/**************************************************************************** * * Copyright (c) 2022 PX4 Development Team. All rights reserved. * * Redistribution and use in source and binary forms, with or without * modification, are permitted provided that the following conditions * are met: * * 1. Redistributions of source code must retain the above copyright * notice, this list of conditions and the following disclaimer. * 2. Redistributions in binary form must reproduce the above copyright * notice, this list of conditions and the following disclaimer in * the documentation and/or other materials provided with the * distribution. * 3. Neither the name PX4 nor the names of its contributors may be * used to endorse or promote products derived from this software * without specific prior written permission. * * THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS * "AS IS" AND ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT * LIMITED TO, THE IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS * FOR A PARTICULAR PURPOSE ARE DISCLAIMED. IN NO EVENT SHALL THE * COPYRIGHT OWNER OR CONTRIBUTORS BE LIABLE FOR ANY DIRECT, INDIRECT, * INCIDENTAL, SPECIAL, EXEMPLARY, OR CONSEQUENTIAL DAMAGES (INCLUDING, * BUT NOT LIMITED TO, PROCUREMENT OF SUBSTITUTE GOODS OR SERVICES; LOSS * OF USE, DATA, OR PROFITS; OR BUSINESS INTERRUPTION) HOWEVER CAUSED * AND ON ANY THEORY OF LIABILITY, WHETHER IN CONTRACT, STRICT * LIABILITY, OR TORT (INCLUDING NEGLIGENCE OR OTHERWISE) ARISING IN * ANY WAY OUT OF THE USE OF THIS SOFTWARE, EVEN IF ADVISED OF THE * POSSIBILITY OF SUCH DAMAGE. * ****************************************************************************/ /** * Test the fusion of body frame specific forces for the estimation of wind speed */ #include #include "EKF/ekf.h" #include "sensor_simulator/sensor_simulator.h" #include "sensor_simulator/ekf_wrapper.h" class EkfDragFusionTest : public ::testing::Test { public: EkfDragFusionTest(): ::testing::Test(), _ekf{std::make_shared()}, _sensor_simulator(_ekf), _ekf_wrapper(_ekf), _quat_sim(Eulerf(0.0f, 0.0f, 0.0f)) {}; std::shared_ptr _ekf; SensorSimulator _sensor_simulator; EkfWrapper _ekf_wrapper; const Quatf _quat_sim; // Setup the Ekf with synthetic measurements void SetUp() override { // run briefly to init, then manually set in air and at rest (default for a real vehicle) _ekf->init(0); _ekf->set_is_fixed_wing(false); _ekf->set_in_air_status(false); _ekf->set_vehicle_at_rest(true); } // Use this method to clean up any memory, network etc. after each test void TearDown() override { } }; TEST_F(EkfDragFusionTest, testForwardMomentumDrag) { const float pitch = math::radians(10.0f); const float roll = math::radians(0.0f); const Eulerf euler_angles_sim(roll, pitch, 0.0f); const Quatf quat_sim(euler_angles_sim); _sensor_simulator.simulateOrientation(quat_sim); _ekf_wrapper.enableGpsFusion(); _sensor_simulator.startGps(); const float bcoef_x = 0.0f; const float bcoef_y = 0.0f; const float mcoef = 0.15f; _ekf_wrapper.setDragFusionParameters(bcoef_x, bcoef_y, mcoef); _ekf_wrapper.enableDragFusion(); // simulate a vehicle that is hovering and tilting into wind _ekf->set_in_air_status(true); _ekf->set_vehicle_at_rest(false); // Wind estimation is slow when using drag fusion _sensor_simulator.runSeconds(90); EXPECT_TRUE(_ekf_wrapper.isWindVelocityEstimated()); const Vector2f vel_wind_earth = _ekf->getWindVelocity(); // drag acceleration = mcoef * airspeed Vector2f predicted_accel; predicted_accel(0) = CONSTANTS_ONE_G * sinf(pitch); predicted_accel(1) = - CONSTANTS_ONE_G * sinf(roll); Vector2f wind_speed = predicted_accel / mcoef; EXPECT_NEAR(vel_wind_earth(0), wind_speed(0), fmaxf(1.0f, 0.1f * fabsf(wind_speed(0)))); EXPECT_NEAR(vel_wind_earth(1), wind_speed(1), fmaxf(1.0f, 0.1f * fabsf(wind_speed(1)))); }; TEST_F(EkfDragFusionTest, testLateralMomentumDrag) { const float pitch = math::radians(0.0f); const float roll = math::radians(10.0f); const Eulerf euler_angles_sim(roll, pitch, 0.0f); const Quatf quat_sim(euler_angles_sim); _sensor_simulator.simulateOrientation(quat_sim); _ekf_wrapper.enableGpsFusion(); _sensor_simulator.startGps(); // Apply parameter changes required to do drag fusion wind estimation const float bcoef_x = 0.0f; const float bcoef_y = 0.0f; const float mcoef = 0.15f; _ekf_wrapper.setDragFusionParameters(bcoef_x, bcoef_y, mcoef); _ekf_wrapper.enableDragFusion(); // simulate a vehicle that is hovering and tilting into wind _ekf->set_in_air_status(true); _ekf->set_vehicle_at_rest(false); // Wind estimation is slow when using drag fusion _sensor_simulator.runSeconds(90); EXPECT_TRUE(_ekf_wrapper.isWindVelocityEstimated()); const