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gnss-sdr/src/algorithms/tracking/libs/tracking_loop_filter.cc

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/*!
* \file tracking_loop_filter.cc
* \brief Generic 1st to 3rd order loop filter implementation
* \author Cillian O'Driscoll, 2015. cillian.odriscoll(at)gmail.com
*
* Class implementing a generic 1st, 2nd or 3rd order loop filter. Based
* on the bilinear transform of the standard Weiner filter.
*
* -------------------------------------------------------------------------
*
* Copyright (C) 2010-2015 (see AUTHORS file for a list of contributors)
*
* GNSS-SDR is a software defined Global Navigation
* Satellite Systems receiver
*
* This file is part of GNSS-SDR.
*
* GNSS-SDR is free software: you can redistribute it and/or modify
* it under the terms of the GNU General Public License as published by
* the Free Software Foundation, either version 3 of the License, or
* (at your option) any later version.
*
* GNSS-SDR is distributed in the hope that it will be useful,
* but WITHOUT ANY WARRANTY; without even the implied warranty of
* MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the
* GNU General Public License for more details.
*
* You should have received a copy of the GNU General Public License
* along with GNSS-SDR. If not, see <http://www.gnu.org/licenses/>.
*
* -------------------------------------------------------------------------
*/
#include "tracking_loop_filter.h"
#include <cmath>
#include <glog/logging.h>
Tracking_loop_filter::Tracking_loop_filter(float update_interval,
float noise_bandwidth,
int loop_order,
bool include_last_integrator)
: d_loop_order(loop_order),
d_current_index(0),
d_include_last_integrator(include_last_integrator),
d_noise_bandwidth(noise_bandwidth),
d_update_interval(update_interval)
{
d_inputs.resize(MAX_LOOP_HISTORY_LENGTH, 0.0);
d_outputs.resize(MAX_LOOP_HISTORY_LENGTH, 0.0);
update_coefficients();
}
Tracking_loop_filter::Tracking_loop_filter()
: d_loop_order(2),
d_current_index(0),
d_include_last_integrator(false),
d_noise_bandwidth(15.0),
d_update_interval(0.001)
{
d_inputs.resize(MAX_LOOP_HISTORY_LENGTH, 0.0);
d_outputs.resize(MAX_LOOP_HISTORY_LENGTH, 0.0);
update_coefficients();
}
Tracking_loop_filter::~Tracking_loop_filter()
{
// Don't need to do anything here
}
float Tracking_loop_filter::apply(float current_input)
{
// Now apply the filter coefficients:
float result = 0.0;
// Hanlde the old outputs first:
for (unsigned int ii = 0; ii < d_output_coefficients.size(); ++ii)
{
result += d_output_coefficients[ii] * d_outputs[(d_current_index + ii) % MAX_LOOP_HISTORY_LENGTH];
}
// Now update the index to handle the inputs.
// DO NOT CHANGE THE ORDER OF THE ABOVE AND BELOW CODE
// SNIPPETS!!!!!!!
// Implementing a sort of circular buffer for the inputs and outputs
// the current input/output is at d_current_index, the nth previous
// input/output is at (d_current_index+n)%d_loop_order
d_current_index--;
if (d_current_index < 0)
{
d_current_index += MAX_LOOP_HISTORY_LENGTH;
}
d_inputs[d_current_index] = current_input;
for (unsigned int ii = 0; ii < d_input_coefficients.size(); ++ii)
{
result += d_input_coefficients[ii] * d_inputs[(d_current_index + ii) % MAX_LOOP_HISTORY_LENGTH];
}
d_outputs[d_current_index] = result;
return result;
}
void Tracking_loop_filter::update_coefficients(void)
{
// Analog gains:
float g1;
float g2;
float g3;
// Natural frequency
float wn;
float T = d_update_interval;
float zeta = 1.0 / std::sqrt(2.0);
// The following is based on the bilinear transform approximation of
// the analog integrator. The loop format is from Kaplan & Hegarty
// Table 5.6. The basic concept is that the loop has a cascade of
// integrators:
// 1 for a 1st order loop
// 2 for a 2nd order loop
// 3 for a 3rd order loop
// The bilinear transform approximates 1/s as
// T/2(1 + z^-1)/(1-z^-1) in the z domain.
