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255 lines
9.0 KiB
C++
255 lines
9.0 KiB
C++
/****************************************************************************
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*
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* Copyright (c) 2022 PX4 Development Team. All rights reserved.
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*
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* Redistribution and use in source and binary forms, with or without
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* modification, are permitted provided that the following conditions
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* are met:
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*
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* 1. Redistributions of source code must retain the above copyright
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* notice, this list of conditions and the following disclaimer.
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* 2. Redistributions in binary form must reproduce the above copyright
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* notice, this list of conditions and the following disclaimer in
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* the documentation and/or other materials provided with the
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* distribution.
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* 3. Neither the name PX4 nor the names of its contributors may be
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* used to endorse or promote products derived from this software
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* without specific prior written permission.
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*
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* THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS
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* "AS IS" AND ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT
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* LIMITED TO, THE IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS
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* FOR A PARTICULAR PURPOSE ARE DISCLAIMED. IN NO EVENT SHALL THE
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* COPYRIGHT OWNER OR CONTRIBUTORS BE LIABLE FOR ANY DIRECT, INDIRECT,
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* INCIDENTAL, SPECIAL, EXEMPLARY, OR CONSEQUENTIAL DAMAGES (INCLUDING,
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* BUT NOT LIMITED TO, PROCUREMENT OF SUBSTITUTE GOODS OR SERVICES; LOSS
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* OF USE, DATA, OR PROFITS; OR BUSINESS INTERRUPTION) HOWEVER CAUSED
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* AND ON ANY THEORY OF LIABILITY, WHETHER IN CONTRACT, STRICT
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* LIABILITY, OR TORT (INCLUDING NEGLIGENCE OR OTHERWISE) ARISING IN
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* ANY WAY OUT OF THE USE OF THIS SOFTWARE, EVEN IF ADVISED OF THE
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* POSSIBILITY OF SUCH DAMAGE.
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*
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****************************************************************************/
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/**
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* Accelerometer failure handling (bias, clipping, ...)
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*/
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#include <gtest/gtest.h>
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#include "EKF/ekf.h"
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#include "sensor_simulator/sensor_simulator.h"
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#include "sensor_simulator/ekf_wrapper.h"
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#include "test_helper/reset_logging_checker.h"
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class EkfAccelerometerTest : public ::testing::Test
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{
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public:
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EkfAccelerometerTest(): ::testing::Test(),
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_ekf{std::make_shared<Ekf>()},
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_sensor_simulator(_ekf),
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_ekf_wrapper(_ekf) {};
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std::shared_ptr<Ekf> _ekf;
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SensorSimulator _sensor_simulator;
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EkfWrapper _ekf_wrapper;
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// Setup the Ekf with synthetic measurements
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void SetUp() override
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{
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// run briefly to init, then manually set in air and at rest (default for a real vehicle)
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_ekf->init(0);
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_sensor_simulator.runSeconds(0.1);
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_ekf->set_in_air_status(false);
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_ekf->set_vehicle_at_rest(true);
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_sensor_simulator.runSeconds(7);
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}
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// Use this method to clean up any memory, network etc. after each test
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void TearDown() override
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{
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}
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void testBias(float bias, float duration, float tolerance);
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};
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void EkfAccelerometerTest::testBias(float bias, float duration, float tolerance)
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{
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_sensor_simulator._imu.setAccelData(Vector3f(0.f, 0.f, -CONSTANTS_ONE_G + bias));
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_sensor_simulator.runSeconds(duration);
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Vector3f estimated_bias = _ekf->getAccelBias();
