Active–Passive Fusion Technology Based on Neural Network-Aided Extended Kalman Filter

The information fusion algorithm based on extended Kalman filter is widely used in the field of information fusion because of its relatively simple algorithm and solid theoretical foundation. This paper uses the advantages of neural networks and their advantages in solving nonlinear and time-varying systems to improve the traditional extended Kalman filtering method, improve the speed and accuracy of filtering, and improve the quality of active and passive data fusion.