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Probabilistic multi-hypothesis tracking (PMHT) is an algorithm for tracking multiple targets when measurement-to- target assignments are unknown and must be jointly estimated with the target tracks. Multi-frame assignment PMHT (MF- PMHT) is an algorithm designed to mitigate some performance problems associated with PMHT. In MF-PMHT, the PMHT algorithm is applied to multi-frame sequences in the last...
PMHT algorithm, as proposed, promises high performance multi target tracking in clutter with (relatively) modest computational resources. However, when applied to practical target tracking situations, a number of problems need to be overcome. PMHT assumes fixed number of tracks, and furthermore it assumes that all tracks are true tracks. No track quality measure is provided within PMHT to enable false...
Geolocation with three or more unmanned aerial vehicles (UAVs) based on time-difference-of-arrivals (TDOA) is possible but has implementation problems including UAV trajectory optimization, measurement association, and communication bandwidth limitations. The complexity of each of these problems is manageable with a simpler system of two netted UAVs that processes multiple TDOA measurements collected...
Tracking objects using multiple sensors is more efficient than those using one sensor. In this paper, we proposed a method to fuse data from multiple sensors in Gaussian mixture probability hypothesis density filter. This method can avoid the data association problem in multi-sensor multi-object tracking. Moreover, it is more reliable and less computational than particle probability hypothesis density...
Over-the-horizon (OTH) radar and automatic identification system (AIS) are commonly used in the surveillance of maritime areas. This paper presents a method, which includes tracking and association algorithms, for fusing the information from these two types of systems into an overall maritime picture. Data to be fused consists of asynchronous track estimates from the OTH system and measurements obtained...
In multi-sensor multi-target bearings-only tracking we often see false intersections of bearings known as ghosts. When the bearing measurements from each sensor have been associated to form sequences termed threads, the problem is to associate pairs of threads to identify the true target intersections. In this paper we present two algorithms: (i) classical bayesian thread association (CBTA) and (ii)...
Multi-sensor systems in automotive safety applications and sensor data fusion have become very popular in recent years. Sensors on board cars and active safety applications are increasing in number and the need to define a common method for object extraction and serving these applications has been recognized. Authors propose a high level fusion approach suitable for automotive sensor networks with...
Assume an ESA (electronically steered antenna) radar. In between the surveillance mode operations (where the radar completes one scan of the surveillance area), this radar has spare time for (at least one) additional mode which could be optimized for various special requirements. The optimization is often translated to the choice of the next track to update. In this paper we propose a resource allocation...
Smart Spaces are an emerging technology which is gathering interest in several domains of application since they allow to supply services and to interact with users in a pervasive way. One of their basic tasks regards the localization of the users in order to provide services in a personalized and location- based way. However since the guarded area is usually complex (e.g. with occlusions) and extent...
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