IMM Interactive Multiple Model Tracking Algorithm Source Code

I have uploaded the source code implementation of the Interactive Multiple Model (IMM) tracking algorithm here and would like to engage in technical discussions with fellow researchers interested in target tracking. This advanced algorithm employs multiple motion models to track targets, utilizing interactive learning and dynamic weight allocation across models to achieve more accurate and stable tracking performance. The implementation typically involves key components such as model probability calculation, state mixing, Kalman filter bank execution, and probability update functions. I am particularly interested in both the practical implementation aspects and theoretical applications of this algorithm in target tracking domains, and hope to collaborate with peers to explore implementation details and identify potential innovations. If you have any technical insights, suggestions, or questions regarding this algorithm or target tracking methodologies, please feel free to share your thoughts in the comments section below.