Sensor Fusion and Tracking Toolbox™ includes algorithms and tools for the design, simulation, and analysis of systems that fuse data from multiple sensors to maintain position, orientation, and situational awareness. Reference examples provide a starting point for implementing components of airborne, ground-based, shipborne, and underwater surveillance, navigation, and autonomous systems.
The toolbox includes multi-object trackers, sensor fusion filters, motion and sensor models, and data association algorithms that let you evaluate fusion architectures using real and synthetic data. With Sensor Fusion and Tracking Toolbox you can import and define scenarios and trajectories, stream signals, and generate synthetic data for active and passive sensors, including RF, acoustic, EO/IR, and GPS/IMU sensors. You can also evaluate system accuracy and performance with standard benchmarks, metrics, and animated plots.
For simulation acceleration or desktop prototyping, the toolbox supports C code generation.
Learn the basics of Sensor Fusion and Tracking Toolbox
Examples for autonomous system tracking, surveillance system tracking, localization, and hardware connectivity
Quaternions, Euler angles, rotation matrices, and conversions
Ground-truth waypoint- and rate-based trajectories and scenarios
IMU, GPS, RADAR, ESM, and EO/IR
IMU and GPS sensor fusion to determine orientation and position
Kalman and particle filters, linearization functions, and motion models
Multi-sensor multi-object trackers, data association, and track fusion
Multi-object theater plots, detection and object tracks, and track metrics