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ekf: split accel bias learning in independant xyz components (#817)

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This is a non-functional change required to select accel bias estimation
per axis selection. The intent is then to disable the learning before
takeoff of the components that are poorly observable.
This commit is contained in:
Mathieu Bresciani
2020-05-15 09:20:27 +02:00
committed by GitHub
parent 19bbea75c0
commit 9788c3bdf2
3 changed files with 74 additions and 89 deletions
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test/test_EKF_initialization.cpp
+6 -6
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@@ -99,14 +99,14 @@ class EkfInitializationTest : public ::testing::Test {
const Vector3f vel_var = _ekf->getVelocityVariance();
const float pos_variance_limit = 0.2f;
EXPECT_TRUE(pos_var(0) > pos_variance_limit) << "pos_var(1)" << pos_var(0);
EXPECT_TRUE(pos_var(1) > pos_variance_limit) << "pos_var(2)" << pos_var(1);
EXPECT_TRUE(pos_var(2) > pos_variance_limit) << "pos_var(3)" << pos_var(2);
EXPECT_TRUE(pos_var(0) > pos_variance_limit) << "pos_var(0)" << pos_var(0);
EXPECT_TRUE(pos_var(1) > pos_variance_limit) << "pos_var(1)" << pos_var(1);
EXPECT_TRUE(pos_var(2) > pos_variance_limit) << "pos_var(2)" << pos_var(2);
const float vel_variance_limit = 0.4f;
EXPECT_TRUE(vel_var(0) > vel_variance_limit) << "vel_var(1)" << vel_var(0);
EXPECT_TRUE(vel_var(1) > vel_variance_limit) << "vel_var(2)" << vel_var(1);
EXPECT_TRUE(vel_var(2) > vel_variance_limit) << "vel_var(3)" << vel_var(2);
EXPECT_TRUE(vel_var(0) > vel_variance_limit) << "vel_var(0)" << vel_var(0);
EXPECT_TRUE(vel_var(1) > vel_variance_limit) << "vel_var(1)" << vel_var(1);
EXPECT_TRUE(vel_var(2) > vel_variance_limit) << "vel_var(2)" << vel_var(2);
}
};