The goal of using data fusion in multisensor environments is to obtain a lower detection error probability and a higher reliability by using data from multiple ...
As stopping targets are indistinguishable from ground clutter, the early detection of a stopping event itself as well as tracking of 'stop & go' targets can be ...
In this paper, we propose a new fusion method that maps the confidence outputs from different detectors to a shared range where they compare meaningfully, and ...
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Data Fusion: Cumulative Effects of Discrete Fusion on Target Detection Probability. ... Data fusion: remote sensing for target detection and tracking. IGARSS ...
Level one data fusion is the process of combining data in order to track and classify individual entities. This document introduces the basic concepts and ...
This enables estimates of the residual combat strength of the object, which has direct implications on countermeasures, e.g. Target Tracking and Data Fusion ...
Data fusion techniques combine information collected from different sources to extract useful information. They also facilitate more accurate and robust ...
The integration of data and knowledge from several sources is known as data fusion. This paper summarizes the state of the data fusion field and describes ...
Compared with the independent processing of a single source, the advantages of data fusion include improving detectability and reliability, expanding the range ...
In this paper, we present fast sensor placement algorithms based on a probabilistic data fusion ... sion is employed, the probability of detecting a target is.
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