switch (d_loop_order)
{
case 1:
wn = d_noise_bandwidth * 4.0;
g1 = wn;
if (d_include_last_integrator)
{
d_input_coefficients.resize(2);
d_input_coefficients[0] = g1 * T / 2.0;
d_input_coefficients[1] = g1 * T / 2.0;
d_output_coefficients.resize(1);
d_output_coefficients[0] = 1.0;
}
else
{
d_input_coefficients.resize(1);
d_input_coefficients[0] = g1;
d_output_coefficients.resize(0);
}
break;
case 2:
wn = d_noise_bandwidth * (8.0 * zeta) / (4.0 * zeta * zeta + 1.0);
g1 = wn * wn;
g2 = wn * 2.0 * zeta;
if (d_include_last_integrator)
{
d_input_coefficients.resize(3);
d_input_coefficients[0] = T / 2.0 * (g1 * T / 2.0 + g2);
d_input_coefficients[1] = T * T / 2.0 * g1;
d_input_coefficients[2] = T / 2.0 * (g1 * T / 2.0 - g2);
d_output_coefficients.resize(2);
d_output_coefficients[0] = 2.0;
d_output_coefficients[1] = -1.0;
}
else
{
d_input_coefficients.resize(2);
d_input_coefficients[0] = (g1 * T / 2.0 + g2);
d_input_coefficients[1] = g1 * T / 2.0 - g2;
d_output_coefficients.resize(1);
d_output_coefficients[0] = 1.0;
}
break;
case 3:
wn = d_noise_bandwidth / 0.7845; // From Kaplan
float a3 = 1.1;
float b3 = 2.4;
g1 = wn * wn * wn;
g2 = a3 * wn * wn;
g3 = b3 * wn;
if (d_include_last_integrator)
{
d_input_coefficients.resize(4);
d_input_coefficients[0] = T / 2.0 * (g3 + T / 2.0 * (g2 + T / 2.0 * g1));
d_input_coefficients[1] = T / 2.0 * (-g3 + T / 2.0 * (g2 + 3.0 * T / 2.0 * g1));
d_input_coefficients[2] = T / 2.0 * (-g3 - T / 2.0 * (g2 - 3.0 * T / 2.0 * g1));
d_input_coefficients[3] = T / 2.0 * (g3 - T / 2.0 * (g2 - T / 2.0 * g1));
d_output_coefficients.resize(3);
d_output_coefficients[0] = 3.0;
d_output_coefficients[1] = -3.0;
d_output_coefficients[2] = 1.0;
}
else
{
d_input_coefficients.resize(3);
d_input_coefficients[0] = g3 + T / 2.0 * (g2 + T / 2.0 * g1);
d_input_coefficients[1] = g1 * T * T / 2.0 - 2.0 * g3;
d_input_coefficients[2] = g3 + T / 2.0 * (-g2 + T / 2.0 * g1);
d_output_coefficients.resize(2);
d_output_coefficients[0] = 2.0;
d_output_coefficients[1] = -1.0;
}
break;
};
}
void Tracking_loop_filter::set_noise_bandwidth(float noise_bandwidth)
{
d_noise_bandwidth = noise_bandwidth;
update_coefficients();
}
float Tracking_loop_filter::get_noise_bandwidth(void) const
{
return d_noise_bandwidth;
}
void Tracking_loop_filter::set_update_interval(float update_interval)
{
d_update_interval = update_interval;
update_coefficients();
}
float Tracking_loop_filter::get_update_interval(void) const
{
return d_update_interval;
}
void Tracking_loop_filter::set_include_last_integrator(bool include_last_integrator)
{
d_include_last_integrator = include_last_integrator;
update_coefficients();
}
bool Tracking_loop_filter::get_include_last_integrator(void) const
{
return d_include_last_integrator;
}
void Tracking_loop_filter::set_order(int loop_order)
{
if (loop_order < 1 or loop_order > MAX_LOOP_ORDER)
{
LOG(ERROR) << "Ignoring attempt to set loop order to " << loop_order
<< ". Maximum allowed order is: " << MAX_LOOP_ORDER
<< ". Not changing current value of " << d_loop_order;
return;
}
d_loop_order = loop_order;
update_coefficients();
}
int Tracking_loop_filter::get_order(void) const
{
return d_loop_order;
}
void Tracking_loop_filter::initialize(float initial_output)
{
d_inputs.assign(MAX_LOOP_HISTORY_LENGTH, 0.0);
d_outputs.assign(MAX_LOOP_HISTORY_LENGTH, initial_output);
d_current_index = MAX_LOOP_HISTORY_LENGTH - 1;
}
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