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while designing a multi-object tracking system, it is essential to devise a method to evaluate its performance against the available ground truth. this ground truth is typically available from a simulation environment or by using techniques like ground-truth extraction using manual or automated labeling on recorded data. though it is possible to qualitatively evaluate a tracking algorithm using visualization tools, the approach is usually not scalable. this example introduces different quantitative analysis tools in sensor fusion and tracking toolbox™ for assessing a tracker's performance. you will also use some common events like false tracks, track swaps etc. encountered while tracking multiple objects to understand the strengths and limitations of these tools.

use the allan variance to determine noise parameters of a mems gyroscope. these parameters can be used to model the gyroscope in simulation. the gyroscope measurement is modeled as:

magnetometers detect magnetic field strength along a sensor's x,y and z axes. accurate magnetic field measurements are essential for sensor fusion and the determination of heading and orientation.