Onboard information fusion for multisatellites, which is based on spatial computing mode,
can improve the satellites' capability, such as the spatial–temporal coverage, detection …

Most conventional target tracking algorithms assume that a target can generate at most one
measurement per scan. However, there are tracking problems where this assumption is not …

Traditional multiple target tracking (MTT) algorithms are model-based. Target and sensor
models are used to associate measurements, perform track filtering, score possible …

In the last five years, the state-of-the-art in computer vision has improved greatly thanks to an
increased use of deep convolutional neural networks (CNNs), advances in graphical …

Multiframe track-before-detect (MF-TBD) usually uses sliding-window-based batch
processing, where a number N of the latest data frames are jointly processed at each …

Multi-vehicle tracking is crucial in many applications, such as traffic surveillance, intelligent
transportation systems, and advanced driver assistance systems. Most conventional multi …

Nowadays, a variety of different sources can be combined together to measure and monitor
maritime human activities. Reliable data fusion techniques are essential to associate the …

In this article, we propose a novel approach to distributed joint detection, tracking, and
classification (D-JDTC) of multiple targets by means of a multisensor network. The proposed …

For an airborne sensor, there is a pressing need to be able to detect/track submerged
submarines, shipwrecks, sea mines, unexploded explosive ordnance, and buried drums …

Autonomous vehicle technology is rapidly becoming the driving force in the automobile
industry. As such, the interest in high-resolution radio detection and ranging (radar) for …