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Merge branch 'next' of https://github.com/gnss-sdr/gnss-sdr into next

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This commit is contained in:
Carles Fernandez
2019-06-16 11:13:18 +02:00
parent 5cf552d65b 75d51ab837
commit 01099e27f2
14 changed files with 755 additions and 382 deletions
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1
.clang-tidy
View File

@@ -32,7 +32,6 @@ Checks: '-*,
performance-inefficient-algorithm,
performance-move-const-arg,
performance-type-promotion-in-math-fn,
performance-unnecessary-copy-initialization,
performance-unnecessary-value-param,
readability-container-size-empty,
readability-identifier-naming,

200
CMakeLists.txt
View File

@@ -295,6 +295,12 @@ if(${CMAKE_SYSTEM_NAME} MATCHES "Darwin")
set(OS_IS_MACOSX TRUE)
execute_process(COMMAND uname -v OUTPUT_VARIABLE DARWIN_VERSION)
string(REGEX MATCH "[0-9]+" DARWIN_VERSION ${DARWIN_VERSION})
if(${DARWIN_VERSION} MATCHES "19")
set(MACOS_CATALINA TRUE)
set(CMAKE_XCODE_ATTRIBUTE_CLANG_CXX_LANGUAGE_STANDARD "c++14")
set(CMAKE_XCODE_ATTRIBUTE_CLANG_CXX_LIBRARY "libc++")
message(STATUS "Configuring GNSS-SDR v${VERSION} to be built on macOS Catalina 10.15")
endif()
if(${DARWIN_VERSION} MATCHES "18")
set(MACOS_MOJAVE TRUE)
set(CMAKE_XCODE_ATTRIBUTE_CLANG_CXX_LANGUAGE_STANDARD "c++14")
@@ -468,7 +474,7 @@ endif()
################################################################################
# Set C and C++ standard
# Set minimal C and C++ standards
################################################################################
if(NOT (CMAKE_VERSION VERSION_LESS "3.1"))
set(CMAKE_C_STANDARD 11)
@@ -484,7 +490,7 @@ else()
endif()
endif()
if(CMAKE_CXX_COMPILER_ID MATCHES "Clang")
if(OS_IS_MACOSX)
if(CMAKE_CXX_COMPILER_ID STREQUAL "AppleClang")
if(CLANG_VERSION VERSION_LESS "600")
add_compile_options("$<$<STREQUAL:$<TARGET_PROPERTY:LINKER_LANGUAGE>,CXX>:-std=c++11>")
else()
@@ -623,132 +629,6 @@ set_package_properties(GNURADIO PROPERTIES
PURPOSE "Implements flowgraph scheduler, provides some processing blocks and classes to create new ones."
TYPE REQUIRED
)
if(GNURADIO_VERSION)
if(GNURADIO_VERSION VERSION_LESS ${GNSSSDR_GNURADIO_MIN_VERSION})
unset(GNURADIO_RUNTIME_FOUND)
message(STATUS "The GNU Radio version installed in your system (v${GNURADIO_VERSION}) is too old.")
endif()
endif()
if(NOT GNURADIO_RUNTIME_FOUND)
message(STATUS "CMake cannot find GNU Radio >= ${GNSSSDR_GNURADIO_MIN_VERSION}")
if(OS_IS_LINUX)
message("Go to https://github.com/gnuradio/pybombs")
message("and follow the instructions to install GNU Radio in your system.")
endif()
if(OS_IS_MACOSX)
message("You can install it easily via Macports:")
message(" sudo port install gnuradio ")
message("Alternatively, you can use homebrew:")
message(" brew install gnuradio")
endif()
message(FATAL_ERROR "GNU Radio v${GNSSSDR_GNURADIO_MIN_VERSION} or later is required to build gnss-sdr.")
else()
if(NOT TARGET Gnuradio::runtime)
add_library(Gnuradio::runtime SHARED IMPORTED)
list(GET GNURADIO_RUNTIME_LIBRARIES 0 FIRST_DIR)
get_filename_component(GNURADIO_RUNTIME_DIR ${FIRST_DIR} ABSOLUTE)
set_target_properties(Gnuradio::runtime PROPERTIES
IMPORTED_LINK_INTERFACE_LANGUAGES "CXX"
IMPORTED_LOCATION "${GNURADIO_RUNTIME_DIR}"
INTERFACE_INCLUDE_DIRECTORIES "${GNURADIO_RUNTIME_INCLUDE_DIRS}"
INTERFACE_LINK_LIBRARIES "${GNURADIO_RUNTIME_LIBRARIES}"
)
endif()
endif()
if(NOT GNURADIO_ANALOG_FOUND)
message(FATAL_ERROR "*** The gnuradio-analog library v${GNSSSDR_GNURADIO_MIN_VERSION} or later is required to build gnss-sdr")
else()
if(NOT TARGET Gnuradio::analog)
add_library(Gnuradio::analog SHARED IMPORTED)
list(GET GNURADIO_ANALOG_LIBRARIES 0 FIRST_DIR)
get_filename_component(GNURADIO_ANALOG_DIR ${FIRST_DIR} ABSOLUTE)
set_target_properties(Gnuradio::analog PROPERTIES
IMPORTED_LINK_INTERFACE_LANGUAGES "CXX"
IMPORTED_LOCATION "${GNURADIO_ANALOG_DIR}"
INTERFACE_INCLUDE_DIRECTORIES "${GNURADIO_ANALOG_INCLUDE_DIRS}"
INTERFACE_LINK_LIBRARIES "${GNURADIO_ANALOG_LIBRARIES}"
)
endif()
endif()
if(NOT GNURADIO_BLOCKS_FOUND)
message(FATAL_ERROR "*** The gnuradio-blocks library v${GNSSSDR_GNURADIO_MIN_VERSION} or later is required to build gnss-sdr")
else()
if(NOT TARGET Gnuradio::blocks)
add_library(Gnuradio::blocks SHARED IMPORTED)
list(GET GNURADIO_BLOCKS_LIBRARIES 0 FIRST_DIR)
get_filename_component(GNURADIO_BLOCKS_DIR ${FIRST_DIR} ABSOLUTE)
set_target_properties(Gnuradio::blocks PROPERTIES
IMPORTED_LINK_INTERFACE_LANGUAGES "CXX"
IMPORTED_LOCATION "${GNURADIO_BLOCKS_DIR}"
INTERFACE_INCLUDE_DIRECTORIES "${GNURADIO_BLOCKS_INCLUDE_DIRS}"
INTERFACE_LINK_LIBRARIES "${GNURADIO_BLOCKS_LIBRARIES}"
)
endif()
endif()
if(NOT GNURADIO_FILTER_FOUND)
message(FATAL_ERROR "*** The gnuradio-filter library v${GNSSSDR_GNURADIO_MIN_VERSION} or later is required to build gnss-sdr")
else()
if(NOT TARGET Gnuradio::filter)
add_library(Gnuradio::filter SHARED IMPORTED)
list(GET GNURADIO_FILTER_LIBRARIES 0 FIRST_DIR)
get_filename_component(GNURADIO_FILTER_DIR ${FIRST_DIR} ABSOLUTE)
set_target_properties(Gnuradio::filter PROPERTIES
IMPORTED_LINK_INTERFACE_LANGUAGES "CXX"
IMPORTED_LOCATION "${GNURADIO_FILTER_DIR}"
INTERFACE_INCLUDE_DIRECTORIES "${GNURADIO_FILTER_INCLUDE_DIRS}"
INTERFACE_LINK_LIBRARIES "${GNURADIO_FILTER_LIBRARIES}"
