Tracking and Resolution in Radar
The module addresses the essential elements of target tracking in radar systems, including tracking principles, methods, angular resolution, and advanced algorithms. It explains the importance of estimating a target's trajectory and the algorithms used for accurate tracking, especially in multi-target scenarios. The Monopulse technique and Kalman Filters are highlighted as key advancements in providing precise angular measurements and handling measurement noise.
Sections
Navigate through the learning materials and practice exercises.
What we have learnt
- Accurate target tracking is crucial for applications such as air traffic control and missile guidance.
- Angular resolution is determined primarily by antenna beamwidth and is critical for distinguishing closely spaced targets.
- Advanced tracking algorithms, including Kalman Filters and Monopulse techniques, enhance the radar's ability to accurately estimate target states.
Key Concepts
- -- State Vector
- Representation of the kinematic state (position, velocity, acceleration) of a target at a specific time.
- -- Kalman Filter
- An optimal recursive data processing algorithm used for state estimation in dynamic systems, particularly in radar tracking.
- -- Angular Resolution
- The minimum angular separation between two targets that a radar can distinguish as separate entities.
- -- Monopulse Technique
- A radar method that allows for highly accurate angular measurements of a target within a single radar pulse.
- -- TrackWhileScan (TWS)
- A radar method that enables simultaneous tracking of multiple targets while continuously scanning for new ones.
Additional Learning Materials
Supplementary resources to enhance your learning experience.