Video Filtering or Averaging of Spectrum Analyzer

Chapter Video Filtering or Averaging

Guide to Spectrum and Signal Analysis
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Guide to Spectrum and Signal Analysis

  • | 13When comparing spectrum analyzer specifications it is important that sensitivity is compared for equal bandwidths since noise varies with bandwidth.An alternative measure of sensitivity is the noise factor FN:where S = Signal and N = NoiseSince the noise factor is a dimensionless figure of merit we can derive the noise figure as:Using the equation PN = kTB it is possible to calculate the theoretical value of absolute sensitivity for a given bandwidth. For example, if a spectrum analyzer generates no noise products at a temperature of 17 degrees Celsius, referred to a 1Hz bandwidth, then:absolute sensitivity = 1.38 x 10–23 x 290= 4x1021 W/Hz= –174dBm/HzTo determine the noise figure of a typical spectrum analyzer where the average noise floor is specified as 120 dBm referred to a 300 Hz bandwidth:–120 dBm = –174 dBm/Hz + 10 log 300 + F (dB) F (dB) = –120 + 174 –24.8Noise Figure = 29.2 dBVideo Filtering or AveragingVery low level signals can be difficult to distinguish from the average internal noise level of many spectrum analyzers. Since analyzers display signal plus noise, some form of averaging or filtering is required to assist the visual detection process. As mentioned earlier, a video filter is a low pass, post detection filter that averages the internal noise of the analyzer.Because spectrum analyzers measure signal plus noise, the minimum signal power that can be displayed is the same as the average noise power of the analyzer. From this statement it would appear that the signal would be lost in the analyzer noise but:if signal power = average noise powerthen by definition, the minimum signal power that can be displayed will be:WhereS = signal powerN = average noise powerFN = (S/N)IN / (S/N)OUTF = 10 log (FN) dBFN = (S/N)IN / (S/N)OUTF = 10 log (FN) dB= 2 S + NN