This example shows how to generate an air traffic control scenario, simulate radar detections from an airport surveillance radar (ASR), and configure a global nearest neighbor (GNN) tracker to track the simulated targets using the radar detections. This enables you to evaluate different target scenarios, radar requirements, and tracker configurations without needing access to costly aircraft or equipment. This example covers the entire synthetic data workflow.

This example shows how to fuse radar detections from a multiplatform radar network. The network includes two airborne and one ground-based long-range radar platforms. See the Multiplatform Radar Detection Generation example for details. A central tracker processes the detections from all platforms at a fixed update interval. This enables you to evaluate the network's performance against different target types and maneuvers as well as platform configurations and locations.

This example illustrates how to track targets using passive angle-only measurements from a single sensor. Passive angle-only measurements contain azimuth and elevation of a target with respect to the sensor. The absence of range measurements makes the problem challenging as the targets to be tracked are fully observable only under certain conditions.

This example illustrates tracking of objects using measurements from spatially distributed and synchronous passive sensors. In the Passive Ranging Using a Single Maneuvering Sensor, you learned that passive measurements provide incomplete observability of target's state and how a single sensor can be maneuvered to gain range information. Alternatively, multiple stationary sensors can also be used to gain observability. In this example, you will learn how to track multiple objects by fusing multiple detections from passive synchronous sensors.

This example simulates a multifunction phased array radar system. A multifunction radar can perform jobs that usually require multiple traditional radars. For example, scanning radars are responsible for searching targets while track radars are responsible for tracking targets. In this example, the multifunction phased array radar performs both scan (search) and track tasks. Based on the detections and tracks obtained from the current echo, the radar decides what to do next to ensure that targets of interest are tracked and the desired airspace is searched. The multifunction phased array radar works as a closed loop from task scheduling and waveform selection to detection generation and target tracking.

This example shows you how to track extended objects. Extended objects are objects whose dimensions span multiple sensor resolution cells. As a result, the sensors report multiple detections of the extended objects in a single scan. In this example, you compare the results of tracking extended objects with a point object tracker and an extended object tracker.

This example shows how to estimate the pose (position and orientation) of a ground vehicle using an inertial measurement unit (IMU) and a monocular camera. In this example, you:

This example shows how you might build an IMU + GPS fusion algorithm suitable for unmanned aerial vehicles (UAVs) or quadcopters.