Sensor Fusion and Tracking Toolbox
Design, simulate, and test multisensor tracking and positioning systems
Have questions? Contact Sales.
Have questions? Contact Sales.
Sensor Fusion and Tracking Toolbox includes tools for designing, simulating, validating, and deploying systems that fuse data from multiple sensors to maintain situational awareness and localization. Reference examples provide a starting point for multi-object tracking and sensor fusion development for surveillance and autonomous systems, including airborne, spaceborne, ground-based, shipborne, and underwater systems.
You can fuse data from real-world sensors such as active and passive radar, sonar, lidar, EO/IR, IMU, and GPS. To further test your tracking algorithms, you can use the simulation environment and sensor models. The toolbox also includes multi-object trackers and estimation filters for evaluating and validating various fusion architectures using track performance metrics such as OSPA and GOSPA.
For simulation acceleration, rapid prototyping, or deployment the toolbox supports C/C++ code generation.
Simulate and track surveillance, autonomous, and inertial navigation systems.
Define multiplatform scenarios, then assign motion profiles and attach sensor models to each platform. Simulate these scenarios and dynamically visualize platform trajectories, sensor coverages, and object detections.
Use a library of domain-specific target and sensor specification to build a multi-object multisensor tracker. Alternatively, use trackers that integrate filters, data association, and track management and choose from a variety of well-known multi-target algorithms, for example multi-hypothesis and joint probabilistic data association.
Explore centralized or decentralized multi-object tracking architectures and evaluate design tradeoffs between track-to-track fusion, central-level tracking, or hybrid tracking architectures for tracking applications.
Use the Tracking Data Importer app to interactively import and convert real-world or simulated tracking truth data for visualization and analysis.
Analyze and evaluate the performance of tracking systems against ground truth using a variety of tracking metrics. Visualize ground truth, sensor coverages, detections, and tracks on a map or in a MATLAB figure.
Deploy algorithms to hardware targets by automatically generating C/C++ code from fusion and tracking algorithms. Deploy generated code to low-cost, single-precision processors with limited memory.
30 days of exploration at your fingertips.
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Contact the Sensor Fusion and Tracking Toolbox technical team.