Radar and Camera Tracking

Track extended objects using radar and camera

These examples track extended objects using radar and camera detections.

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Highway Vehicle Tracking Using Multi-Sensor Data Fusion

Track vehicles on a highway with commonly used sensors such as radar, camera, and lidar. In this example, you configure and run a Joint Integrated Probabilistic Data Association (JIPDA) tracker to track vehicles using recorded data from a suburban highway driving scenario.

Since R2024b
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Extended Object Tracking of Highway Vehicles with Radar and Camera

Track highway vehicles around an ego vehicle as extended objects that span multiple sensor resolution cells.

Open Script

Asynchronous Sensor Fusion and Tracking with Retrodiction

Construct an asynchronous sensor fusion and tracking model in Simulink®.

Since R2021b
Open Model

Processor-in-the-Loop Verification of JPDA Tracker for Automotive Applications

Generate embedded code for a JPDA tracker and verify it using processor-in-the-loop (PIL) simulations.

Since R2022a
Open Live Script

Highway Vehicle Tracking with Multipath Radar Reflections

The challenges associated with tracking vehicles on a highway in the presence of multipath radar reflections. It also shows a ghost filtering approach used with an extended object tracker to simultaneously filter ghost detections and track objects.

Since R2021a
Open Live Script

Extended Object Tracking of Highway Vehicles with Radar and Camera in Simulink

Track highway vehicles around an ego vehicle in Simulink. In this example, you use multiple extended object tracking techniques to track highway vehicles and evaluate their tracking performance. This example closely follows the Extended Object Tracking of Highway Vehicles with Radar and Camera MATLAB® example.

Since R2021b
Open Model

Extended Target Tracking with Multipath Radar Reflections in Simulink

Model and mitigate multipath radar reflections in a highway driving scenario in Simulink®. It closely follows the Highway Vehicle Tracking with Multipath Radar Reflections MATLAB® example.

Since R2021b
Open Live Script

Grid-Based Tracking in Urban Environments Using Multiple Radars

Track moving objects with multiple high-resolution radars using a grid-based tracker. A grid-based tracker enables early fusion of data from high-resolution sensors such as radars and lidars to estimate a dynamic occupancy grid map and a global object list. For grid-based tracking with lidar sensors refer to the Grid-Based Tracking in Urban Environments Using Multiple Lidars

Since R2024a
Open Live Script