Inertial Navigation System


Inertial Navigation System (INS) is the most important component of an Unmanned Aerial Vehicle (UAV).

The UAV must be able to flight with or without support from the base station. In order to do that, the UAV, must have an intelligent system in order to find the position and the traveled route of the vehicle, also doing the necessary calculation using the desired trace they will control the actuators of the vehicle in order to have the right direction and speed. The navigation system will have 7 degrees of freedom.

UAVs are used in many fields such as traffic control, military applications, surveillance missions and many others. The main advantages of using a UAV are the following:

  • No human risk, we can send a UAV in high risk mission (such as surveillance missions with bad weather conditions).
  • Reduced equipment needed, since the vehicle is unmanned we can discard all the safety equipment of the vehicle and also many safety tests that cost too much.
  • Low cost, we have the ability to use equipments with decreased performance.
  • Easy to use, there is no need for highly skilled staff.
  • Easy to build, it is much easier to build a UAV than a real aircraft.

The UAV will have an embedded digital camera that will send video to the ground station real time through the embedded RF transmitter. There are many applications in real life such as surveillance detection projects, traffic control system, air photography and more.


Basic System Diagram

In order to create an autonomous vehicle we will use a combination of Global Position Satellite (GPS) and Inertial Navigation System (INS) approach. The advantages of the INS are the following:

  • It is autonomous, no external source needed
  • It is well suited for navigation. It measures the variables to be controlled
  • It has good immunity to jamming
  • It is stealth

On the other hand, sensor errors increase with time.

By using INS/GPS approach we are able to have better performance, unacceptable (for INS only mode) sensors errors now can be handled easily (using Kalman filters), navigation performance is not affected by GPS signal losses and more.


Next: Hardware

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