Multi sensor tracking is a process used in systems like the MultiSensorTracker (MST) to combine and analyze data received from various types of sensors.
Understanding Multi Sensor Tracking
At its core, multi sensor tracking involves taking input from different data sources, such as Radar and AIS (Automatic Identification System), and using this information to build a unified picture. The goal is to create system tracks.
How it Works
According to the reference, a MultiSensorTracker:
- Processes and Correlates Data: It receives data streams from multiple sensor types. This data is then processed and correlated, meaning the system looks for relationships and commonalities between the measurements from different sensors about the same object or target.
- Produces System Tracks: Based on the correlated data, the system generates 'system tracks'. A system track represents a single, coherent estimate of a target's position, identity, and movement, synthesized from all available sensor inputs.
- Updates Tracks: These system tracks are dynamic. They are continuously updated as new data arrives from one or more of the connected sensors. This ongoing update process helps maintain an accurate and current representation of the target's status.
Key Features and Benefits
The reference highlights specific features that contribute to the effectiveness of multi sensor tracking:
- Combining Different Sensor Types: The ability to integrate data from fundamentally different sensor technologies (like Radar, which detects physical objects, and AIS, which receives identification broadcast messages) provides a more comprehensive understanding than using a single sensor type alone.
- Flexible Input Filtering: Before the data is processed and correlated, flexible filtering can be applied. This assures sensor specific data preprocessing. This means that data from each sensor type can be cleaned or adjusted according to its specific characteristics and limitations.
- Preventing Undesired Target Merging: A critical function of the filtering and correlation process is to prevent undesired target merging. This ensures that distinct targets are not mistakenly combined into a single track, which is crucial for maintaining situational awareness.
By combining data from multiple sources and intelligently processing it, multi sensor tracking creates robust and reliable system tracks, offering a clearer and more accurate picture of the operational environment.