)
endif()
endif()
if(NOT GNURADIO_FFT_FOUND)
message(FATAL_ERROR "*** The gnuradio-fft library v${GNSSSDR_GNURADIO_MIN_VERSION} or later is required to build gnss-sdr")
else()
if(NOT TARGET Gnuradio::fft)
add_library(Gnuradio::fft SHARED IMPORTED)
list(GET GNURADIO_FFT_LIBRARIES 0 FIRST_DIR)
get_filename_component(GNURADIO_FFT_DIR ${FIRST_DIR} ABSOLUTE)
set_target_properties(Gnuradio::fft PROPERTIES
IMPORTED_LINK_INTERFACE_LANGUAGES "CXX"
IMPORTED_LOCATION "${GNURADIO_FFT_DIR}"
INTERFACE_INCLUDE_DIRECTORIES "${GNURADIO_FFT_INCLUDE_DIRS}"
INTERFACE_LINK_LIBRARIES "${GNURADIO_FFT_LIBRARIES}"
)
endif()
endif()
if(NOT GNURADIO_PMT_FOUND)
message(FATAL_ERROR "*** The gnuradio-pmt library v${GNSSSDR_GNURADIO_MIN_VERSION} or later is required to build gnss-sdr")
else()
if(NOT TARGET Gnuradio::pmt)
add_library(Gnuradio::pmt SHARED IMPORTED)
list(GET GNURADIO_PMT_LIBRARIES 0 FIRST_DIR)
get_filename_component(GNURADIO_PMT_DIR ${FIRST_DIR} ABSOLUTE)
set_target_properties(Gnuradio::pmt PROPERTIES
IMPORTED_LINK_INTERFACE_LANGUAGES "CXX"
IMPORTED_LOCATION "${GNURADIO_PMT_DIR}"
INTERFACE_INCLUDE_DIRECTORIES "${GNURADIO_PMT_INCLUDE_DIRS}"
INTERFACE_LINK_LIBRARIES "${GNURADIO_PMT_LIBRARIES}"
)
endif()
endif()
if(ENABLE_UHD AND UHD_FOUND AND GNURADIO_UHD_FOUND)
if(NOT TARGET Gnuradio::uhd)
add_library(Gnuradio::uhd SHARED IMPORTED)
list(GET GNURADIO_UHD_LIBRARIES 0 FIRST_DIR)
get_filename_component(GNURADIO_UHD_DIR ${FIRST_DIR} ABSOLUTE)
set_target_properties(Gnuradio::uhd PROPERTIES
IMPORTED_LINK_INTERFACE_LANGUAGES "CXX"
IMPORTED_LOCATION "${GNURADIO_UHD_DIR}"
INTERFACE_INCLUDE_DIRECTORIES "${GNURADIO_UHD_INCLUDE_DIRS}"
INTERFACE_LINK_LIBRARIES "${GNURADIO_UHD_LIBRARIES}"
)
endif()
endif()
@@ -769,7 +649,7 @@ endif()
################################################################################
# Dectect availability of std::filesystem
# Detect availability of std::filesystem and set C++ standard accordingly
################################################################################
set(FILESYSTEM_FOUND FALSE)
if(NOT (GNURADIO_VERSION VERSION_LESS 3.8) AND LOG4CPP_READY_FOR_CXX17)
@@ -787,7 +667,11 @@ if(NOT (GNURADIO_VERSION VERSION_LESS 3.8) AND LOG4CPP_READY_FOR_CXX17)
TYPE OPTIONAL
)
if(${FILESYSTEM_FOUND})
set(CMAKE_CXX_STANDARD 17)
if(CMAKE_VERSION VERSION_LESS 3.12)
set(CMAKE_CXX_STANDARD 17)
else()
set(CMAKE_CXX_STANDARD 20)
endif()
set(CMAKE_CXX_STANDARD_REQUIRED ON)
endif()
endif()
@@ -1231,37 +1115,30 @@ if(NOT GLOG_FOUND OR ${LOCAL_GFLAGS})
set(GFLAGS_LIBRARIES_TO_LINK ${GFlags_LIBS})
set(GFLAGS_LIBRARY_DIR_TO_LINK ${GFlags_LIBRARY_DIRS})
endif()
if(CMAKE_CXX_COMPILER_ID MATCHES "Clang")
file(WRITE ${CMAKE_CURRENT_BINARY_DIR}/glog-${GNSSSDR_GLOG_LOCAL_VERSION}/tmp/configure_with_gflags
"#!/bin/sh
export CPPFLAGS=-I${GFlags_INCLUDE_DIRS}
export LDFLAGS=-L${GFLAGS_LIBRARY_DIR_TO_LINK}
export LIBS=\"${GFLAGS_LIBRARIES_TO_LINK} -lc++\"
export CXXFLAGS=\"-stdlib=libc++\"
export CC=clang
export CXX=clang++
cd ${CMAKE_CURRENT_SOURCE_DIR}/thirdparty/glog/glog-${GNSSSDR_GLOG_LOCAL_VERSION}/
aclocal
automake --add-missing
autoreconf -vfi
cd ${CMAKE_CURRENT_BINARY_DIR}/glog-${GNSSSDR_GLOG_LOCAL_VERSION}
${CMAKE_CURRENT_SOURCE_DIR}/thirdparty/glog/glog-${GNSSSDR_GLOG_LOCAL_VERSION}/configure"
)
else()
file(WRITE ${CMAKE_CURRENT_BINARY_DIR}/glog-${GNSSSDR_GLOG_LOCAL_VERSION}/tmp/configure_with_gflags
"#!/bin/sh
export CPPFLAGS=-I${GFlags_INCLUDE_DIRS}
export LDFLAGS=-L${GFLAGS_LIBRARY_DIR_TO_LINK}
export LIBS=${GFLAGS_LIBRARIES_TO_LINK}
cd ${CMAKE_CURRENT_SOURCE_DIR}/thirdparty/glog/glog-${GNSSSDR_GLOG_LOCAL_VERSION}/
aclocal
automake --add-missing
autoreconf -vfi
cd ${CMAKE_CURRENT_BINARY_DIR}/glog-${GNSSSDR_GLOG_LOCAL_VERSION}
${CMAKE_CURRENT_SOURCE_DIR}/thirdparty/glog/glog-${GNSSSDR_GLOG_LOCAL_VERSION}/configure"
)
if(OS_IS_MACOSX)
set(GFLAGS_LIBRARIES_TO_LINK "${GFLAGS_LIBRARIES_TO_LINK} -lc++")
set(GLOG_EXPORT_CXX_LIBRARIES "export CXXFLAGS=\"-stdlib=libc++\"")
endif()
if(CMAKE_CXX_COMPILER_ID MATCHES "Clang")
set(GLOG_EXPORT_C_COMPILER "export CC=clang")
set(GLOG_EXPORT_CXX_COMPILER "export CXX=clang++")
endif()
file(WRITE ${CMAKE_CURRENT_BINARY_DIR}/glog-${GNSSSDR_GLOG_LOCAL_VERSION}/tmp/configure_with_gflags
"#!/bin/sh
export CPPFLAGS=-I${GFlags_INCLUDE_DIRS}
export LDFLAGS=-L${GFLAGS_LIBRARY_DIR_TO_LINK}
export LIBS=\"${GFLAGS_LIBRARIES_TO_LINK}\"
${GLOG_EXPORT_CXX_LIBRARIES}
${GLOG_EXPORT_C_COMPILER}
${GLOG_EXPORT_CXX_COMPILER}
cd ${CMAKE_CURRENT_SOURCE_DIR}/thirdparty/glog/glog-${GNSSSDR_GLOG_LOCAL_VERSION}/
aclocal
automake --add-missing
autoreconf -vfi
cd ${CMAKE_CURRENT_BINARY_DIR}/glog-${GNSSSDR_GLOG_LOCAL_VERSION}
${CMAKE_CURRENT_SOURCE_DIR}/thirdparty/glog/glog-${GNSSSDR_GLOG_LOCAL_VERSION}/configure"
)
file(COPY ${CMAKE_CURRENT_BINARY_DIR}/glog-${GNSSSDR_GLOG_LOCAL_VERSION}/tmp/configure_with_gflags
DESTINATION ${CMAKE_CURRENT_BINARY_DIR}/glog-${GNSSSDR_GLOG_LOCAL_VERSION}
@@ -1460,6 +1337,9 @@ set_package_properties(Armadillo PROPERTIES
TYPE REQUIRED
)
if(ARMADILLO_FOUND)
set_package_properties(Armadillo PROPERTIES
DESCRIPTION "C++ library for linear algebra and scientific computing (found: v${ARMADILLO_VERSION_STRING})"
)
if(${ARMADILLO_VERSION_STRING} VERSION_LESS ${GNSSSDR_ARMADILLO_MIN_VERSION})
set(ARMADILLO_FOUND false)
set(ENABLE_OWN_ARMADILLO true)

