Since people have realized wireless communication, wireless communication technology has developed rapidly. Today, mobile network, WiFi, Bluetooth, RFID and other technologies are flourishing, and the RF spectrum has become more and more crowded. Sometimes different types of RF signals interfere with each other. In the face of fast and randomly changing signals, traditional scanning spectrum analyzers can no longer meet the real-time requirements in scenarios where real-time spectrum needs to be observed.
Aiming at the higher requirements for testing equipment of widely used wireless technologies such as frequency hopping and spread spectrum, this article briefly introduces the difference between real-time spectrum analyzers and traditional scanning spectrum analyzers in signal processing.
1. Traditional scanning spectrum analyzer
A traditional scanning spectrum analyzer (superheterodyne spectrum analyzer) will scan to the stop frequency (far right of the screen) according to the set start frequency (the leftmost of the screen). The scan time is related to Span settings, RBW settings, etc.: the larger the Span, the smaller the RBW, and the more time it takes to scan once. Under complex environment conditions, it is difficult to obtain frequency domain information of rapidly changing signals well.
We use a swept spectrum analyzer to analyze transient signals such as Bluetooth signals. It can be seen from Figure 1 that the result obtained by scanning a Span is basically only one signal, but the measurement result is not ideal. The spectrum analyzer is scanning the signal at the frequency point where the red dot is located in the figure. If the Bluetooth signal appears at other frequency points at this time, the scanning spectrum analyzer cannot scan the signal. In order to capture the complete Bluetooth signal, we can try to use the Max Hold function to record the signal that has appeared (as shown in Figure 2 below), but after using the Max Hold function for a period of time, some signal details will gradually be covered, and finally it is even unclear a complete transient signal.
Figure 1 Bluetooth signals scanned by the scanning spectrum analyzer in different time periods
Figure 2 Recording signals using the Max Hold function
It can be seen that unless the signal to be tested happens to appear at the scanned frequency points at the same time, the signal to be tested cannot be scanned, and the probability of omission is very high. It is difficult for a scanning spectrum analyzer to capture some transient signals or abnormal signals that change quickly. Even if the Max Hold function is used to record the scanned signals during this period, some signal details will be covered. Compared with the sweep results of real-time spectrum analyzers (Figure 3 below), the performance of swept spectrum analyzers in capturing transient signals is not satisfactory.
Traditional swept spectrum analyzers can also use the Swept FFT mode to process signals. However, it is necessary to collect and process a section of signal first, and then collect the next section of signal after processing this section of signal. This mode will have a dead zone, and it is difficult to completely collect transient signals. Therefore, it is difficult for traditional analyzers to obtain the frequency domain information of transient signals well.
2. Real-time Spectrum Analyzer
Compared with the traditional scanning spectrum analyzer, the FFT output processing method of the real-time spectrum analyzer is different. The FFT adopted by the traditional spectrum analyzer: acquisition signal-processing-display. When the spectrum analyzer is processing the data, no signal can be collected during this period, and the probability of signal omission is very high.
The FFT of the real-time spectrum analyzer adopts seamless processing. While collecting data, a large number of FFT operations are performed in the background. The speed of data processing is much faster than the speed of data collection, and the entire Span signal can be processed quickly at one time. When the processing speed is greater than the acquisition speed, it can be guaranteed that the spectrum analyzer can also process the collected signals while collecting signals all the time, and there is no problem of missing signals.
It should be noted that the real-time spectrum analyzer can not achieve seamless processing under all settings. When both Span and RBW are set relatively large, the data acquisition time may be shorter than the data processing time. In this case The real-time spectrum analyzer cannot work in seamless processing mode.
In order to avoid this situation, the real-time spectrum analyzer will use overlap processing to restore the transient signal as much as possible through multiple FFT analysis. The real-time spectrum analyzer also has a more important parameter POI, that is, the probability of interception. Generally, the minimum duration of 100% POI is used to characterize the stable capture and measurement capabilities of the spectrum analyzer for signals. When the duration of the signal is greater than the minimum duration, the spectrum analyzer can capture 100% of the signal. Conversely, when the signal duration does not meet the POI conditions, the spectrum analyzer cannot guarantee the accuracy of the measurement results.
Compared with the traditional scanning spectrum analyzer, the real-time spectrum analyzer has more significant advantages in transient signal measurement. In Figure 3 below, the real-time spectrum analyzer is used to measure the Bluetooth signal, and it is found that there is also a suspected wifi signal interference
Figure 3 Real-time spectrum analyzer measures Bluetooth signal
Compared with traditional spectrum analyzers, real-time spectrum analyzers have greater advantages in capturing transient signals, which can help users better analyze sporadic or random signals.
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