technical characteristics and applicable objects of various signal spectrum testing technologies.
Table 1 Descriptions of various signal spectrum testing techniques.
1.4. The working principle of a real-time spectrum analyzer.
Pushang SP900 series signal analyzer not only supports conventional spectrum measurement functions, but also supports vector signal analysis; In particular, the real-time spectrum analysis function supports a maximum bandwidth of 510MHz and a minimum POI of 351us。The real-time spectrum test diagram is as follows:
At the same time, the SP900's existing measurement program library supports more than 25 kinds of measurement application software, covering a variety of complex modulation signals: 2G, 3G, 4G, 5G NR, and cellular communication. Zigbee, Pulse, and EMI, among others. Pair with custom options to meet your testing needs.