MATLAB Implementation of Maneuvering Target Tracking

Maneuvering target tracking is a key research area in target tracking, primarily addressing situations where a target's motion state may abruptly change. The Interactive Multiple Model (IMM) algorithm is a classic method for maneuvering target tracking that operates multiple models in parallel and combines probability-weighted results to improve tracking accuracy.

In maneuvering target tracking, a target's motion patterns may include constant velocity, accelerated motion, or turning maneuvers. Traditional single-model filtering approaches (such as Kalman filters) struggle to adapt to changes in target motion states, whereas the IMM algorithm enhances tracking robustness by fusing predictions from multiple models.

The "Current" Statistical Model (CSM) is one of the commonly used motion models in the IMM algorithm. It assumes that the target's acceleration varies within certain statistical bounds and adapts to the target's maneuvering characteristics by dynamically adjusting the noise covariance matrix. This model is particularly suitable for scenarios with rapid changes in target motion states, such as tracking high-speed maneuvering targets like drones or missiles.

The implementation of the IMM algorithm generally involves the following steps: First, initialize filters for multiple distinct motion models. Second, compute the matching probabilities for each model based on the previous state estimate. Then, update the final state estimate through weighted fusion. Finally, update each model's probability based on observation data for the next computation cycle. This interactive model-switching mechanism enables the algorithm to adapt to the target's maneuvering behavior autonomously.

In practical applications, combining the IMM algorithm with the "Current" Statistical Model significantly improves the accuracy and stability of maneuvering target tracking, making it especially valuable for high-speed dynamic target tracking tasks in military, aerospace, and related fields.