43
cmake/Modules/FindGFORTRAN.cmake
View File

@@ -45,12 +45,37 @@ find_library(GFORTRAN NAMES gfortran
/usr/lib/gcc/i686-redhat-linux/4.8.2
/usr/lib/gcc/x86_64-redhat-linux/7
/usr/lib/gcc/i686-redhat-linux/7
/usr/lib/gcc/x86_64-redhat-linux/8
/usr/lib/gcc/i686-redhat-linux/8
/usr/lib/gcc/x86_64-redhat-linux/9
/usr/lib/gcc/i686-redhat-linux/9
/usr/lib64/gcc/x86_64-redhat-linux/7
/usr/lib64/gcc/x86_64-redhat-linux/8
/usr/lib64/gcc/x86_64-redhat-linux/9
/usr/lib/gcc/armv7hl-redhat-linux-gnueabi/7
/usr/lib/gcc/aarch64-redhat-linux/7
/usr/lib/gcc/i586-suse-linux/4.8 # OpenSUSE 13.1
/usr/lib/gcc/i586-suse-linux/4.9
/usr/lib/gcc/i586-suse-linux/7
/usr/lib/gcc/i586-suse-linux/8
/usr/lib/gcc/i586-suse-linux/9
/usr/lib/gcc/x86_64-suse-linux/4.8
/usr/lib/gcc/x86_64-suse-linux/4.9
/usr/lib64/gcc/x86_64-suse-linux/7
/usr/lib64/gcc/x86_64-suse-linux/8
/usr/lib64/gcc/x86_64-suse-linux/9
/usr/lib/gcc/armv7hl-suse-linux-gnueabi/7
/usr/lib/gcc/armv7hl-suse-linux-gnueabi/8
/usr/lib/gcc/armv7hl-suse-linux-gnueabi/9
/usr/lib64/gcc/aarch64-suse-linux/7
/usr/lib64/gcc/aarch64-suse-linux/8
/usr/lib64/gcc/aarch64-suse-linux/9
/usr/lib64/gcc/powerpc64-suse-linux/7
/usr/lib64/gcc/powerpc64-suse-linux/8
/usr/lib64/gcc/powerpc64-suse-linux/9
/usr/lib64/gcc/powerpc64le-suse-linux/7
/usr/lib64/gcc/powerpc64le-suse-linux/8
/usr/lib64/gcc/powerpc64le-suse-linux/9
/usr/lib/gcc/i486-linux-gnu # Debian 7
/usr/lib/gcc/i486-linux-gnu/4.4
/usr/lib/gcc/i486-linux-gnu/4.6
@@ -142,6 +167,24 @@ find_library(GFORTRAN NAMES gfortran
/usr/lib/gcc/powerpc64le-linux-gnu/8
/usr/lib/gcc/s390x-linux-gnu/8
/usr/lib/gcc/alpha-linux-gnu/8
/usr/lib/gcc/x86_64-linux-gnu/9
/usr/lib/gcc/aarch64-linux-gnu/9
/usr/lib/gcc/arm-linux-gnueabi/9
/usr/lib/gcc/arm-linux-gnueabihf/9
/usr/lib/gcc/i686-linux-gnu/9
/usr/lib/gcc/powerpc64le-linux-gnu/9
/usr/lib/gcc/powerpc64-linux-gnu/9/
/usr/lib/gcc/s390x-linux-gnu/9
/usr/lib/gcc/alpha-linux-gnu/9
/usr/lib/gcc/hppa-linux-gnu/9
/usr/lib/gcc/m68k-linux-gnu/9
/usr/lib/gcc/mips-linux-gnu/9
/usr/lib/gcc/mips64el-linux-gnuabi64/9
/usr/lib/gcc/mipsel-linux-gnu/9
/usr/lib/gcc/riscv64-linux-gnu/9
/usr/lib/gcc/sh4-linux-gnu/9
/usr/lib/gcc/sparc64-linux-gnu/9
/usr/lib/gcc/x86_64-linux-gnux32/9
${GFORTRAN_ROOT}/lib
$ENV{GFORTRAN_ROOT}/lib
)

37
cmake/Modules/FindGNURADIO.cmake
View File

@@ -143,6 +143,21 @@ function(GR_MODULE EXTVAR PCNAME INCFILE LIBFILE)
set(GNURADIO_FOUND FALSE) # Trick for feature_summary
endif()
# Create imported target
string(TOLOWER ${EXTVAR} gnuradio_component)
if(NOT TARGET Gnuradio::${gnuradio_component})
add_library(Gnuradio::${gnuradio_component} SHARED IMPORTED)
set(GNURADIO_LIBRARY ${GNURADIO_${EXTVAR}_LIBRARIES})
list(GET GNURADIO_LIBRARY 0 FIRST_DIR)
get_filename_component(GNURADIO_DIR ${FIRST_DIR} ABSOLUTE)
set_target_properties(Gnuradio::${gnuradio_component} PROPERTIES
IMPORTED_LINK_INTERFACE_LANGUAGES "CXX"
IMPORTED_LOCATION "${GNURADIO_DIR}"
INTERFACE_INCLUDE_DIRECTORIES "${GNURADIO_${EXTVAR}_INCLUDE_DIRS}"
INTERFACE_LINK_LIBRARIES "${GNURADIO_LIBRARY}"
)
endif()
mark_as_advanced(GNURADIO_${EXTVAR}_LIBRARIES GNURADIO_${EXTVAR}_INCLUDE_DIRS)
endfunction()
@@ -218,3 +233,25 @@ if(NOT DEFINED GNURADIO_FOUND)
set(GNURADIO_FOUND TRUE)
endif()
set(GNURADIO_VERSION ${PC_GNURADIO_RUNTIME_VERSION})
if(NOT GNSSSDR_GNURADIO_MIN_VERSION)
set(GNSSSDR_GNURADIO_MIN_VERSION "3.7.3")
endif()
if(GNURADIO_VERSION)
if(GNURADIO_VERSION VERSION_LESS ${GNSSSDR_GNURADIO_MIN_VERSION})
unset(GNURADIO_RUNTIME_FOUND)
message(STATUS "The GNU Radio version installed in your system (v${GNURADIO_VERSION}) is too old.")
if(OS_IS_LINUX)
message("Go to https://github.com/gnuradio/pybombs")
message("and follow the instructions to install GNU Radio in your system.")
endif()
if(OS_IS_MACOSX)
message("You can install it easily via Macports:")
message(" sudo port install gnuradio ")
message("Alternatively, you can use homebrew:")
message(" brew install gnuradio")
endif()
message(FATAL_ERROR "GNU Radio v${GNSSSDR_GNURADIO_MIN_VERSION} or later is required to build gnss-sdr.")
endif()
endif()

