INS + GPS Integration using Kalman Filter

Hello World,

I want to implement an outdoor localisation to get the accurate measurement of a drone using GPS INS localisation.

I have acquired MKR IMU Sheild, MKR GPS and Arduino.

I am confused on how to proceed with implementing this solution. I have not done such implementation before.

I am looking for any guide to help me get started or similar tutorial I can model after.

Thanks

Consumer grade IMUs are of no use for inertial navigation, so the best a hobbyist can do is use the GPS measurements. For accurate localization, RTK-GPS units are available, but you will need either a GPS-RTK base station or access to a commericial source of correction information, valid for your locality.

The Ublox C94-M8P works well for me.

I don't want to implement a consumer grade solution. I just just realise GPS INS and I have already acquired the needed hardwares for that.

I am just looking for a similar implementation or better still how I can implement Kalman Filter or extended Kalman Filter on the IMU and GPS data.

What hardware? Post links.

The hardware, excluding Arduino

IMU: Arduino MKR IMU Shield — Arduino Official Store

GPS: Arduino MKR GPS Shield — Arduino Official Store

That is a consumer grade IMU. It is fine for orientation, but will not work for inertial navigation. In fact, the BNO055 works much more poorly than more modern sensors, even for orientation.

Why is this the case?

I thought I could be able to get the data for gyro, accelero and magneto from it and then fuse it with the GPS using a filter.

So this is not possible?

It is possible, but the IMU data are so inaccurate that they won't do any good at all. Here is a simple summary of just ONE of the major problems. Using Accelerometers to Estimate Position and Velocity | CH Robotics

Commercial grade IMUs used for navigation cost in the range of $10K to $50K.

It would be a great learning experience to write the Kalman filter, so don't let the poor quality IMU stop you! Let us know how it goes.

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