mirror of
https://github.com/f4exb/sdrangel.git
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786640ee1f
- Run CTCSS filter with reduced rate to much detection - Convert tabs to spaces to be consistent in the file - Fix AF squelch threshold setting after changing SR
275 lines
6.8 KiB
C++
275 lines
6.8 KiB
C++
///////////////////////////////////////////////////////////////////////////////////
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// Copyright (C) 2015 Edouard Griffiths, F4EXB. //
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// //
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// This program is free software; you can redistribute it and/or modify //
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// it under the terms of the GNU General Public License as published by //
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// the Free Software Foundation as version 3 of the License, or //
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// (at your option) any later version. //
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// //
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// This program is distributed in the hope that it will be useful, //
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// but WITHOUT ANY WARRANTY; without even the implied warranty of //
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// MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the //
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// GNU General Public License V3 for more details. //
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// //
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// You should have received a copy of the GNU General Public License //
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// along with this program. If not, see <http://www.gnu.org/licenses/>. //
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///////////////////////////////////////////////////////////////////////////////////
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#include <cmath>
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#include "dsp/afsquelch.h"
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AFSquelch::AFSquelch() :
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m_nbAvg(128),
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m_N(24),
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m_sampleRate(48000),
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m_samplesProcessed(0),
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m_samplesAvgProcessed(0),
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m_maxPowerIndex(0),
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m_nTones(2),
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m_samplesAttack(0),
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m_attackCount(0),
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m_samplesDecay(0),
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m_decayCount(0),
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m_squelchCount(0),
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m_isOpen(false),
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m_threshold(0.0)
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{
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m_k = new double[m_nTones];
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m_coef = new double[m_nTones];
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m_toneSet = new double[m_nTones];
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m_u0 = new double[m_nTones];
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m_u1 = new double[m_nTones];
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m_power = new double[m_nTones];
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m_movingAverages.resize(m_nTones, MovingAverage<double>(m_nbAvg, 0.0f));
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for (unsigned int j = 0; j < m_nTones; ++j)
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{
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m_toneSet[j] = j == 0 ? 1000.0 : 6000.0;
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m_k[j] = ((double)m_N * m_toneSet[j]) / (double) m_sampleRate;
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m_coef[j] = 2.0 * cos((2.0 * M_PI * m_toneSet[j])/(double) m_sampleRate);
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m_u0[j] = 0.0;
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m_u1[j] = 0.0;
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m_power[j] = 0.0;
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m_movingAverages[j].fill(0.0);
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}
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}
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AFSquelch::~AFSquelch()
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{
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delete[] m_k;
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delete[] m_coef;
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delete[] m_toneSet;
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delete[] m_u0;
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delete[] m_u1;
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delete[] m_power;
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}
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void AFSquelch::setCoefficients(
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unsigned int N,
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unsigned int nbAvg,
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unsigned int sampleRate,
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unsigned int samplesAttack,
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unsigned int samplesDecay,
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const double *tones)
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{
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m_N = N; // save the basic parameters for use during analysis
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m_nbAvg = nbAvg;
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m_sampleRate = sampleRate;
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m_samplesAttack = samplesAttack;
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m_samplesDecay = samplesDecay;
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m_movingAverages.resize(m_nTones, MovingAverage<double>(m_nbAvg, 0.0));
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m_samplesProcessed = 0;
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m_samplesAvgProcessed = 0;
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m_maxPowerIndex = 0;
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m_attackCount = 0;
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m_decayCount = 0;
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m_squelchCount = 0;
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m_isOpen = false;
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m_threshold = 0.0;
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// for each of the frequencies (tones) of interest calculate
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// k and the associated filter coefficient as per the Goertzel
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// algorithm. Note: we are using a real value (as opposed to
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// an integer as described in some references. k is retained
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// for later display. The tone set is specified in the
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// constructor. Notice that the resulting coefficients are
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// independent of N.
