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Introduction to the Density View on a Real Time Spectrum Analyzer

Posted by gm77 25/06/2021 0 Comment(s) 272 Test & Measurement,

What is the density?



Fig. 1 Density view
 

The density is defined as the number of times a frequency and amplitude point is hit during an acquisition interval. X-axis represents frequency, Y-axis represents amplitude, Z-axis represents number of hits, and T-axis represents time. This view displays four-dimensional data on a two-dimensional display, using color to represent Z-axis and brightness to represent T-axis.

As shown in Figure 1, the density view will also display a white trace. This trace shows the real time spectrum for the latest acquisition interval. When using positive peak, negative peak or average detectors, the white trace obtains detector data from all data within the acquisition interval. When using the Sample detector, the last FFT was adopted. In order to display the signal status over a longer time range, multiple density view can be displayed on the screen.
The latest density view is displayed with the highest brightness. The longer the time from the latest density view, the lower the brightness of the density view. Such display of the brightness is generally called persistence view.
 

Discover the detailed characteristics of the measured signal


The density view is particularly suitable for analyzing signal features that are difficult to detect by traditional methods. By comparing the monochromatic spectrum display of the traditional spectrum analyzer with the density view of the RSA real-time spectrum analyzer, we illustrate the difference between them.
 



Fig. 2 Normal view(left), Density view (right)
 

Fig. 2 shows the analysis and display of the same WLAN signal by the traditional sweep monochromatic spectrum and density spectrum. We can clearly observe that the density mode can clearly display the upstream and downstream content of WLAN signal, while the traditional spectrum analyzer can only display the peak amplitude of the signal using a monochromatic trace. This is because the density view uses the color temperature technology, which uses colors to represent the frequency and time of different signals.
 

  • First of all, the number of signal hits is represented by the color depth. Low hits are
    represented in lighter color, and high hits are represented in darker color.
  • Secondly, the time information of the signal is displayed by adjusting the color shade.
    The newly appeared signal is displayed with the highest brightness. The longer the
    distance from the current time, the lower the brightness of the signal.


In contrast, because of the principle of "power accumulation", the traditional scanning spectrum analyzers can only display the highest energy signal in the maximum holding trace and cannot distinguish whether there are other signals on the same frequency point or frequency band.
 

Find hidden signals


Density mode is very effective for detecting instantaneous signals that are hard to find, or for finding time-varying small energy signals that are hidden beneath the spectrum of other signals.
 



Fig. 3 Hidden signals found in density mode
 

Usually, the small transient signals hidden beneath larger signals are hard to detect, but they will have a serious impact on the quality and safety of the signal. With the advent of real-time spectrum analyzer, even if the small signal appears irregularly in time and the signal duration is very short, using density view, it can also be displayed on the screen, "leaving a trace", which provides the possibility for further signal analysis and intervention.
 

Resolve co-frequency signals


When there are multiple signals in a frequency band and overlap each other, traditional analyzers can hardly view these signals separately. The display usually only shows the superposition of the signal energy at each frequency point.

In Figure 4, at the frequency band of 2.4GHz, there are WLAN signals, Bluetooth transmission signals and multiple signals with low repetition rates and wide frequency bands covering the whole frequency band. With traditional monochromatic sweep spectrum, when there are many different signals in the same frequency band, it is difficult to see which signals exist, or even to distinguish different signals at all. Using density view, the whole problem can be easily solved.
 



Fig. 4 Resolve co-frequency signals in the density view
 

When two time-varying signals overlap, the density view can simply display different signals. In the figure above, we can easily distinguish multiple overlapping signals on the same channel. The color of the signal tells us the frequency of each signal, and the brightness of the signal tells us the time information of each signal.

In addition, we can easily analyze that noise-like wideband signals with low occurrence interfere with all other signals, and it is easy to see on the display which signals are stronger and which are weaker than the interference signals.
 

Observe the crowded spectrum

 



Fig. 5 Observe the crowded spectrum in the density view
 

 

Fig. 5 is an example of time-sharing displays of some dynamically changing signals, transient abrupt signals, and multiple signals within the same frequency range. Without effectively viewing all of these signals, we may not know whether they are working efficiently performing time-sharing or whether they are causing serious interference with each other.

The density view can not only help us to see the time-varying RF signals that could not be displayed separately or even at all, but also can accurately analyze the specific information contained in the signal. Even when signals are completely overlapped, the density view can still distinguish and reveal the properties of multiple time-varying signals, and clearly know its amplitude and frequency. This is impossible in the traditional monochrome display.
 

Conclusion


The density view demonstrated above is just a small feature of the RIGOL RSA series realtime spectrum analyzer. Let's explore more gameplay of the real-time spectrum analyzer!
 

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