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https://github.com/gnss-sdr/gnss-sdr
synced 2025-01-16 04:05:46 +00:00
Add a simple CN0 smoother
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@ -439,6 +439,7 @@ dll_pll_veml_tracking::dll_pll_veml_tracking(const Dll_Pll_Conf &conf_) : gr::bl
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d_carrier_lock_fail_counter = 0;
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d_carrier_lock_threshold = trk_parameters.carrier_lock_th;
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d_Prompt_Data = static_cast<gr_complex *>(volk_gnsssdr_malloc(sizeof(gr_complex), volk_gnsssdr_get_alignment()));
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d_cn0_smoother = Exponential_Smoother();
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d_acquisition_gnss_synchro = nullptr;
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d_channel = 0;
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@ -848,9 +849,12 @@ bool dll_pll_veml_tracking::cn0_and_tracking_lock_status(double coh_integration_
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d_cn0_estimation_counter++;
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return true;
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}
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d_cn0_estimation_counter = 0;
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d_Prompt_buffer[d_cn0_estimation_counter % trk_parameters.cn0_samples] = d_P_accu;
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d_cn0_estimation_counter++;
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// Code lock indicator
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d_CN0_SNV_dB_Hz = cn0_svn_estimator(d_Prompt_buffer, trk_parameters.cn0_samples, coh_integration_time_s);
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double d_CN0_SNV_dB_Hz_raw = cn0_svn_estimator(d_Prompt_buffer, trk_parameters.cn0_samples, coh_integration_time_s);
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d_CN0_SNV_dB_Hz = d_cn0_smoother.smooth(d_CN0_SNV_dB_Hz_raw);
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// Carrier lock indicator
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d_carrier_lock_test = carrier_lock_detector(d_Prompt_buffer, trk_parameters.cn0_samples);
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// Loss of lock detection
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@ -1593,7 +1597,7 @@ int dll_pll_veml_tracking::general_work(int noutput_items __attribute__((unused)
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DLOG(INFO) << "Number of samples between Acquisition and Tracking = " << acq_trk_diff_samples << " ( " << acq_trk_diff_seconds << " s)";
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DLOG(INFO) << "PULL-IN Doppler [Hz] = " << d_carrier_doppler_hz
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<< ". PULL-IN Code Phase [samples] = " << d_acq_code_phase_samples;
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d_cn0_smoother.reset();
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consume_each(samples_offset); // shift input to perform alignment with local replica
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return 0;
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}
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@ -34,6 +34,7 @@
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#include "cpu_multicorrelator_real_codes.h"
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#include "dll_pll_conf.h"
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#include "exponential_smoother.h"
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#include "tracking_FLL_PLL_filter.h" // for PLL/FLL filter
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#include "tracking_loop_filter.h" // for DLL filter
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#include <boost/circular_buffer.hpp>
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@ -197,6 +198,7 @@ private:
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double d_carrier_lock_threshold;
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boost::circular_buffer<gr_complex> d_Prompt_circular_buffer;
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gr_complex *d_Prompt_buffer;
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Exponential_Smoother d_cn0_smoother;
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// file dump
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std::ofstream d_dump_file;
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@ -43,6 +43,7 @@ set(TRACKING_LIB_SOURCES
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tracking_loop_filter.cc
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dll_pll_conf.cc
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bayesian_estimation.cc
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exponential_smoother.cc
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)
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set(TRACKING_LIB_HEADERS
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@ -59,6 +60,7 @@ set(TRACKING_LIB_HEADERS
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tracking_loop_filter.h
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dll_pll_conf.h
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bayesian_estimation.h
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exponential_smoother.h
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)
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if(ENABLE_FPGA)
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139
src/algorithms/tracking/libs/exponential_smoother.cc
Normal file
139
src/algorithms/tracking/libs/exponential_smoother.cc
Normal file
@ -0,0 +1,139 @@
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/*!
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* \file exponential_smoother.cc
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* \brief Class that implements an exponential smoother
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* \authors Carles Fernandez, 2019 cfernandez@cttc.es
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*
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* Class that implements a first-order exponential smoother.
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*
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* -------------------------------------------------------------------------
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*
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* Copyright (C) 2010-2019 (see AUTHORS file for a list of contributors)
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*
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* GNSS-SDR is a software defined Global Navigation
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* Satellite Systems receiver
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*
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* This file is part of GNSS-SDR.
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*
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* GNSS-SDR 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, either version 3 of the License, or
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* (at your option) any later version.
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*
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* GNSS-SDR 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 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 GNSS-SDR. If not, see <https://www.gnu.org/licenses/>.
