Abstract
Multi-sensing system for target tracking has been addressed by many researchers from different fields. In this work, a multi-sensing system within the time, space, and frequency domains is first described. The system development is based on sensor spatial and temporal characteristics, and therefore is reliable and stable. The frequency outcome of sensors is employed to segment the detection scope into different domains, and is simple to implement. For resolving the challenge of decision-making strategy, this work combines the spatial and temporal properties with the determination mechanism as well as optimizes the system devising—making it a very promising basis for the realization of tracking accuracy improvement. With this strategy, target detection results are obtained and evaluated by probability-based parameters. The proposed decision-making scheme receives a high detection accuracy as well as a good working performance according to statistical analysis, allowing a straightforward methodology for the configuration of multi-sensing system.
Highlights
The significance of sensors for target tracking as well as its application has attracted a great deal of interest over last decades
2 Basic concepts on spatial and temporal characteristics We describe the theory of spatial and temporal features of moving objects, which influences the accuracy demanded of tracking [21]
Results indicate that the detection accuracy of the sensing system can be estimated via probability-based functions by segmenting the working region into three-dimensional domain
Summary
The significance of sensors for target tracking as well as its application has attracted a great deal of interest over last decades. On the basic of previous researches, multi-sensors have already been employed for traffic speed and travel time detecting [4,5,6]. Indoor positioning is another such field, with recent publications revealing the capability in. The multiple sensors detect the designated target in continuous time series and the sensing frequencies are updated and transformed in a timely manner. The multi-domain figure based on classical sensing signal of different orders is discrete in its dimension parameter Rn. Suppose that there are two independent ST s, i.e., the variability of the object trajectories is calculated by the measuring of the two regions. As long as the angle of the angle δ is fixed, it is possible to use the above exhibited formula to determine the domain representation in an effective way
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