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2016
Book Article
Titel
Tracking and Data Fusion for Ground Surveillance
Abstract
Ground surveillance comprises track extraction and maintenance of single ground moving vehicles and convoys, as well as low-flying objects such as helicopters or unmanned aerial vehicles (UAVs). By using airborne sensor platforms in stand-off ground surveillance applications, the effect of topographical screening is alleviated, thus extending the sensors' field of view. Characteristic problems of signal processing related to ground moving target indication (GMTI) tracking with space-time adaptive processing (STAP) radar are discussed. This chapter shows how the knowledge on the clutter notch of the sensor can be incorporated into a Bayesian tracking scheme. In many ground surveillance applications, vehicles on roads are the most important objects. Digital road maps are available for many areas in a good quality, and can be exploited to enhance the tracking performance in terms of track precision and track continuity. The chapter talks about convoy tracking with the cardinalized probability hypothesis density filter.