diff --git a/selfdrive/locationd/kalman/models/car_kf.py b/selfdrive/locationd/kalman/models/car_kf.py
index 4adb8c291..b31affa42 100755
--- a/selfdrive/locationd/kalman/models/car_kf.py
+++ b/selfdrive/locationd/kalman/models/car_kf.py
@@ -46,22 +46,22 @@ class CarKalman():
 
   # state covariance
   P_initial = np.diag([
-    .1**2,
-    .1**2,
+    0.1**2,
+    0.1**2,
     math.radians(0.1)**2,
     math.radians(0.1)**2,
 
     10**2, 10**2,
-    1**2,
-    1**2,
+    1.0**2,
+    1.0**2,
   ])
 
   # process noise
   Q = np.diag([
-    (.05/10)**2,
+    (.05/100)**2,
     .0001**2,
-    math.radians(0.01)**2,
-    math.radians(0.2)**2,
+    math.radians(0.001)**2,
+    math.radians(0.05)**2,
 
     .1**2, .1**2,
     math.radians(0.1)**2,
diff --git a/selfdrive/locationd/paramsd.py b/selfdrive/locationd/paramsd.py
index 375ae4ad4..80eddedf3 100755
--- a/selfdrive/locationd/paramsd.py
+++ b/selfdrive/locationd/paramsd.py
@@ -52,17 +52,17 @@ class ParamsLearner:
         self.kf.predict_and_observe(t,
                                     ObservationKind.ROAD_FRAME_XY_SPEED,
                                     np.array([[[v_calibrated[0], -v_calibrated[1]]]]),
-                                    np.array([np.diag([v_calibrated_std[0]**2, v_calibrated_std[1]**2])]))
+                                    np.array([np.diag([v_calibrated_std[0]**2, 1e6*v_calibrated_std[1]**2])]))
 
         self.kf.predict_and_observe(t, ObservationKind.ANGLE_OFFSET_FAST, np.array([[[0]]]))
 
         # Clamp values
-        x = self.kf.x
-        if not (10 < x[States.STEER_RATIO] < 25):
-          self.kf.predict_and_observe(t, ObservationKind.STEER_RATIO, np.array([[[15.0]]]))
+        # x = self.kf.x
+        # if not (10 < x[States.STEER_RATIO] < 25):
+        #   self.kf.predict_and_observe(t, ObservationKind.STEER_RATIO, np.array([[[15.0]]]))
 
-        if not (0.5 < x[States.STIFFNESS] < 3.0):
-          self.kf.predict_and_observe(t, ObservationKind.STIFFNESS, np.array([[[1.0]]]))
+        # if not (0.5 < x[States.STIFFNESS] < 3.0):
+        #   self.kf.predict_and_observe(t, ObservationKind.STIFFNESS, np.array([[[1.0]]]))
 
     elif which == 'carState':
       self.carstate_counter += 1
@@ -136,7 +136,7 @@ def main(sm=None, pm=None):
       msg.liveParameters.steerRatio = float(x[States.STEER_RATIO])
       msg.liveParameters.stiffnessFactor = float(x[States.STIFFNESS])
       msg.liveParameters.angleOffsetAverage = math.degrees(x[States.ANGLE_OFFSET])
-      msg.liveParameters.angleOffset = math.degrees(x[States.ANGLE_OFFSET_FAST])
+      msg.liveParameters.angleOffset = msg.liveParameters.angleOffsetAverage + math.degrees(x[States.ANGLE_OFFSET_FAST])
 
       i += 1
       if i % 6000 == 0:   # once a minute