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for (unsigned int j = 0; j < m_nTones; ++j)
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{
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m_toneSet[j] = tones[j] < ((double) m_sampleRate) * 0.4 ? tones[j] : ((double) m_sampleRate) * 0.4; // guarantee 80% Nyquist rate
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m_k[j] = ((double)m_N * m_toneSet[j]) / (double)m_sampleRate;
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m_coef[j] = 2.0 * cos((2.0 * M_PI * m_toneSet[j])/(double)m_sampleRate);
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m_u0[j] = 0.0;
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m_u1[j] = 0.0;
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m_power[j] = 0.0;
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m_movingAverages[j].fill(0.0);
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}
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}
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// Analyze an input signal
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bool AFSquelch::analyze(double sample)
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{
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feedback(sample); // Goertzel feedback
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if (m_samplesProcessed < m_N) // completed a block of N
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{
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m_samplesProcessed++;
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return false;
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}
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else
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{
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feedForward(); // calculate the power at each tone
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m_samplesProcessed = 0;
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if (m_samplesAvgProcessed < m_nbAvg)
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{
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m_samplesAvgProcessed++;
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return false;
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}
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else
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{
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return true; // have a result
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}
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}
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}
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void AFSquelch::feedback(double in)
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{
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double t;
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// feedback for each tone
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for (unsigned int j = 0; j < m_nTones; ++j)
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{
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t = m_u0[j];
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m_u0[j] = in + (m_coef[j] * m_u0[j]) - m_u1[j];
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m_u1[j] = t;
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}
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}
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void AFSquelch::feedForward()
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{
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for (unsigned int j = 0; j < m_nTones; ++j)
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{
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m_power[j] = (m_u0[j] * m_u0[j]) + (m_u1[j] * m_u1[j]) - (m_coef[j] * m_u0[j] * m_u1[j]);
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m_movingAverages[j].feed(m_power[j]);
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m_u0[j] = 0.0;
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m_u1[j] = 0.0; // reset for next block.
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}
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evaluate();
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}
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void AFSquelch::reset()
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{
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for (unsigned int j = 0; j < m_nTones; ++j)
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{
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m_u0[j] = 0.0;
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m_u1[j] = 0.0;
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m_power[j] = 0.0;
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m_movingAverages[j].fill(0.0);
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}
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m_samplesProcessed = 0;
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m_maxPowerIndex = 0;
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m_isOpen = false;
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}
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bool AFSquelch::evaluate()
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{
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double maxPower = 0.0;
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double minPower;
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int minIndex = 0, maxIndex = 0;
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for (unsigned int j = 0; j < m_nTones; ++j)
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{
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if (m_movingAverages[j].sum() > maxPower)
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{
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maxPower = m_movingAverages[j].sum();
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maxIndex = j;
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}
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}
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if (maxPower == 0.0)
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{
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return m_isOpen;
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}
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minPower = maxPower;
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for (unsigned int j = 0; j < m_nTones; ++j)
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{
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if (m_movingAverages[j].sum() < minPower) {
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minPower = m_movingAverages[j].sum();
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minIndex = j;
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}
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}
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// m_isOpen = ((minPower/maxPower < m_threshold) && (minIndex > maxIndex));
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if ((minPower/maxPower < m_threshold) && (minIndex > maxIndex)) // open condition
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{
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if (m_squelchCount < m_samplesAttack + m_samplesDecay)
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{
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m_squelchCount++;
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}
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}
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else
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{
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if (m_squelchCount > m_samplesAttack)
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{
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m_squelchCount--;
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}
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else
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{
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m_squelchCount = 0;
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}
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}
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m_isOpen = (m_squelchCount >= m_samplesAttack) ;
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// if ((minPower/maxPower < m_threshold) && (minIndex > maxIndex)) // open condition
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// {
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// if ((m_samplesAttack > 0) && (m_attackCount < m_samplesAttack))
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// {
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// m_isOpen = false;
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// m_attackCount++;
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// }
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// else
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// {
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// m_isOpen = true;
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// m_decayCount = 0;
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// }
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// }
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// else
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// {
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// if ((m_samplesDecay > 0) && (m_decayCount < m_samplesDecay))
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// {
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// m_isOpen = true;
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// m_decayCount++;
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// }
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// else
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// {
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// m_isOpen = false;
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// m_attackCount = 0;
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// }
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// }
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return m_isOpen;
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}
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void AFSquelch::setThreshold(double threshold)
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{
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qDebug("AFSquelch::setThreshold: threshold: %f", threshold);
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m_threshold = threshold;
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reset();
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}
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