5
docs/changelog
View File

@@ -16,7 +16,7 @@
- Improved preamble detection implementation in the decoding of navigation messages (acceleration by x1.6 on average per channel).
- Shortened Acquisition to Tracking transition time.
- Applied clang-tidy checks and fixes related to performance: performance-faster-string-find, performance-inefficient-algorithm, performance-move-const-arg, performance-type-promotion-in-math-fn, performance-unnecessary-copy-initialization, performance-unnecessary-value-param, readability-string-compare.
- Applied clang-tidy checks and fixes related to performance: performance-faster-string-find, performance-inefficient-algorithm, performance-move-const-arg, performance-type-promotion-in-math-fn, performance-unnecessary-value-param, readability-string-compare.
### Improvements in Flexibility:
@@ -50,7 +50,8 @@
- Added interfaces for FPGA off-loading.
- CMake scripts now follow a modern approach (targets and properties) but still work with 2.8.12.
- Improvements for macOS users using Homebrew.
- The volk_gnsssdr library can now be built without requiring Boost if the compiler supports C++17.
- The volk_gnsssdr library can now be built without requiring Boost if the compiler supports C++17 or higher.
- CMake scripts automatically select among C++11, C++14, C++17 or C++20 standards, the most recent as possible, depending on compiler and dependencies versions.
### Improvements in Reliability

12
src/algorithms/libs/volk_gnsssdr_module/volk_gnsssdr/CMakeLists.txt
View File

@@ -95,7 +95,11 @@ if((CMAKE_CXX_COMPILER_ID STREQUAL "GNU") AND NOT WIN32)
set(CMAKE_CXX_STANDARD 14)
else()
if(${FILESYSTEM_FOUND})
set(CMAKE_CXX_STANDARD 17)
if(CMAKE_VERSION VERSION_LESS 3.12)
set(CMAKE_CXX_STANDARD 17)
else()
set(CMAKE_CXX_STANDARD 20)
endif()
set(CMAKE_CXX_STANDARD_REQUIRED ON)
else()
set(CMAKE_CXX_STANDARD 14)
@@ -134,7 +138,11 @@ if(CMAKE_CXX_COMPILER_ID MATCHES "Clang")
set(CMAKE_CXX_STANDARD 14)
else()
if(${FILESYSTEM_FOUND})
set(CMAKE_CXX_STANDARD 17)
if(CMAKE_VERSION VERSION_LESS 3.12)
set(CMAKE_CXX_STANDARD 17)
else()
set(CMAKE_CXX_STANDARD 20)
endif()
set(CMAKE_CXX_STANDARD_REQUIRED ON)
else()
set(CMAKE_CXX_STANDARD 14)

9
src/algorithms/tracking/libs/CMakeLists.txt
View File

@@ -33,7 +33,6 @@ set(TRACKING_LIB_SOURCES
cpu_multicorrelator.cc
cpu_multicorrelator_real_codes.cc
cpu_multicorrelator_16sc.cc
cubature_filter.cc
lock_detectors.cc
tcp_communication.cc
tcp_packet_data.cc
@@ -51,7 +50,6 @@ set(TRACKING_LIB_HEADERS
cpu_multicorrelator.h
cpu_multicorrelator_real_codes.h
cpu_multicorrelator_16sc.h
cubature_filter.h
lock_detectors.h
tcp_communication.h
tcp_packet_data.h
@@ -65,6 +63,12 @@ set(TRACKING_LIB_HEADERS
exponential_smoother.h
)
if(ARMADILLO_VERSION_STRING VERSION_GREATER 7.400)
# sqrtmat_sympd() requires 7.400
set(TRACKING_LIB_SOURCES ${TRACKING_LIB_SOURCES} nonlinear_tracking.cc)
set(TRACKING_LIB_HEADERS ${TRACKING_LIB_HEADERS} nonlinear_tracking.h)
endif()
if(ENABLE_FPGA)
set(TRACKING_LIB_SOURCES ${TRACKING_LIB_SOURCES} fpga_multicorrelator.cc dll_pll_conf_fpga.cc)
set(TRACKING_LIB_HEADERS ${TRACKING_LIB_HEADERS} fpga_multicorrelator.h dll_pll_conf_fpga.h)
@@ -84,6 +88,7 @@ target_link_libraries(tracking_libs
Gnuradio::runtime
Volkgnsssdr::volkgnsssdr
core_system_parameters
algorithms_libs
${OPT_TRACKING_LIBRARIES}
PRIVATE
Gflags::gflags

