targettracking
Target tracking is the process of estimating the evolving state of a moving target over time using observations from one or more sensors. The state typically includes position, velocity, and sometimes acceleration or other attributes, while the measurements may be noisy and incomplete due to clutter or missed detections. Tracking aims to produce a consistent sequence of state estimates that explain the observed data and support tasks such as prediction, control, or alerting. Applications span radar, sonar, lidar, video surveillance, autonomous vehicles, and robotics.
Core elements of target tracking include a state-space model, a measurement model, and an inference algorithm.
Track management involves initializing, maintaining, updating, and deleting tracks, as well as handling occlusions and clutter.
Challenges in target tracking include clutter, false alarms, occlusions, measurement dropouts, and the need for real-time