多目标跟踪和传感器融合位于感知系统的核心，是自主系统和监视系统的关键组成部分。传感器，如摄像机，闪光灯，雷达和声纳产生用作跟踪器的输入的检测。多目标跟踪算法用于估计对象的数量，以及它们的状态，包括位置，速度，以及某些情况下的大小和方向。该信息使自主系统和监控系统能够维持态势意识。
Multi-object tracking performance is driven by factors such as:
- Sensor parameters including probability of detection (Pd), resolution, and accuracy
- The number of targets and detections present
- The presence of false measurements for objects not in the environment
- Ambiguity in measurements of objects being tracked
Tracking objects in a large flock moving in complex trajectories using MATLAB and Simulink
With MATLAB®和传感器融合和跟踪工具箱™, you can track objects with data from real-world sensors, including active and passive radar, sonar, lidar, EO/IR, IMU, and GPS. You can also generate synthetic data from virtual sensors to test your algorithms under different scenarios. The toolbox includes a library of multi-object trackers and estimation filters that you can further customize for your application. You can also generate C code withMATLAB Coder™ to accelerate simulation performance or to get a head start on your prototype system.
To learn more about multi-object tracking, see传感器融合和跟踪工具箱与matlab一起使用。
