Multi-Sensor Data Fusion Across Multiple Time Cycles
Integrating data from multiple sensors over several time cycles to enable comprehensive decision-making through advanced algorithmic processing
Multi-Sensor Data Fusion Based on Extended Kalman Filter (EKF)
Multi-Sensor Data Fusion in Clutter Environments Using Extended Kalman Filter
Multi-Sensor Target Localization Algorithm
This algorithm implements multi-sensor target localization using cross positioning with the common perpendicular line method, suitable for real-time target tracking applications.
IMM_MSPDA Association for Multi-Sensor Multi-Target Data Fusion
The IMM_MSPDA algorithm for multi-sensor multi-target data fusion demonstrates excellent performance in tracking maneuvering targets using multiple model approaches, with implementation involving model probability updates and Markov switching mechanisms.
Asynchronous Fusion Algorithm under Correlated Noise Conditions
Asynchronous fusion algorithm addressing correlated noise in multi-sensor systems with implementation insights