Understanding Limitations & Their Solutions in GPS Inertial Simulation

Even without first factoring in the integration of any global positioning system, you will notice that testing inertial navigation sensors presents significant challenges in unique capacities. These problems arise from the design of sensors, both angular and linear. Angular sensors run on angular rate tables, whereas linear sensors use centrifuges.

It is important you understand that first

Here is where most of the critical problems with inertial simulation arise. Characterizing these sensors separately only allows you limited navigation testing. And, having that you have to use the high-rate tables with lever arms makes this testing process even more challenging.

You, however, can establish full operational navigation performance by doing your field tests on appropriate select moving vehicle platforms. You will say that will cost you more time and money, but it is the best option here. But, you can save on that by:

Using a GPS Constellation Simulator

Using GPS constellation simulators can help you reduce the number of field trials you need to derive a comprehensive analysis of your inertial system’s operational performance. Also, you can use these simulators in a lab to match, accurately and in real-time, the trajectory of your GPS vehicle from the sensor outputs of the simulated inertial system.

The Place of Traditional Techniques

You can also use traditional techniques to establish the sensor performance of your inertial system, and represent the bias or drift as sensor error models using appropriate coefficients of the simulated sensor motion. However, it will be necessary here that you provide altitude references for the inertial navigation.

The key advantage of using this simulated approach in optimizing inertial simulation is that every stimulus to your navigation algorithms is under your control, and is extremely repeatable. That saves you the cost of carrying out field tests exclusively. You also have the benefit of choice in debugging and fine-tuning the simulated navigation algorithms depending on the scenario on which you are running the operational tests.

 

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