| 摘要 |
Embodiments of the present invention generally relate to systems and methods comprising First Order Multiple Hypothesis Testing for a Global Nearest Neighbor Data Correlation solution. Generating and storing multiple target hypotheses to allow immediate recovery in case of a false decision in uncertain association environment, improves the system's ability to handle multiple target tracking, in terms of tracker error, and creates a more accurate situational picture for a system's operator. Introducing the quality factor, and a configurable number of maximum hypotheses testing, assures the system is easily adjustable to different environments, to balance tradeoffs between its estimation accuracy and computational load.
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