- MathWorks announces the Sensor Fusion and Tracking Toolbox available for version 2018b of its Matlab development and calculation software.
- This toolbox provides algorithms and functions dedicated to program development that allow autonomous systems to determine their position and orientation, and to perceive their environment.
To perceive their environment and geolocate autonomous systems must fuse data from various sensors. This Matlab toolkit provides tracking and location algorithms, as well as reference examples to facilitate the implementation of on-board surveillance and navigation systems to autonomous airborne, land and underwater systems.
This toolbox provides a reusable environment that can be shared between developers. It offers simulation functions for sensor detection, geo-localization, and testing of sensor data fusion architectures as well as tracking evaluation.
According to Paul Barnard, Marketing Director of Design Automation at MathWork, “Algorithm designers working on tracking and navigation systems often use their own tools that can be difficult to maintain and reuse. With Sensor Fusion and Tracking Toolbox, it is possible to explore multiple designs and perform simulation analyses without having to create custom libraries.”
# Other specifications of ‘’Sensor Fusion and Tracking Toolbox”:
- Multi-object trackers, sensor fusion filters, motion and sensor models, and data association algorithms can be used to evaluate fusion architectures using real and synthetic data.
- Scenario and trajectory generation tools.
- Synthetic data generation for active and passive sensors, including RF, acoustic, EO/IR, and GPS/IMU sensors.
- System accuracy and performance – benchmarks, metrics and standardized animated diagrams.
- Deployment options to accelerate simulation or prototyping using C code generation.