Predicate model of process knowledge about observed objects in multichannel intelligent monitoring systems
DOI:
https://doi.org/10.30837/rt.2019.4.199.08Keywords:
model of process knowledge, decision making, moving object, detection, recognition, intelligent system.Abstract
A model of process knowledge about observed objects in multichannel intelligent monitoring systems, a method of intellectual analysis of processes and a decision-making method based on precedents are proposed. The main features and structural elements of the model of process knowledge are given. It is shown that advantage of this model is related to the configuration and hierarchical representation of the process for detecting and recognizing moving objects based on the intelligent analysis of signals and algebra of finite predicates. It is shown how this approach can be used to automate the process of detecting and recognizing objects that can be both in motion mode and in rest mode. As a result of the experiments, real radar signals are converted into symbolic images based on the algebra of finite predicates, and process knowledge about moving, stationary and inactive objects in monitoring systems of air and ground transport is formalized. It is also proposed to use this approach as a tool for building a model of process knowledge of multi-frame signal processing in intelligent monitoring systems for stealth and inactive objects. From the received signals about air and ground objects, a map or data matrix is formed. Then, as a result of accumulation, a new spatial signal image or virtual image is formed, that is, a new symbolic model of signal marks for moving and stationary objects is formed. Thus, the database turns into a process knowledge base, as a result of analysis of which the required solution is obtained.References
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