199
src/algorithms/tracking/libs/cubature_filter.cc
View File

@@ -1,199 +0,0 @@
/*!
* \file cubature_filter.cc
* \brief Interface of a library with Bayesian noise statistic estimation
*
* Cubature_Filter implements the functionality of the Cubature Kalman
* Filter, which uses multidimensional cubature rules to estimate the
* time evolution of a nonlinear system.
*
* [1] I Arasaratnam and S Haykin. Cubature kalman filters. IEEE
* Transactions on Automatic Control, 54(6):1254–1269,2009.
*
* \authors <ul>
* <li> Gerald LaMountain, 2019. gerald(at)ece.neu.edu
* <li> Jordi Vila-Valls 2019. jvila(at)cttc.es
* </ul>
* -------------------------------------------------------------------------
*
* Copyright (C) 2010-2019 (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 <https://www.gnu.org/licenses/>.
*
* -------------------------------------------------------------------------
*/
#include "cubature_filter.h"
Cubature_filter::Cubature_filter()
{
int nx = 1;
x_pred_out = arma::zeros(nx, 1);
P_x_pred_out = arma::eye(nx, nx) * (nx + 1);
x_est = x_pred_out;
P_x_est = P_x_pred_out;
}
Cubature_filter::Cubature_filter(int nx)
{
x_pred_out = arma::zeros(nx, 1);
P_x_pred_out = arma::eye(nx, nx) * (nx + 1);
x_est = x_pred_out;
P_x_est = P_x_pred_out;
}
Cubature_filter::Cubature_filter(const arma::vec& x_pred_0, const arma::mat& P_x_pred_0)
{
x_pred_out = x_pred_0;
P_x_pred_out = P_x_pred_0;
x_est = x_pred_out;
P_x_est = P_x_pred_out;
}
Cubature_filter::~Cubature_filter() = default;
void Cubature_filter::initialize(const arma::mat& x_pred_0, const arma::mat& P_x_pred_0)
{
x_pred_out = x_pred_0;
P_x_pred_out = P_x_pred_0;
x_est = x_pred_out;
P_x_est = P_x_pred_out;
}
/*
* Perform the prediction step of the cubature Kalman filter
*/
void Cubature_filter::predict_sequential(const arma::vec& x_post, const arma::mat& P_x_post, Model_Function* transition_fcn, const arma::mat& noise_covariance)
{
// Compute number of cubature points
int nx = x_post.n_elem;
int np = 2 * nx;
// Generator Matrix
arma::mat gen_one = arma::join_horiz(arma::eye(nx, nx), -1.0 * arma::eye(nx, nx));
// Initialize predicted mean and covariance
arma::vec x_pred = arma::zeros(nx, 1);
arma::mat P_x_pred = arma::zeros(nx, nx);
// Factorize posterior covariance
arma::mat Sm_post = arma::chol(P_x_post, "lower");
// Propagate and evaluate cubature points
arma::vec Xi_post;
arma::vec Xi_pred;
for (uint8_t i = 0; i < np; i++)
{
Xi_post = Sm_post * (std::sqrt(static_cast<float>(np) / 2.0) * gen_one.col(i)) + x_post;
Xi_pred = (*transition_fcn)(Xi_post);
x_pred = x_pred + Xi_pred;
P_x_pred = P_x_pred + Xi_pred * Xi_pred.t();
}
// Estimate predicted state and error covariance
x_pred = x_pred / static_cast<float>(np);
P_x_pred = P_x_pred / static_cast<float>(np) - x_pred * x_pred.t() + noise_covariance;
// Store predicted state and error covariance
x_pred_out = x_pred;
P_x_pred_out = P_x_pred;
}
/*
* Perform the update step of the cubature Kalman filter
*/
void Cubature_filter::update_sequential(const arma::vec& z_upd, const arma::vec& x_pred, const arma::mat& P_x_pred, Model_Function* measurement_fcn, const arma::mat& noise_covariance)
{
// Compute number of cubature points
int nx = x_pred.n_elem;
int nz = z_upd.n_elem;
int np = 2 * nx;
// Generator Matrix
arma::mat gen_one = arma::join_horiz(arma::eye(nx, nx), -1.0 * arma::eye(nx, nx));
// Evaluate predicted measurement and covariances
arma::mat z_pred = arma::zeros(nz, 1);
arma::mat P_zz_pred = arma::zeros(nz, nz);
arma::mat P_xz_pred = arma::zeros(nx, nz);
// Factorize predicted covariance
arma::mat Sm_pred = arma::chol(P_x_pred, "lower");
// Propagate and evaluate cubature points
arma::vec Xi_pred;
arma::vec Zi_pred;
for (uint8_t i = 0; i < np; i++)
{
Xi_pred = Sm_pred * (std::sqrt(static_cast<float>(np) / 2.0) * gen_one.col(i)) + x_pred;
Zi_pred = (*measurement_fcn)(Xi_pred);
z_pred = z_pred + Zi_pred;
P_zz_pred = P_zz_pred + Zi_pred * Zi_pred.t();
P_xz_pred = P_xz_pred + Xi_pred * Zi_pred.t();
}
// Estimate measurement covariance and cross covariances
z_pred = z_pred / static_cast<float>(np);
P_zz_pred = P_zz_pred / static_cast<float>(np) - z_pred * z_pred.t() + noise_covariance;
P_xz_pred = P_xz_pred / static_cast<float>(np) - x_pred * z_pred.t();
// Estimate cubature Kalman gain
arma::mat W_k = P_xz_pred * arma::inv(P_zz_pred);
// Estimate and store the updated state and error covariance
x_est = x_pred + W_k * (z_upd - z_pred);
P_x_est = P_x_pred - W_k * P_zz_pred * W_k.t();
}
arma::mat Cubature_filter::get_x_pred() const
{
return x_pred_out;
}
arma::mat Cubature_filter::get_P_x_pred() const
{
return P_x_pred_out;
}
arma::mat Cubature_filter::get_x_est() const
{
return x_est;
}
arma::mat Cubature_filter::get_P_x_est() const
{
return P_x_est;
}

