/*!
* \file tracking_discriminators.cc
* \brief Implementation of a library with a set of code tracking
* and carrier tracking discriminators that is used by the tracking algorithms.
* \authors
* - Javier Arribas, 2011. jarribas(at)cttc.es
*
- Luis Esteve, 2012. luis(at)epsilon-formacion.com
*
*
* -----------------------------------------------------------------------------
*
* Copyright (C) 2010-2020 (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.
*
* SPDX-License-Identifier: GPL-3.0-or-later
*
* -----------------------------------------------------------------------------
*/
#include "tracking_discriminators.h"
#include "MATH_CONSTANTS.h"
// All the outputs are in RADIANS
double phase_unwrap(double phase_rad)
{
if (phase_rad >= HALF_PI)
{
return phase_rad - GNSS_PI;
}
if (phase_rad <= -HALF_PI)
{
return phase_rad + GNSS_PI;
}
else
{
return phase_rad;
}
}
/*
* FLL four quadrant arctan discriminator:
* \f{equation}
* \frac{\phi_2-\phi_1}{t_2-t1}=\frac{ATAN2(cross,dot)}{t_1-t_2},
* \f}
* where \f$cross=I_{PS1}Q_{PS2}-I_{PS2}Q_{PS1}\f$ and \f$dot=I_{PS1}I_{PS2}+Q_{PS1}Q_{PS2}\f$,
* \f$I_{PS1},Q_{PS1}\f$ are the inphase and quadrature prompt correlator outputs respectively at sample time \f$t_1\f$, and
* \f$I_{PS2},Q_{PS2}\f$ are the inphase and quadrature prompt correlator outputs respectively at sample time \f$t_2\f$. The output is in [radians/second].
*/
double fll_four_quadrant_atan(gr_complex prompt_s1, gr_complex prompt_s2, double t1, double t2)
{
const float dot = prompt_s1.real() * prompt_s2.real() + prompt_s1.imag() * prompt_s2.imag();
const float cross = prompt_s1.real() * prompt_s2.imag() - prompt_s2.real() * prompt_s1.imag();
return std::atan2(cross, dot) / (t2 - t1);
}
/*
* FLL differential arctan discriminator:
* \f{equation}
* e_{atan}(k)=\frac{1}{t_1-t_2}\text{phase_unwrap}(\tan^-1(\frac{Q(k)}{I(k)})-\tan^-1(\frac{Q(k-1)}{I(k-1)}))
* \f}
* The output is in [radians/second].
*/
double fll_diff_atan(gr_complex prompt_s1, gr_complex prompt_s2, double t1, double t2)
{
double diff_atan = std::atan(prompt_s2.imag() / prompt_s2.real()) - std::atan(prompt_s1.imag() / prompt_s1.real());
if (std::isnan(diff_atan))
{
diff_atan = 0;
}
return phase_unwrap(diff_atan) / (t2 - t1);
}
/*
* PLL four quadrant arctan discriminator:
* \f{equation}
* \phi=ATAN2(Q_{PS},I_{PS}),
* \f}
* where \f$I_{PS1},Q_{PS1}\f$ are the inphase and quadrature prompt correlator outputs respectively. The output is in [radians].
*/
double pll_four_quadrant_atan(gr_complex prompt_s1)
{
return static_cast(std::atan2(prompt_s1.imag(), prompt_s1.real()));
}
/*
* PLL Costas loop two quadrant arctan discriminator:
* \f{equation}
* \phi=ATAN\left(\frac{Q_{PS}}{I_{PS}}\right),
* \f}
* where \f$I_{PS1},Q_{PS1}\f$ are the inphase and quadrature prompt correlator outputs respectively. The output is in [radians].
*/
double pll_cloop_two_quadrant_atan(gr_complex prompt_s1)
{
if (prompt_s1.real() != 0.0)
{
return static_cast(std::atan(prompt_s1.imag() / prompt_s1.real()));
}
return 0.0;
}
/*
* DLL Noncoherent Early minus Late envelope normalized discriminator:
* \f{equation}
* error = \frac{y_{intercept} - \text{slope} * \epsilon}{\text{slope}} \frac{E-L}{E+L},
* \f}
* where \f$E=\sqrt{I_{ES}^2+Q_{ES}^2}\f$ is the Early correlator output absolute value and
* \f$L=\sqrt{I_{LS}^2+Q_{LS}^2}\f$ is the Late correlator output absolute value. The output is in [chips].
*/
double dll_nc_e_minus_l_normalized(gr_complex early_s1, gr_complex late_s1, float spc, float slope, float y_intercept)
{
const double P_early = std::abs(early_s1);
const double P_late = std::abs(late_s1);
const double E_plus_L = P_early + P_late;
if (E_plus_L == 0.0)
{
return 0.0;
}
return ((y_intercept - slope * spc) / slope) * (P_early - P_late) / E_plus_L;
}
/*
* DLL Noncoherent Very Early Minus Late Power (VEMLP) normalized discriminator, using the outputs
* of four correlators, Very Early (VE), Early (E), Late (L) and Very Late (VL):
* \f{equation}
* error=\frac{E-L}{E+L},
* \f}
* where \f$E=\sqrt{I_{VE}^2+Q_{VE}^2+I_{E}^2+Q_{E}^2}\f$ and
* \f$L=\sqrt{I_{VL}^2+Q_{VL}^2+I_{L}^2+Q_{L}^2}\f$ . The output is in [chips].
*/
double dll_nc_vemlp_normalized(gr_complex very_early_s1, gr_complex early_s1, gr_complex late_s1, gr_complex very_late_s1)
{
const double Early = std::sqrt(very_early_s1.real() * very_early_s1.real() + very_early_s1.imag() * very_early_s1.imag() + early_s1.real() * early_s1.real() + early_s1.imag() * early_s1.imag());
const double Late = std::sqrt(late_s1.real() * late_s1.real() + late_s1.imag() * late_s1.imag() + very_late_s1.real() * very_late_s1.real() + very_late_s1.imag() * very_late_s1.imag());
const double E_plus_L = Early + Late;
if (E_plus_L == 0.0)
{
return 0.0;
}
return (Early - Late) / E_plus_L;
}