Vector2f vel_wind_earth = _ekf->getWindVelocity(); // drag acceleration = mcoef * airspeed Vector2f predicted_accel; predicted_accel(0) = CONSTANTS_ONE_G * sinf(pitch); predicted_accel(1) = - CONSTANTS_ONE_G * sinf(roll); Vector2f wind_speed = predicted_accel / mcoef; EXPECT_NEAR(vel_wind_earth(0), wind_speed(0), fmaxf(1.0f, 0.1f * fabsf(wind_speed(0)))); EXPECT_NEAR(vel_wind_earth(1), wind_speed(1), fmaxf(1.0f, 0.1f * fabsf(wind_speed(1)))); }; TEST_F(EkfDragFusionTest, testForwardBluffBodyDrag) { const float roll = math::radians(0.0f); const float pitch = math::radians(-10.0f); const Eulerf euler_angles_sim(roll, pitch, 0.0f); const Quatf quat_sim(euler_angles_sim); _sensor_simulator.simulateOrientation(quat_sim); _ekf_wrapper.enableGpsFusion(); _sensor_simulator.startGps(); // Apply parameter changes required to do drag fusion wind estimation const float bcoef_x = 70.0f; const float bcoef_y = 50.0f; const float mcoef = 0.0f; _ekf_wrapper.setDragFusionParameters(bcoef_x, bcoef_y, mcoef); _ekf_wrapper.enableDragFusion(); // simulate a vehicle that is hovering and tilting into wind _ekf->set_in_air_status(true); _ekf->set_vehicle_at_rest(false); // Wind estimation is slow when using drag fusion _sensor_simulator.runSeconds(90); EXPECT_TRUE(_ekf_wrapper.isWindVelocityEstimated()); const Vector2f vel_wind_earth = _ekf->getWindVelocity(); Vector2f predicted_accel(CONSTANTS_ONE_G * sinf(pitch), 0.0f); const float airspeed = sqrtf((2.0f * bcoef_x * predicted_accel.length()) / CONSTANTS_AIR_DENSITY_SEA_LEVEL_15C); Vector2f wind_speed(-airspeed, 0.0f); // The magnitude of error perpendicular to wind is equivalent to the error in the direction of wind // which is why we use the same threshold for each axis. EXPECT_NEAR(vel_wind_earth(0), wind_speed(0), 1.0f); EXPECT_NEAR(vel_wind_earth(1), wind_speed(1), 1.0f); }; TEST_F(EkfDragFusionTest, testLateralBluffBodyDrag) { const float roll = math::radians(10.0f); const float pitch = math::radians(0.0f); const Eulerf euler_angles_sim(roll, pitch, 0.0f); const Quatf quat_sim(euler_angles_sim); _sensor_simulator.simulateOrientation(quat_sim); _ekf_wrapper.enableGpsFusion(); _sensor_simulator.startGps(); // Apply parameter changes required to do drag fusion wind estimation const float bcoef_x = 70.0f; const float bcoef_y = 50.0f; const float mcoef = 0.0f; _ekf_wrapper.setDragFusionParameters(bcoef_x, bcoef_y, mcoef); _ekf_wrapper.enableDragFusion(); // simulate a vehicle that is hovering and tilting into wind _ekf->set_in_air_status(true); _ekf->set_vehicle_at_rest(false); // Wind estimation is slow when using drag fusion _sensor_simulator.runSeconds(90); EXPECT_TRUE(_ekf_wrapper.isWindVelocityEstimated()); const Vector2f vel_wind_earth = _ekf->getWindVelocity(); Vector2f predicted_accel(0.0f, - CONSTANTS_ONE_G * sinf(roll)); const float airspeed = sqrtf((2.0f * bcoef_y * predicted_accel.length()) / CONSTANTS_AIR_DENSITY_SEA_LEVEL_15C); Vector2f wind_speed(0.0f, -airspeed); // The magnitude of error perpendicular to wind is equivalent to the error in the of wind // which is why we use the same threshold for each axis. EXPECT_NEAR(vel_wind_earth(0), wind_speed(0), 1.0f); EXPECT_NEAR(vel_wind_earth(1), wind_speed(1), 1.0f); }; TEST_F(EkfDragFusionTest, testDiagonalBluffBodyDrag) { const float roll = math::radians(-10.0f); const float pitch = math::radians(-10.0f); const Eulerf euler_angles_sim(roll, pitch, 0.f); const Quatf quat_sim(euler_angles_sim); _sensor_simulator.simulateOrientation(quat_sim); _ekf_wrapper.enableGpsFusion(); _sensor_simulator.startGps(); // Apply parameter changes required to do drag fusion wind estimation const float bcoef_x = 50.0f; const float bcoef_y = 50.0f; const float mcoef = 0.0f; _ekf_wrapper.setDragFusionParameters(bcoef_x, bcoef_y, mcoef); _ekf_wrapper.enableDragFusion(); // simulate a vehicle that is hovering and tilting into wind _ekf->set_in_air_status(true); _ekf->set_vehicle_at_rest(false); // Wind estimation is slow when using drag fusion _sensor_simulator.runSeconds(90); EXPECT_TRUE(_ekf_wrapper.isWindVelocityEstimated()); const Vector2f vel_wind_earth = _ekf->getWindVelocity(); Vector2f predicted_accel = quat_sim.rotateVectorInverse(Vector3f(0.f, 0.f, -CONSTANTS_ONE_G)).xy(); const float airspeed = sqrtf((2.0f * bcoef_y * predicted_accel.norm()) / CONSTANTS_AIR_DENSITY_SEA_LEVEL_15C); Vector2f wind_speed(airspeed * predicted_accel / predicted_accel.norm()); // The magnitude of error perpendicular to wind is equivalent to the error in the of wind // which is why we use the same threshold for each axis. EXPECT_NEAR(vel_wind_earth(0), wind_speed(0), 1.0f); EXPECT_NEAR(vel_wind_earth(1), wind_speed(1), 1.0f); };