390
src/algorithms/tracking/libs/nonlinear_tracking.cc Normal file
View File

@@ -0,0 +1,390 @@
/*!
* \file cubature_filter.cc
* \brief Interface of a library for nonlinear tracking algorithms
*
* Cubature_Filter implements the functionality of the Cubature Kalman
* Filter, which uses multidimensional cubature rules to estimate the
* time evolution of a nonlinear system. Unscented_filter implements
* an Unscented Kalman Filter which uses Unscented Transform rules to
* perform a similar estimation.
*
* [1] I Arasaratnam and S Haykin. Cubature kalman filters. IEEE
* Transactions on Automatic Control, 54(6):1254–1269,2009.
*
* \authors <ul>
* <li> Gerald LaMountain, 2019. gerald(at)ece.neu.edu
* <li> Jordi Vila-Valls 2019. jvila(at)cttc.es
* </ul>
* -------------------------------------------------------------------------
*
* Copyright (C) 2010-2019 (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 <https://www.gnu.org/licenses/>.
*
* -------------------------------------------------------------------------
*/
#include "nonlinear_tracking.h"
/***************** CUBATURE KALMAN FILTER *****************/
Cubature_filter::Cubature_filter()
{
int nx = 1;
x_pred_out = arma::zeros(nx, 1);
P_x_pred_out = arma::eye(nx, nx) * (nx + 1);
x_est = x_pred_out;
P_x_est = P_x_pred_out;
}
Cubature_filter::Cubature_filter(int nx)
{
x_pred_out = arma::zeros(nx, 1);
P_x_pred_out = arma::eye(nx, nx) * (nx + 1);
x_est = x_pred_out;
P_x_est = P_x_pred_out;
}
Cubature_filter::Cubature_filter(const arma::vec& x_pred_0, const arma::mat& P_x_pred_0)
{
x_pred_out = x_pred_0;
P_x_pred_out = P_x_pred_0;
x_est = x_pred_out;
P_x_est = P_x_pred_out;
}
Cubature_filter::~Cubature_filter() = default;
void Cubature_filter::initialize(const arma::mat& x_pred_0, const arma::mat& P_x_pred_0)
{
x_pred_out = x_pred_0;
P_x_pred_out = P_x_pred_0;
x_est = x_pred_out;
P_x_est = P_x_pred_out;
}
/*
* Perform the prediction step of the cubature Kalman filter
*/
void Cubature_filter::predict_sequential(const arma::vec& x_post, const arma::mat& P_x_post, Model_Function* transition_fcn, const arma::mat& noise_covariance)
{
// Compute number of cubature points
int nx = x_post.n_elem;
int np = 2 * nx;
// Generator Matrix
arma::mat gen_one = arma::join_horiz(arma::eye(nx, nx), -1.0 * arma::eye(nx, nx));
// Initialize predicted mean and covariance
arma::vec x_pred = arma::zeros(nx, 1);
arma::mat P_x_pred = arma::zeros(nx, nx);
// Factorize posterior covariance
arma::mat Sm_post = arma::chol(P_x_post, "lower");
// Propagate and evaluate cubature points
arma::vec Xi_post;
arma::vec Xi_pred;
for (uint8_t i = 0; i < np; i++)
{
Xi_post = Sm_post * (std::sqrt(static_cast<float>(np) / 2.0) * gen_one.col(i)) + x_post;
Xi_pred = (*transition_fcn)(Xi_post);
x_pred = x_pred + Xi_pred;
P_x_pred = P_x_pred + Xi_pred * Xi_pred.t();
}
// Compute predicted mean and error covariance
x_pred = x_pred / static_cast<float>(np);
P_x_pred = P_x_pred / static_cast<float>(np) - x_pred * x_pred.t() + noise_covariance;
// Store predicted mean and error covariance
x_pred_out = x_pred;
P_x_pred_out = P_x_pred;
}
/*
* Perform the update step of the cubature Kalman filter
*/
void Cubature_filter::update_sequential(const arma::vec& z_upd, const arma::vec& x_pred, const arma::mat& P_x_pred, Model_Function* measurement_fcn, const arma::mat& noise_covariance)
{
// Compute number of cubature points
int nx = x_pred.n_elem;
int nz = z_upd.n_elem;
int np = 2 * nx;
// Generator Matrix
arma::mat gen_one = arma::join_horiz(arma::eye(nx, nx), -1.0 * arma::eye(nx, nx));
// Initialize estimated predicted measurement and covariances
arma::mat z_pred = arma::zeros(nz, 1);
arma::mat P_zz_pred = arma::zeros(nz, nz);
arma::mat P_xz_pred = arma::zeros(nx, nz);
// Factorize predicted covariance
arma::mat Sm_pred = arma::chol(P_x_pred, "lower");
// Propagate and evaluate cubature points
arma::vec Xi_pred;
arma::vec Zi_pred;
for (uint8_t i = 0; i < np; i++)
{
Xi_pred = Sm_pred * (std::sqrt(static_cast<float>(np) / 2.0) * gen_one.col(i)) + x_pred;
Zi_pred = (*measurement_fcn)(Xi_pred);
z_pred = z_pred + Zi_pred;
P_zz_pred = P_zz_pred + Zi_pred * Zi_pred.t();
P_xz_pred = P_xz_pred + Xi_pred * Zi_pred.t();
}
// Compute measurement mean, covariance and cross covariance
z_pred = z_pred / static_cast<float>(np);
P_zz_pred = P_zz_pred / static_cast<float>(np) - z_pred * z_pred.t() + noise_covariance;
P_xz_pred = P_xz_pred / static_cast<float>(np) - x_pred * z_pred.t();
// Compute cubature Kalman gain
arma::mat W_k = P_xz_pred * arma::inv(P_zz_pred);
// Compute and store the updated mean and error covariance
x_est = x_pred + W_k * (z_upd - z_pred);
P_x_est = P_x_pred - W_k * P_zz_pred * W_k.t();
}
arma::mat Cubature_filter::get_x_pred() const
{
return x_pred_out;
}
arma::mat Cubature_filter::get_P_x_pred() const
{
return P_x_pred_out;
}
arma::mat Cubature_filter::get_x_est() const
{
return x_est;
}
arma::mat Cubature_filter::get_P_x_est() const
{
return P_x_est;
}
/***************** END CUBATURE KALMAN FILTER *****************/
/***************** UNSCENTED KALMAN FILTER *****************/
Unscented_filter::Unscented_filter()
{
int nx = 1;
x_pred_out = arma::zeros(nx, 1);
P_x_pred_out = arma::eye(nx, nx) * (nx + 1);
x_est = x_pred_out;
P_x_est = P_x_pred_out;
}
Unscented_filter::Unscented_filter(int nx)
{
x_pred_out = arma::zeros(nx, 1);
P_x_pred_out = arma::eye(nx, nx) * (nx + 1);
x_est = x_pred_out;
P_x_est = P_x_pred_out;
}
Unscented_filter::Unscented_filter(const arma::vec& x_pred_0, const arma::mat& P_x_pred_0)
{
x_pred_out = x_pred_0;
P_x_pred_out = P_x_pred_0;
x_est = x_pred_out;
P_x_est = P_x_pred_out;
}
Unscented_filter::~Unscented_filter() = default;
void Unscented_filter::initialize(const arma::mat& x_pred_0, const arma::mat& P_x_pred_0)
{
x_pred_out = x_pred_0;
P_x_pred_out = P_x_pred_0;
x_est = x_pred_out;
P_x_est = P_x_pred_out;
}
/*
* Perform the prediction step of the Unscented Kalman filter
*/
void Unscented_filter::predict_sequential(const arma::vec& x_post, const arma::mat& P_x_post, Model_Function* transition_fcn, const arma::mat& noise_covariance)
{
// Compute number of sigma points
int nx = x_post.n_elem;
int np = 2 * nx + 1;
float alpha = 0.001;
float kappa = 0.0;
float beta = 2.0;
float lambda = std::pow(alpha, 2.0) * (static_cast<float>(nx) + kappa) - static_cast<float>(nx);
// Compute UT Weights
float W0_m = lambda / (static_cast<float>(nx) + lambda);
float W0_c = lambda / (static_cast<float>(nx) + lambda) + (1 - std::pow(alpha, 2.0) + beta);
float Wi_m = 1.0 / (2.0 * (static_cast<float>(nx) + lambda));
// Propagate and evaluate sigma points
arma::mat Xi_fact = arma::zeros(nx, nx);
arma::mat Xi_post = arma::zeros(nx, np);
arma::mat Xi_pred = arma::zeros(nx, np);
Xi_post.col(0) = x_post;
Xi_pred.col(0) = (*transition_fcn)(Xi_post.col(0));
for (uint8_t i = 1; i <= nx; i++)
{
Xi_fact = std::sqrt(static_cast<float>(nx) + lambda) * arma::sqrtmat_sympd(P_x_post);
Xi_post.col(i) = x_post + Xi_fact.col(i - 1);
Xi_post.col(i + nx) = x_post - Xi_fact.col(i - 1);
Xi_pred.col(i) = (*transition_fcn)(Xi_post.col(i));
Xi_pred.col(i + nx) = (*transition_fcn)(Xi_post.col(i + nx));
}
// Compute predicted mean
arma::vec x_pred = W0_m * Xi_pred.col(0) + Wi_m * arma::sum(Xi_pred.cols(1, np - 1), 1);
// Compute predicted error covariance
arma::mat P_x_pred = W0_c * ((Xi_pred.col(0) - x_pred) * (Xi_pred.col(0).t() - x_pred.t()));
for (uint8_t i = 1; i < np; i++)
{
P_x_pred = P_x_pred + Wi_m * ((Xi_pred.col(i) - x_pred) * (Xi_pred.col(i).t() - x_pred.t()));
}
P_x_pred = P_x_pred + noise_covariance;
// Store predicted mean and error covariance
x_pred_out = x_pred;
P_x_pred_out = P_x_pred;
}
/*
* Perform the update step of the Unscented Kalman filter
*/
void Unscented_filter::update_sequential(const arma::vec& z_upd, const arma::vec& x_pred, const arma::mat& P_x_pred, Model_Function* measurement_fcn, const arma::mat& noise_covariance)
{
// Compute number of sigma points
int nx = x_pred.n_elem;
int nz = z_upd.n_elem;
int np = 2 * nx + 1;
float alpha = 0.001;
float kappa = 0.0;
float beta = 2.0;
float lambda = std::pow(alpha, 2.0) * (static_cast<float>(nx) + kappa) - static_cast<float>(nx);
// Compute UT Weights
float W0_m = lambda / (static_cast<float>(nx) + lambda);
float W0_c = lambda / (static_cast<float>(nx) + lambda) + (1.0 - std::pow(alpha, 2.0) + beta);
float Wi_m = 1.0 / (2.0 * (static_cast<float>(nx) + lambda));
// Propagate and evaluate sigma points
arma::mat Xi_fact = arma::zeros(nx, nx);
arma::mat Xi_pred = arma::zeros(nx, np);
arma::mat Zi_pred = arma::zeros(nz, np);
Xi_pred.col(0) = x_pred;
Zi_pred.col(0) = (*measurement_fcn)(Xi_pred.col(0));
for (uint8_t i = 1; i <= nx; i++)
{
Xi_fact = std::sqrt(static_cast<float>(nx) + lambda) * arma::sqrtmat_sympd(P_x_pred);
Xi_pred.col(i) = x_pred + Xi_fact.col(i - 1);
Xi_pred.col(i + nx) = x_pred - Xi_fact.col(i - 1);
Zi_pred.col(i) = (*measurement_fcn)(Xi_pred.col(i));
Zi_pred.col(i + nx) = (*measurement_fcn)(Xi_pred.col(i + nx));
}
// Compute measurement mean
arma::mat z_pred = W0_m * Zi_pred.col(0) + Wi_m * arma::sum(Zi_pred.cols(1, np - 1), 1);
// Compute measurement covariance and cross covariance
arma::mat P_zz_pred = W0_c * ((Zi_pred.col(0) - z_pred) * (Zi_pred.col(0).t() - z_pred.t()));
arma::mat P_xz_pred = W0_c * ((Xi_pred.col(0) - x_pred) * (Zi_pred.col(0).t() - z_pred.t()));
for (uint8_t i = 0; i < np; i++)
{
P_zz_pred = P_zz_pred + Wi_m * ((Zi_pred.col(i) - z_pred) * (Zi_pred.col(i).t() - z_pred.t()));
P_xz_pred = P_xz_pred + Wi_m * ((Xi_pred.col(i) - x_pred) * (Zi_pred.col(i).t() - z_pred.t()));
}
P_zz_pred = P_zz_pred + noise_covariance;
// Estimate cubature Kalman gain
arma::mat W_k = P_xz_pred * arma::inv(P_zz_pred);
// Estimate and store the updated mean and error covariance
x_est = x_pred + W_k * (z_upd - z_pred);
P_x_est = P_x_pred - W_k * P_zz_pred * W_k.t();
}
arma::mat Unscented_filter::get_x_pred() const
{
return x_pred_out;
}
arma::mat Unscented_filter::get_P_x_pred() const
{
return P_x_pred_out;
}
arma::mat Unscented_filter::get_x_est() const
{
return x_est;
}
arma::mat Unscented_filter::get_P_x_est() const
{
return P_x_est;
}
/***************** END UNSCENTED KALMAN FILTER *****************/

