Tuned input parameter so OD converges.

src/main/resources/maxvalier.in

@@ -69,17 +69,17 @@ orbit.date = 2019-06-11T16:35:29.149
 
 ### Cartesian elements
 ## Position along X in inertial frame (m)
-orbit.cartesian.px = -5423194
+orbit.cartesian.px = -5273194
 ## Position along Y in inertial frame (m)
-orbit.cartesian.py = -4550295
+orbit.cartesian.py = -4450295
 ## Position along Z in inertial frame (m)
-orbit.cartesian.pz = 250075
+orbit.cartesian.pz = 110075
 ## Velocity along X in inertial frame (m/s)
-orbit.cartesian.vx = -735
+orbit.cartesian.vx = -585
 ## Velocity along Y in inertial frame (m/s)
-orbit.cartesian.vy =  740
+orbit.cartesian.vy =  790
 ## Velocity along Z in inertial frame (m/s)
-orbit.cartesian.vz = 7760
+orbit.cartesian.vz = 7610
 
 ## TLE parameters
 #Line 1
@@ -272,7 +272,7 @@ estimator.optimization.engine = Levenberg-Marquardt
 # divided by estimator.orbital.parameters.position.scale. So if the initial guess
 # is about 100km wrong and estimator.orbital.parameters.position.scale is set to 10.0,
 # the initial step bound factor should be of the order of magnitude of 1.0e6
-estimator.Levenberg.Marquardt.initial.step.bound.factor = 1.0e6
+estimator.Levenberg.Marquardt.initial.step.bound.factor = 100.0
 
 # convergence is reached when max|p(k+1) - p(k)| < ε for each
 # normalized estimated parameters p and iterations k and k+1