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*
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* -------------------------------------------------------------------------
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*/
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#include "exponential_smoother.h"
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#include <iostream> ///////////////
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#include <iterator>
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#include <numeric>
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Exponential_Smoother::Exponential_Smoother()
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{
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alpha_ = 0.001;
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old_value_ = 0.0;
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one_minus_alpha_ = 1.0 - alpha_;
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samples_for_initialization_ = 500;
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initializing_ = true;
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init_counter_ = 0;
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min_value_ = 25;
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offset_ = 9.0;
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init_buffer_.reserve(samples_for_initialization_);
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}
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Exponential_Smoother::~Exponential_Smoother() = default;
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void Exponential_Smoother::set_alpha(float alpha)
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{
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alpha_ = alpha;
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if (alpha_ < 0)
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{
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alpha_ = 0;
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}
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if (alpha_ > 1)
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{
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alpha_ = 1;
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}
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one_minus_alpha_ = 1.0 - alpha_;
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}
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void Exponential_Smoother::set_offset(float offset)
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{
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offset_ = offset;
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}
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void Exponential_Smoother::set_samples_for_initialization(int num_samples)
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{
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int ns = num_samples;
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if (ns <= 0)
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{
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ns = 1;
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}
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samples_for_initialization_ = num_samples;
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init_buffer_.reserve(samples_for_initialization_);
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}
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void Exponential_Smoother::reset()
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{
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initializing_ = true;
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init_counter_ = 0;
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init_buffer_.clear();
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}
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void Exponential_Smoother::set_min_value(float value)
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{
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min_value_ = value;
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}
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double Exponential_Smoother::smooth(double raw)
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{
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float raw_f = static_cast<float>(raw);
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double smooth_d = static_cast<double>((this)->smooth(raw_f));
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return smooth_d;
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}
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float Exponential_Smoother::smooth(float raw)
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{
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float smoothed_value;
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if (initializing_ == true)
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{
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init_counter_++;
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smoothed_value = raw;
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init_buffer_.push_back(smoothed_value);
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if (init_counter_ == samples_for_initialization_)
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{
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old_value_ = std::accumulate(std::begin(init_buffer_), std::end(init_buffer_), 0.0) / static_cast<float>(init_buffer_.size());
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if (old_value_ < (min_value_ + offset_))
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{
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// flush buffer and start again
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init_counter_ = 0;
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init_buffer_.clear();
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}
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else
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{
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initializing_ = false;
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}
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}
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}
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else
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{
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smoothed_value = alpha_ * raw + one_minus_alpha_ * old_value_;
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old_value_ = smoothed_value;
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}
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return smoothed_value;
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}
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71
src/algorithms/tracking/libs/exponential_smoother.h
Normal file
71
src/algorithms/tracking/libs/exponential_smoother.h
Normal file
@ -0,0 +1,71 @@
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/*!
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* \file exponential_smoother.h
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* \brief Class that implements an exponential smoother
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* \authors Carles Fernandez, 2019 cfernandez@cttc.es
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*
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* Class that implements a first-order exponential smoother.
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*
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* -------------------------------------------------------------------------
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*
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* Copyright (C) 2010-2019 (see AUTHORS file for a list of contributors)
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*
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* GNSS-SDR is a software defined Global Navigation
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* Satellite Systems receiver
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*
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* This file is part of GNSS-SDR.
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*
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* GNSS-SDR 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, either version 3 of the License, or
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* (at your option) any later version.
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*
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* GNSS-SDR 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 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 GNSS-SDR. If not, see <https://www.gnu.org/licenses/>.
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*
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* -------------------------------------------------------------------------
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*/
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#ifndef GNSS_SDR_EXPONENTIAL_SMOOTHER_H_
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#define GNSS_SDR_EXPONENTIAL_SMOOTHER_H_
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#include <vector>
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/*! \brief
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* Class that implements a first-order exponential smoother.
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*
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* smoothed_value[k] = alpha * raw + (1-alpha) * smoothed_value[k-1]
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*
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* The length of the initialization can be controlled with
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* set_samples_for_initialization(int num_samples)
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*/
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class Exponential_Smoother
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{
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public:
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Exponential_Smoother(); //!< Constructor
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~Exponential_Smoother(); //!< Destructor
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void set_alpha(float alpha); //!< 0 < alpha < 1. The higher, the most responsive, but more variance. Default value: 0.0001
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void set_samples_for_initialization(int num_samples); //!< Number of samples averaged for initialization. Default value:
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void reset();
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void set_min_value(float value);
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void set_offset(float offset);
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float smooth(float raw);
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double smooth(double raw);
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private:
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float alpha_; // takes value 0.0001 if not set
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int samples_for_initialization_;
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float one_minus_alpha_;
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float old_value_;
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float min_value_;
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float offset_;
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bool initializing_;
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int init_counter_;
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std::vector<float> init_buffer_;
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};
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#endif // GNSS_SDR_EXPONENTIAL_SMOOTHER_H_
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