Developing a First-Order Model for Simplified Higher Level Sensor Fusion Open Access
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Mulitsensor data fusion is a process used to combine the outputs of several sensors in a way that provides more information than the data going into it. This sensor fusion has been researched for decades yet programs relying on it to provide a situational assessment continue to be less than successful. To alleviate the too-much-information too-few-analysts issue, a better approach must be determined. A survey of recent and current data fusions programs was conducted along with a literature review on how different organizations handle a fusion-based assessment. Key points found in this study were used to develop an adaptation of existing data fusion models. The newly adapted model was utilized in a technology demonstration to show that simplified processes could be used to provide an assessment just as effective as what is intended by many much more complicated programs.