plutosdr-fft-log is a tool for logging and playing back arbitrarily large portions of the RF spectrum. it can also identify peaks based on a handful of input parameters and log them to console
plutosdr-fft-log uses the gnuradio python library, please refer to the GNU Radio and IIO Device page for more information
scanner.py is designed to scan frequency ranges and log them efficiently. it is configurable via several command-line arguments:
--dir: directory to save FFT files (default:./fft)--bandwidth: bandwidth per FFT in MHz, will be automatically adjusted if it doesn't fit evenly between start and end frequencies (default: 10, max 52)--start: start frequency in MHz (default: 90)--end: end frequency in MHz (default: 150)--fftsize: FFT size, must be a power of 2 (default: 1024)--frames: number of FFT frames to capture each sample period (default: 2)--cutoff: cutoff frequency for peaks. if not present, defaults to 2 standard deviations above the mean--width: minimum width for peak detection (default: 5)--distance: minimum distance between peaks (default: 30)
there is no
--samplerateargument as the plutosdr uses quadrature sampling -- it is capable of fulfilling the minimum nyquist sampling rate for its entire RF bandwidth
scanner.py continuously scans a specified frequency range and logs the FFT results to .bin files. each log file contains data for an arbitrary large portion of the spectrum, allowing continuous spectrum monitoring:
- FFT computations are performed for chunks of the spectrum defined by the
start,end,bandwidth,fftsize, andframes - the resulting FFT data is logged to binary files in the specified directory. each file's name contains necessary metadata for later replaying the data:
example filename: 80_280_50_4096_8_1715568957.bin, which encodes the start and end frequencies, the bandwidth, FFT size, number of frames, and a timestamp.
replay.pl plays back FFT log files generated by scanner.py, printing detected peaks to the console:
--dir: directory containing FFT log files--cutoff: cutoff frequency for peaks, defaults to 2 standard deviations above the mean if not specified--width: minimum width for peak detection (default: 5)--distance: minimum distance between peaks (default: 30)--sleep: sleep time in seconds between processing each file to simulate real-time playback (default: 1.0)
replay.pl reads FFT log files from the specified directory, using the metadata encoded in each file's name to properly interpret the data:
- it extracts parameters like start and end frequencies, bandwidth, FFT size, and number of frames directly from the filename
- the tool applies peak detection algorithms to identify significant peaks within each FFT data set, based on the user-defined parameters for cutoff frequency, width, and distance
- detected peaks are printed to the console, allowing users to analyze frequency spikes over time
the information about the peaks present is printed to console in both scripts:
Peak at 88.09 MHz, height -21.09
Peak at 90.91 MHz, height -33.05
Peak at 93.09 MHz, height -30.46
Peak at 93.76 MHz, height -25.09
Peak at 94.53 MHz, height -18.05
Peak at 95.30 MHz, height -35.39
Peak at 96.10 MHz, height -27.13
Peak at 96.92 MHz, height -28.99
these are calculated based on the FFT .bin files, so running replay.py with different parameters will result in different peaks being displayed