Why isn't there any integration drift in simulation of Inertial Navigation System(INS)?
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In INS, we obtain measurements from accelerometer and gyroscope; by integrating these the position and orientation of an UAV can be determined. I have simulated the dynamical equations for a point mass model of UAV. To simulate the noise, I added noise to the dynamical equations of velocity and angle rates. Since I want the UAV to track a particular trajectory, there are control laws in loop. When I integrate these equations, I only see noise on top of all the states, but not divergence in any of them. Why isnt the integrated error diverging?
I tried to add Kalman filter to this implementation, by assuming we can measure velocity, heading angle and the altitude of the UAV. Even this formulation is giving similar results with only extra noise in the integrated states.
My doubt is, since there are controllers in loop, at every time step, they are trying to ensure that the desired path is tracked and hence they are ensuring the UAV does not drift from the original path. This argument supports my simulation results. However, I am not sure about this logic. Can someone please explain?