Hi, I have implemented a simple Kalman filter (using standard Kalman filter equations) to integrate INS and wheel encoder. My state vector includes ‘displacement’ and ‘velocity’. (acceleration is the known input) x=[disp; vel] My model is: d(disp)/dt=vel d(vel)/dt=acceleration(in navigation frame) I also have external measurements of velocity from wheel encoder. Kalman gain therefore is a 2x1 vector: K=[K1; K2]. My problem is about the values of Kalman gain. In state estimate update equation (xhat=xhat+K(z-Hx)), since my innovation is the difference of velocity measurement and Hx, (i.e. it only contains velocity information), it seems like K1 should be zero. However, in my program K1 equals 0.5. The plots of estimation results look OK though. Should K1 be zero? If not, where does it get new information about displacement weight while we have only new velocity measurements? Any help will be appreciated.

# Kalman gain for weighting a state which is not directly measured

On Thu, 14 Jun 2012 20:02:53 -0500, adelaide wrote:> Hi, > I have implemented a simple Kalman filter (using standard Kalman filter > equations) to integrate INS and wheel encoder. My state vector includes > ‘displacement’ and ‘velocity’. (acceleration is the knowninput)> x=[disp; vel] > My model is: > d(disp)/dt=vel d(vel)/dt=acceleration(in navigation frame) > I also have external measurements of velocity from wheel encoder. > Kalman gain therefore is a 2x1 vector: K=[K1; K2]. My problem is about > the values of Kalman gain. > In state estimate update equation (xhat=xhat+K(z-Hx)), since my > innovation is the difference of velocity measurement and Hx, (i.e. it > only contains velocity information), it seems like K1 should be zero. > However, in my program K1 equals 0.5. The plots of estimation results > look OK though. Should K1 be zero? > If not, where does it get new information about displacement weight > while we have only new velocity measurements? > Any help will be appreciated.If the velocity is wrong, then the position is wrong and should be adjusted. Therefore, K1 should be nonzero. Does that help?

>On Thu, 14 Jun 2012 20:02:53 -0500, adelaide wrote: > >> Hi, >> I have implemented a simple Kalman filter (using standard Kalman filter >> equations) to integrate INS and wheel encoder. My state vector includes >> ‘displacement’ and ‘velocity’. (acceleration is the knowninput)>> x=[disp; vel] >> My model is: >> d(disp)/dt=vel d(vel)/dt=acceleration(in navigation frame) >> I also have external measurements of velocity from wheel encoder. >> Kalman gain therefore is a 2x1 vector: K=[K1; K2]. My problem is about >> the values of Kalman gain. >> In state estimate update equation (xhat=xhat+K(z-Hx)), since my >> innovation is the difference of velocity measurement and Hx, (i.e. it >> only contains velocity information), it seems like K1 should be zero. >> However, in my program K1 equals 0.5. The plots of estimation results >> look OK though. Should K1 be zero? >> If not, where does it get new information about displacement weight >> while we have only new velocity measurements? >> Any help will be appreciated. > >If the velocity is wrong, then the position is wrong and should be >adjusted. Therefore, K1 should be nonzero. > >Does that help? >

>On Thu, 14 Jun 2012 20:02:53 -0500, adelaide wrote: > >> Hi, >> I have implemented a simple Kalman filter (using standard Kalman filter >> equations) to integrate INS and wheel encoder. My state vector includes >> ‘displacement’ and ‘velocity’. (acceleration is the knowninput)>> x=[disp; vel] >> My model is: >> d(disp)/dt=vel d(vel)/dt=acceleration(in navigation frame) >> I also have external measurements of velocity from wheel encoder. >> Kalman gain therefore is a 2x1 vector: K=[K1; K2]. My problem is about >> the values of Kalman gain. >> In state estimate update equation (xhat=xhat+K(z-Hx)), since my >> innovation is the difference of velocity measurement and Hx, (i.e. it >> only contains velocity information), it seems like K1 should be zero. >> However, in my program K1 equals 0.5. The plots of estimation results >> look OK though. Should K1 be zero? >> If not, where does it get new information about displacement weight >> while we have only new velocity measurements? >> Any help will be appreciated. > >If the velocity is wrong, then the position is wrong and should be >adjusted. Therefore, K1 should be nonzero. > >Does that help?Thanks Tim. So far, I realise it's OK that K1 is nonzero, right? Where does it get the new information though? Because we don't have any new position information in Innovation. Also, I thought position state get correction only from the model through corrected velocity. Isn't that correct? Thanks for your help