A global modeling approach for multi-target tracking and multi-sensor fusion
Yi‐Nung Chung · ThinkTech (Texas Tech University) · 1990
II. DATA ASSOCIATION APPROACHES FOR MULTI-TARGET TRACKING PROBLEMS 8 2.1 Problem Definitions 9 2.2 Basic Concept of the Extended Kalman Filter 14 2.3 1-Step Conditional Maximum Likelihood .16 2.4 1-Step Maximum A Posteriori Estimate .. 18 2.5 Adaptive Procedure 2 0 2.6 False Returns and Missed Detections ... 2 3 2.7 Validation Matrix 26 2.8 Summary 28 IV.SIMULATIONS 45 4.1 simulation of Data Association for Multi-Target Tracking 45 4.1.1Constant Velocity Target Tracking 47 4.1.2Maneuvering Target Tracking .... 52 4.1.3Tracking Accuracy Corresponding to Measurement Covariances 54 4.1.4Tracking Situations with Asynchronous Update Rate 62 4.1.5Maneuvering Targets with Circular Trajectories 64 4.2 simulation of Multi-Target Tracking Via Multi-Sensor Fusion Algorithm 68 4.2.1 Numerical Results 76 4.3 Summary 77 V. CONCLUSIONS 79