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EXPECT_TRUE(matrix::isEqual(estimated_bias, Vector3f(0.f, 0.f, bias),
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tolerance)) << "bias = " << bias << ", estimated = " << estimated_bias(2);
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}
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TEST_F(EkfAccelerometerTest, biasEstimateZero)
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{
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testBias(0.f, 10, 0.f);
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}
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TEST_F(EkfAccelerometerTest, biasEstimatePositive)
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{
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// The estimate should track a slowly changing bias
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const float biases[4] = {0.1f, 0.2f, 0.3f, 0.38f};
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for (int i = 0; i < 4; i ++) {
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testBias(biases[i], 10, 0.03f);
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}
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}
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TEST_F(EkfAccelerometerTest, biasEstimateNegative)
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{
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const float biases[4] = {-0.12f, -0.22f, -0.31, -0.4f};
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for (int i = 0; i < 4; i ++) {
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testBias(biases[i], 10, 0.03f);
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}
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}
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TEST_F(EkfAccelerometerTest, imuFallingDetectionBaroOnly)
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{
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// GIVEN: an accelerometer with a really large Z bias
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const float bias = CONSTANTS_ONE_G;
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_sensor_simulator._imu.setAccelData(Vector3f(0.f, 0.f, -CONSTANTS_ONE_G + bias));
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_sensor_simulator.runSeconds(2);
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// WHEN: there is only one source of vertical aiding
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// THEN: the estimator cannot know which one is wrong
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EXPECT_FALSE(_ekf->fault_status_flags().bad_acc_vertical);
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// BUT WHEN: the accelerometer also reports clipping on the Z axis
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_sensor_simulator._imu.setAccelClipping(false, false, true);
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_sensor_simulator.runSeconds(2);
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// THEN: a single source is enough to detect a bad acceleration
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EXPECT_TRUE(_ekf->fault_status_flags().bad_acc_vertical);
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}
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TEST_F(EkfAccelerometerTest, imuFallingDetectionBaroGnssVel)
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{
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// GIVEN: Baro and GNSS velocity fusion
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_sensor_simulator.startGps();
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_ekf_wrapper.enableGpsFusion();
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_sensor_simulator.runSeconds(15);
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EXPECT_TRUE(_ekf_wrapper.isIntendingBaroHeightFusion());
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EXPECT_TRUE(_ekf_wrapper.isIntendingGpsFusion());
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// AND: an accelerometer with a really large Z bias
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const float bias = CONSTANTS_ONE_G;
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_sensor_simulator._imu.setAccelData(Vector3f(0.f, 0.f, -CONSTANTS_ONE_G + bias));
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_sensor_simulator.runSeconds(2);
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// THEN: the bad vertical acceleration is detected
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EXPECT_TRUE(_ekf->fault_status_flags().bad_acc_vertical);
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// AND WHEN: the accelerometer also reports clipping on the Z axis
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_sensor_simulator._imu.setAccelClipping(false, false, true);
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_sensor_simulator.runSeconds(2);
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// THEN: the bad vertical acceleration is still detected
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EXPECT_TRUE(_ekf->fault_status_flags().bad_acc_vertical);
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}
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TEST_F(EkfAccelerometerTest, imuFallingDetectionGnssOnly)
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{
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// GIVEN: GNSS height and velocity fusion
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_sensor_simulator.startGps();
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_ekf_wrapper.enableGpsFusion();
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_ekf_wrapper.enableGpsHeightFusion();
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_ekf_wrapper.disableBaroHeightFusion();
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_sensor_simulator.runSeconds(15);
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EXPECT_FALSE(_ekf_wrapper.isIntendingBaroHeightFusion());
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EXPECT_TRUE(_ekf_wrapper.isIntendingGpsFusion());
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EXPECT_TRUE(_ekf_wrapper.isIntendingGpsHeightFusion());
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// AND: an accelerometer with a really large Z bias
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const float bias = CONSTANTS_ONE_G;
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_sensor_simulator._imu.setAccelData(Vector3f(0.f, 0.f, -CONSTANTS_ONE_G + bias));
