At the end of last week Udit suggested another paper for us to use as reference for our multilateration software.\u00a0 So I started working on understanding the paper, but while going through the math I noticed that the hardware set up was different than what we have.\u00a0 Instead of having a transmitting tag, and multiple receiving beacons, it had multiple transmitting beacons and receiving tag which does all the math.\u00a0 We decided that moving forward with this paper would not be productive, but it helped us decide to use a Kalman filter.\u00a0 \u00a0We then took a look at a different paper which had a similar hardware set up to our system and used a Kalman filter.<\/p>\n
After looking at the other paper we decided that our approach should be to use Gauss-Newton to estimate the position and then use a Kalman filter to improve the accuracy.\u00a0 So I then did research on Kalman filters, to understand generally how it works, and how we might apply it to our system.<\/p>\n
Next week I will work on implementing the Kalman filter to improve accuracy of the location we predict.<\/p>\n","protected":false},"excerpt":{"rendered":"
At the end of last week Udit suggested another paper for us to use as reference for our multilateration software.\u00a0 So I started working on understanding the paper, but while going through the math I noticed that the hardware set up was different than what we have.\u00a0 Instead of having a transmitting tag, and multiple … <\/p>\n