Learn More
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(More)
An algorithm is developed for tracking multiple targets using distributed bearings-only sensors. It is assumed that the sensors report the measurements asynchronously and the processing is done centrally. The proposed algorithm first forms bearings-only (mono) tracks for each sensor and then combines them to form Cartesian position (stereo) tracks. The(More)
Data fusion has been applied to a large number of fields and the corresponding applications utilize numerous mathematical tools. This survey limits the scope to some aspects of estimation and decision fusion. In estimation fusion our main focus is on the cross-correlation between local estimates from different sources. On the other hand, the problem of(More)
We reexamine the problems of computer-aided classification and pairing of human chromosomes, and propose to jointly optimize the solutions of these two related problems. The combined problem is formulated into one of optimal three-dimensional assignment with an objective function of maximum likelihood. This formulation poses two technical challenges: 1)(More)
Network-centric multisensor-multitarget tracking has numerous advantages over single-sensor or single-platform tracking. In this paper, we present a solution to one of the main problems of network-centric tracking, namely, decentralized information sharing among the platforms participating in the distributed data fusion. This paper presents a decision(More)
For robust data association performance, tracking algorithms available in the literature utilize kinematic as well as non-kinematic information. These algorithms, however, do not provide a systematic way to utilize non-kinematic information to resolve severe and prolonged association ambiguities in the past. We propose a novel framework in which kinematic(More)