Practical Implementation of Air Target Tracking Combined with Radar Systems

In our research on air target tracking, we integrated radar systems to address practical operational scenarios. To handle both linear and nonlinear motions in target movement models, we developed two specialized approaches. One model implements the Interacting Multiple Model (IMM) algorithm using Markov state transition matrices, while the alternative model employs a different methodology. Our MATLAB simulation involved implementing kinematic models with state transition functions and measurement equations, where the IMM algorithm manages model switching through probability calculations. The performance analysis demonstrated that the Interacting Multiple Model Kalman Filter achieves superior trajectory prediction accuracy through optimal data fusion from multiple models. This research contributes significantly to air target tracking technology and provides valuable insights for related fields, particularly in optimizing model transition probabilities and covariance management in practical implementations.