52
src/algorithms/tracking/libs/cubature_filter.h → src/algorithms/tracking/libs/nonlinear_tracking.h
View File

@@ -1,10 +1,12 @@
/*!
* \file cubature_filter.h
* \brief Interface of a library with Bayesian noise statistic estimation
* \file nonlinear_tracking.h
* \brief Interface of a library for nonlinear tracking algorithms
*
* Cubature_Filter implements the functionality of the Cubature Kalman
* Filter, which uses multidimensional cubature rules to estimate the
* time evolution of a nonlinear system.
* time evolution of a nonlinear system. Unscented_filter implements
* an Unscented Kalman Filter which uses Unscented Transform rules to
* perform a similar estimation.
*
* [1] I Arasaratnam and S Haykin. Cubature kalman filters. IEEE
* Transactions on Automatic Control, 54(6):1254–1269,2009.
@@ -38,18 +40,19 @@
* -------------------------------------------------------------------------
*/
#ifndef GNSS_SDR_CUBATURE_FILTER_H_
#define GNSS_SDR_CUBATURE_FILTER_H_
#ifndef GNSS_SDR_NONLINEAR_TRACKING_H_
#define GNSS_SDR_NONLINEAR_TRACKING_H_
#include <armadillo>
#include <gnuradio/gr_complex.h>
// Abstract model function
class Model_Function{
public:
Model_Function() {};
virtual arma::vec operator() (arma::vec input) = 0;
virtual ~Model_Function() = default;
class Model_Function
{
public:
Model_Function(){};
virtual arma::vec operator()(arma::vec input) = 0;
virtual ~Model_Function() = default;
};
class Cubature_filter
@@ -81,4 +84,33 @@ private:
arma::mat P_x_est;
};
class Unscented_filter
{
public:
// Constructors and destructors
Unscented_filter();
Unscented_filter(int nx);
Unscented_filter(const arma::vec& x_pred_0, const arma::mat& P_x_pred_0);
~Unscented_filter();
// Reinitialization function
void initialize(const arma::mat& x_pred_0, const arma::mat& P_x_pred_0);
// Prediction and estimation
void predict_sequential(const arma::vec& x_post, const arma::mat& P_x_post, Model_Function* transition_fcn, const arma::mat& noise_covariance);
void update_sequential(const arma::vec& z_upd, const arma::vec& x_pred, const arma::mat& P_x_pred, Model_Function* measurement_fcn, const arma::mat& noise_covariance);
// Getters
arma::mat get_x_pred() const;
arma::mat get_P_x_pred() const;
arma::mat get_x_est() const;
arma::mat get_P_x_est() const;
private:
arma::vec x_pred_out;
arma::mat P_x_pred_out;
arma::vec x_est;
arma::mat P_x_est;
};
#endif

14
src/tests/CMakeLists.txt
View File

@@ -161,6 +161,11 @@ if(ENABLE_FPGA)
add_definitions(-DFPGA_BLOCKS_TEST=1)
endif()
if(ARMADILLO_VERSION_STRING VERSION_GREATER 8.400)
# mvnrnd() requires 8.400
add_definitions(-DARMADILLO_HAVE_MVNRND=1)
endif()
find_package(Gnuplot)
if(GNUPLOT_FOUND)
add_definitions(-DGNUPLOT_EXECUTABLE="${GNUPLOT_EXECUTABLE}")
@@ -793,13 +798,20 @@ endif()
#########################################################
if(NOT ENABLE_PACKAGING AND NOT ENABLE_FPGA)
set(NONLINEAR_SOURCES "")
if(ARMADILLO_VERSION_STRING VERSION_GREATER 8.400)
set(NONLINEAR_SOURCES
${CMAKE_CURRENT_SOURCE_DIR}/unit-tests/signal-processing-blocks/tracking/cubature_filter_test.cc
${CMAKE_CURRENT_SOURCE_DIR}/unit-tests/signal-processing-blocks/tracking/unscented_filter_test.cc
)
endif()
add_executable(trk_test
${CMAKE_CURRENT_SOURCE_DIR}/single_test_main.cc
${CMAKE_CURRENT_SOURCE_DIR}/unit-tests/signal-processing-blocks/tracking/galileo_e1_dll_pll_veml_tracking_test.cc
${CMAKE_CURRENT_SOURCE_DIR}/unit-tests/signal-processing-blocks/tracking/tracking_loop_filter_test.cc
${CMAKE_CURRENT_SOURCE_DIR}/unit-tests/signal-processing-blocks/tracking/cpu_multicorrelator_real_codes_test.cc
${CMAKE_CURRENT_SOURCE_DIR}/unit-tests/signal-processing-blocks/tracking/bayesian_estimation_test.cc
${CMAKE_CURRENT_SOURCE_DIR}/unit-tests/signal-processing-blocks/tracking/cubature_filter_test.cc
${NONLINEAR_SOURCES}
)
if(${FILESYSTEM_FOUND})
target_compile_definitions(trk_test PRIVATE -DHAS_STD_FILESYSTEM=1)

3
src/tests/test_main.cc
View File

@@ -99,7 +99,10 @@ DECLARE_string(log_dir);
#endif
#include "unit-tests/signal-processing-blocks/tracking/bayesian_estimation_test.cc"
#if ARMADILLO_HAVE_MVNRND
#include "unit-tests/signal-processing-blocks/tracking/cubature_filter_test.cc"
#include "unit-tests/signal-processing-blocks/tracking/unscented_filter_test.cc"
#endif
#include "unit-tests/signal-processing-blocks/tracking/cpu_multicorrelator_real_codes_test.cc"
#include "unit-tests/signal-processing-blocks/tracking/cpu_multicorrelator_test.cc"
#include "unit-tests/signal-processing-blocks/tracking/galileo_e1_dll_pll_veml_tracking_test.cc"

11
src/tests/unit-tests/signal-processing-blocks/tracking/cubature_filter_test.cc
View File

