diff --git a/gtsam/navigation/CombinedImuFactor.cpp b/gtsam/navigation/CombinedImuFactor.cpp
index 21bfcbd1e..b65810aae 100644
--- a/gtsam/navigation/CombinedImuFactor.cpp
+++ b/gtsam/navigation/CombinedImuFactor.cpp
@@ -66,14 +66,14 @@ void PreintegratedCombinedMeasurements::resetIntegration() {
 
 //------------------------------------------------------------------------------
 void PreintegratedCombinedMeasurements::integrateMeasurement(
-    const Vector3& measuredAcc, const Vector3& measuredOmega, double deltaT) {
+    const Vector3& measuredAcc, const Vector3& measuredOmega, double dt) {
   const Matrix3 dRij = deltaRij().matrix();  // expensive when quaternion
 
   // Update preintegrated measurements.
   Matrix3 D_incrR_integratedOmega;  // Right jacobian computed at theta_incr
   Matrix9 A;  // overall Jacobian wrt preintegrated measurements (df/dx)
   Matrix93 B, C;
-  PreintegrationBase::update(measuredAcc, measuredOmega, deltaT,
+  PreintegrationBase::update(measuredAcc, measuredOmega, dt,
                              &D_incrR_integratedOmega, &A, &B, &C);
 
   // Update preintegrated measurements covariance: as in [2] we consider a first
@@ -83,8 +83,8 @@ void PreintegratedCombinedMeasurements::integrateMeasurement(
   // and preintegrated measurements
 
   // Single Jacobians to propagate covariance
-  Matrix3 H_vel_biasacc = -dRij * deltaT;
-  Matrix3 H_angles_biasomega = -D_incrR_integratedOmega * deltaT;
+  Matrix3 H_vel_biasacc = -dRij * dt;
+  Matrix3 H_angles_biasomega = -D_incrR_integratedOmega * dt;
 
   // overall Jacobian wrt preintegrated measurements (df/dx)
   Eigen::Matrix<double, 15, 15> F;
@@ -94,24 +94,27 @@ void PreintegratedCombinedMeasurements::integrateMeasurement(
   F.block<3, 3>(6, 9) = H_vel_biasacc;
   F.block<6, 6>(9, 9) = I_6x6;
 
+  // propagate uncertainty
+  // TODO(frank): use noiseModel routine so we can have arbitrary noise models.
+  const Matrix3& aCov = p().accelerometerCovariance;
+  const Matrix3& wCov = p().gyroscopeCovariance;
+  const Matrix3& iCov = p().integrationCovariance;
+
   // first order uncertainty propagation
-  // Optimized matrix multiplication   (1/deltaT) * G * measurementCovariance *
-  // G.transpose()
+  // Optimized matrix multiplication   (1/dt) * G * measurementCovariance * G.transpose()
   Eigen::Matrix<double, 15, 15> G_measCov_Gt;
   G_measCov_Gt.setZero(15, 15);
 
   // BLOCK DIAGONAL TERMS
-  D_t_t(&G_measCov_Gt) = deltaT * p().integrationCovariance;
-  D_v_v(&G_measCov_Gt) =
-      (1 / deltaT) * (H_vel_biasacc) *
-      (p().accelerometerCovariance + p().biasAccOmegaInit.block<3, 3>(0, 0)) *
-      (H_vel_biasacc.transpose());
-  D_R_R(&G_measCov_Gt) =
-      (1 / deltaT) * (H_angles_biasomega) *
-      (p().gyroscopeCovariance + p().biasAccOmegaInit.block<3, 3>(3, 3)) *
-      (H_angles_biasomega.transpose());
-  D_a_a(&G_measCov_Gt) = deltaT * p().biasAccCovariance;
-  D_g_g(&G_measCov_Gt) = deltaT * p().biasOmegaCovariance;
+  D_t_t(&G_measCov_Gt) = dt * iCov;
+  D_v_v(&G_measCov_Gt) = (1 / dt) * H_vel_biasacc *
+                         (aCov + p().biasAccOmegaInit.block<3, 3>(0, 0)) *
+                         (H_vel_biasacc.transpose());
+  D_R_R(&G_measCov_Gt) = (1 / dt) * H_angles_biasomega *
+                         (wCov + p().biasAccOmegaInit.block<3, 3>(3, 3)) *
+                         (H_angles_biasomega.transpose());
+  D_a_a(&G_measCov_Gt) = dt * p().biasAccCovariance;
+  D_g_g(&G_measCov_Gt) = dt * p().biasOmegaCovariance;
 
   // OFF BLOCK DIAGONAL TERMS
   Matrix3 temp = H_vel_biasacc * p().biasAccOmegaInit.block<3, 3>(3, 0) *