meaning of nonholonomic filter parameters

hello everyone.

I am working with a nonholonomic filter to reconstruct a path using imu data (accelerometer and gyroscope).

I start from a path obtained via the gps sensor and need to reconstruct the same path with imu data.

As I am new to matlab and the use of the kalman filter, I wanted to know if anyone could explain to me the meaning of the various parameters of the nonholonomic filter (such as DecimationFactor, AccelerometerBiasDecayFactor, GyroscopeBiasDecayFactor).

What changes on a practical level if you change these values?

How do they affect the final result?

Many thanks in advance to everyone.

Answer 1

[Maneet Kaur Bagga]

Hi,

As per my understanding you want to know about the tuning of nonholonomic filter parameters in the context of IMU data and path reconstruction.

Please refer to the following tutorial from MathWorks which provides an overview of how to design and simulate the "Inertial Navigation Systems" (INS) in MATLAB, including the role of filters in integrating the sensor data.

https://in.mathworks.com/videos/design-and-simulate-inertial-navigation-systems-1625235854630.html

The following documentation is an example that walks through the process of determining an object's "position" and "orientation" using a combination of inertial sensors and GPS.

https://in.mathworks.com/help/fusion/gs/determine-pose-using-inertial-sensors-and-gps.html

The following documentation provides an overview of multi-sensor positioning techniques in MATLAB, offering insights into how different sensors, including IMUs and GPS, can be combined to achieve accurate positioning.

https://in.mathworks.com/help/nav/multisensor-positioning.html

Please refer to the following MATLAB functions for further understanding:

"insfilter": https://in.mathworks.com/help/nav/ref/insfilter.html

"insfilterNonholonomic": https://in.mathworks.com/help/nav/ref/insfilternonholonomic.html

Hope this helps!