@@ -28,12 +28,13 @@
* -------------------------------------------------------------------------
*/
#include "cubature_filter.h"
#include "nonlinear_tracking.h"
#include <armadillo>
#include <gtest/gtest.h>
#include <random>
#define CUBATURE_TEST_N_TRIALS 1000
#define CUBATURE_TEST_TOLERANCE 0.01
class Transition_Model : public Model_Function
{
@@ -127,8 +128,8 @@ TEST(CubatureFilterComputationTest, CubatureFilterTest)
kf_x_pre = kf_F * kf_x_post;
kf_P_x_pre = kf_F * kf_P_x_post * kf_F.t() + kf_Q;
EXPECT_TRUE(arma::approx_equal(ckf_x_pre, kf_x_pre, "absdiff", 0.01));
EXPECT_TRUE(arma::approx_equal(ckf_P_x_pre, kf_P_x_pre, "absdiff", 0.01));
EXPECT_TRUE(arma::approx_equal(ckf_x_pre, kf_x_pre, "absdiff", CUBATURE_TEST_TOLERANCE));
EXPECT_TRUE(arma::approx_equal(ckf_P_x_pre, kf_P_x_pre, "absdiff", CUBATURE_TEST_TOLERANCE));
// Update Step
kf_H = arma::randu<arma::mat>(ny, nx);
@@ -151,8 +152,8 @@ TEST(CubatureFilterComputationTest, CubatureFilterTest)
kf_x_post = kf_x_pre + kf_K * (kf_y - kf_H * kf_x_pre);
kf_P_x_post = (arma::eye(nx, nx) - kf_K * kf_H) * kf_P_x_pre;
EXPECT_TRUE(arma::approx_equal(ckf_x_post, kf_x_post, "absdiff", 0.01));
EXPECT_TRUE(arma::approx_equal(ckf_P_x_post, kf_P_x_post, "absdiff", 0.01));
EXPECT_TRUE(arma::approx_equal(ckf_x_post, kf_x_post, "absdiff", CUBATURE_TEST_TOLERANCE));
EXPECT_TRUE(arma::approx_equal(ckf_P_x_post, kf_P_x_post, "absdiff", CUBATURE_TEST_TOLERANCE));
delete transition_function;
delete measurement_function;

161
src/tests/unit-tests/signal-processing-blocks/tracking/unscented_filter_test.cc Normal file
View File

@@ -0,0 +1,161 @@
/*!
* \file unscented_filter_test.cc
* \brief This file implements numerical accuracy test for the CKF library.
* \author Gerald LaMountain, 2019. gerald(at)ece.neu.edu
*
* -------------------------------------------------------------------------
*
* Copyright (C) 2010-2019 (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 <https://www.gnu.org/licenses/>.
*
* -------------------------------------------------------------------------
*/
#include "nonlinear_tracking.h"
#include <armadillo>
#include <gtest/gtest.h>
#include <random>
#define UNSCENTED_TEST_N_TRIALS 10
#define UNSCENTED_TEST_TOLERANCE 10
class Transition_Model_UKF : public Model_Function
{
public:
Transition_Model_UKF(arma::mat kf_F) { coeff_mat = kf_F; };
virtual arma::vec operator()(arma::vec input) { return coeff_mat * input; };
private:
arma::mat coeff_mat;
};
class Measurement_Model_UKF : public Model_Function
{
public:
Measurement_Model_UKF(arma::mat kf_H) { coeff_mat = kf_H; };
virtual arma::vec operator()(arma::vec input) { return coeff_mat * input; };
private:
arma::mat coeff_mat;
};
TEST(UnscentedFilterComputationTest, UnscentedFilterTest)
{
Unscented_filter kf_unscented;
arma::vec kf_x;
arma::mat kf_P_x;
arma::vec kf_x_pre;
arma::mat kf_P_x_pre;
arma::vec ukf_x_pre;
arma::mat ukf_P_x_pre;
arma::vec kf_x_post;
arma::mat kf_P_x_post;
arma::vec ukf_x_post;
arma::mat ukf_P_x_post;
arma::mat kf_F;
arma::mat kf_H;
arma::mat kf_Q;
arma::mat kf_R;
arma::vec eta;
arma::vec nu;
arma::vec kf_y;
arma::mat kf_P_y;
arma::mat kf_K;
Model_Function* transition_function;
Model_Function* measurement_function;
//--- Perform initializations ------------------------------
std::random_device r;
std::default_random_engine e1(r());
std::normal_distribution<float> normal_dist(0, 5);
std::uniform_real_distribution<float> uniform_dist(0.1, 5.0);
uint8_t nx = 0;
uint8_t ny = 0;
for (uint16_t k = 0; k < UNSCENTED_TEST_N_TRIALS; k++)
{
nx = std::rand() % 5 + 1;
ny = std::rand() % 5 + 1;
kf_x = arma::randn<arma::vec>(nx, 1);
kf_P_x_post = 5.0 * arma::diagmat(arma::randu<arma::vec>(nx, 1));
kf_x_post = arma::mvnrnd(kf_x, kf_P_x_post);
kf_unscented.initialize(kf_x_post, kf_P_x_post);
// Prediction Step
kf_F = arma::randu<arma::mat>(nx, nx);
kf_Q = arma::diagmat(arma::randu<arma::vec>(nx, 1));
transition_function = new Transition_Model_UKF(kf_F);
arma::mat ttx = (*transition_function)(kf_x_post);
kf_unscented.predict_sequential(kf_x_post, kf_P_x_post, transition_function, kf_Q);
ukf_x_pre = kf_unscented.get_x_pred();
ukf_P_x_pre = kf_unscented.get_P_x_pred();
kf_x_pre = kf_F * kf_x_post;
kf_P_x_pre = kf_F * kf_P_x_post * kf_F.t() + kf_Q;
EXPECT_TRUE(arma::approx_equal(ukf_x_pre, kf_x_pre, "absdiff", UNSCENTED_TEST_TOLERANCE));
EXPECT_TRUE(arma::approx_equal(ukf_P_x_pre, kf_P_x_pre, "absdiff", UNSCENTED_TEST_TOLERANCE));
// Update Step
kf_H = arma::randu<arma::mat>(ny, nx);
kf_R = arma::diagmat(arma::randu<arma::vec>(ny, 1));
eta = arma::mvnrnd(arma::zeros<arma::vec>(nx, 1), kf_Q);
nu = arma::mvnrnd(arma::zeros<arma::vec>(ny, 1), kf_R);
kf_y = kf_H * (kf_F * kf_x + eta) + nu;
measurement_function = new Measurement_Model_UKF(kf_H);
kf_unscented.update_sequential(kf_y, kf_x_pre, kf_P_x_pre, measurement_function, kf_R);
ukf_x_post = kf_unscented.get_x_est();
ukf_P_x_post = kf_unscented.get_P_x_est();
kf_P_y = kf_H * kf_P_x_pre * kf_H.t() + kf_R;
kf_K = (kf_P_x_pre * kf_H.t()) * arma::inv(kf_P_y);
kf_x_post = kf_x_pre + kf_K * (kf_y - kf_H * kf_x_pre);
kf_P_x_post = (arma::eye(nx, nx) - kf_K * kf_H) * kf_P_x_pre;
EXPECT_TRUE(arma::approx_equal(ukf_x_post, kf_x_post, "absdiff", UNSCENTED_TEST_TOLERANCE));
EXPECT_TRUE(arma::approx_equal(ukf_P_x_post, kf_P_x_post, "absdiff", UNSCENTED_TEST_TOLERANCE));
delete transition_function;
delete measurement_function;
}
}