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_sensor_simulator.runSeconds(2);
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// THEN: the bad vertical acceleration is not detected because both sources are of the same type
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EXPECT_FALSE(_ekf->fault_status_flags().bad_acc_vertical);
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// BUT WHEN: the accelerometer also reports clipping on the Z axis
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_sensor_simulator._imu.setAccelClipping(false, false, true);
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_sensor_simulator.runSeconds(2);
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// THEN: a single source is enough to detect a bad acceleration
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EXPECT_TRUE(_ekf->fault_status_flags().bad_acc_vertical);
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}
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TEST_F(EkfAccelerometerTest, imuFallingDetectionBaroRange)
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{
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// GIVEN: baro and range height fusion
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_sensor_simulator._rng.setData(1.f, 100);
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_sensor_simulator._rng.setLimits(0.1f, 9.f);
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_sensor_simulator.startRangeFinder();
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_ekf_wrapper.enableRangeHeightFusion();
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_sensor_simulator.runSeconds(5);
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EXPECT_TRUE(_ekf_wrapper.isIntendingBaroHeightFusion());
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EXPECT_TRUE(_ekf_wrapper.isIntendingRangeHeightFusion());
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// AND: an accelerometer with a really large Z bias
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const float bias = CONSTANTS_ONE_G;
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_sensor_simulator._imu.setAccelData(Vector3f(0.f, 0.f, -CONSTANTS_ONE_G + bias));
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_sensor_simulator.runSeconds(2);
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// THEN: the bad vertical is detected because both sources agree
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EXPECT_TRUE(_ekf->fault_status_flags().bad_acc_vertical);
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}
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TEST_F(EkfAccelerometerTest, imuFallingDetectionBaroEvVel)
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{
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// GIVEN: baro and EV vel fusion
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_ekf_wrapper.enableExternalVisionVelocityFusion();
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_sensor_simulator.startExternalVision();
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_sensor_simulator.runSeconds(1);
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EXPECT_TRUE(_ekf_wrapper.isIntendingBaroHeightFusion());
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EXPECT_TRUE(_ekf_wrapper.isIntendingExternalVisionVelocityFusion());
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EXPECT_FALSE(_ekf_wrapper.isIntendingExternalVisionPositionFusion());
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// AND: an accelerometer with a really large Z bias
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const float bias = CONSTANTS_ONE_G;
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_sensor_simulator._imu.setAccelData(Vector3f(0.f, 0.f, -CONSTANTS_ONE_G + bias));
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_sensor_simulator.runSeconds(2);
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// THEN: the bad vertical is detected because both sources agree
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EXPECT_TRUE(_ekf->fault_status_flags().bad_acc_vertical);
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}
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TEST_F(EkfAccelerometerTest, imuFallingDetectionEvVelHgt)
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{
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// GIVEN: EV height and vel fusion
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_ekf_wrapper.enableExternalVisionVelocityFusion();
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_ekf_wrapper.enableExternalVisionHeightFusion();
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_sensor_simulator.startExternalVision();
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_ekf_wrapper.disableBaroHeightFusion();
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_sensor_simulator.runSeconds(1);
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EXPECT_TRUE(_ekf_wrapper.isIntendingExternalVisionVelocityFusion());
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EXPECT_TRUE(_ekf_wrapper.isIntendingExternalVisionHeightFusion());
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EXPECT_FALSE(_ekf_wrapper.isIntendingExternalVisionPositionFusion());
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EXPECT_FALSE(_ekf_wrapper.isIntendingBaroHeightFusion());
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// AND: an accelerometer with a really large Z bias
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const float bias = CONSTANTS_ONE_G;
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_sensor_simulator._imu.setAccelData(Vector3f(0.f, 0.f, -CONSTANTS_ONE_G + bias));
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_sensor_simulator.runSeconds(2);
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// THEN: the bad vertical acceleration is not detected because both sources are of the same type
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EXPECT_FALSE(_ekf->fault_status_flags().bad_acc_vertical);
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// BUT WHEN: the accelerometer also reports clipping on the Z axis
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_sensor_simulator._imu.setAccelClipping(false, false, true);
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_sensor_simulator.runSeconds(2);
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// THEN: a single source is enough to detect a bad acceleration
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EXPECT_TRUE(_ekf->fault_status_flags().bad_acc_vertical);
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}
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