#!/usr/bin/env python # This tool uses gnuradio to generate FIR filter taps # that can be used for the FIRFilter function in # ODR-DabMod # # Usage: # 1) adapt the filter settings below # 2) Call this script and redirect the output of this script into a file # # Requires: # A recent gnuradio version (3.7) # # # The MIT License (MIT) # # Copyright (c) 2013 Matthias P. Braendli # http://mpb.li # # Permission is hereby granted, free of charge, to any person obtaining a copy # of this software and associated documentation files (the "Software"), to deal # in the Software without restriction, including without limitation the rights # to use, copy, modify, merge, publish, distribute, sublicense, and/or sell # copies of the Software, and to permit persons to whom the Software is # furnished to do so, subject to the following conditions: # # The above copyright notice and this permission notice shall be included in all # copies or substantial portions of the Software. # # THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR # IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY, # FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE # AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER # LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM, # OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE # SOFTWARE. import gnuradio from gnuradio import digital # From documentation at # http://gnuradio.org/doc/doxygen/classgr_1_1filter_1_1firdes.html # use "window method" to design a low-pass FIR filter # # gain: overall gain of filter (typically 1.0) # sampling_freq: sampling freq (Hz) # cutoff_freq: center of transition band (Hz) # transition_width: width of transition band (Hz). # The normalized width of the transition band is what sets the number of taps required. Narrow --> more taps # window_type: What kind of window to use. Determines maximum attenuation and passband ripple. # beta: parameter for Kaiser window gain = 1 sampling_freq = 2.048e6 cutoff = 810e3 transition_width = 250e3 # Generate filter taps and print them out taps = digital.filter.firdes.low_pass(gain, sampling_freq, cutoff, transition_width) # hamming window print(len(taps)) for t in taps: print(t)