An Automatic Recognition Method of Unknown Radiation Source System Based on Similarity Expert Knowledge

Abstract

The invention discloses an automatic identification method of an unknown radiation source system based on similarity expert knowledge. The unknown radiation source is classified twice based on the two elements of attribute coincidence and parameter similarity, and then the two classification results are fused. Obtain the system fusion judgment result: the fusion system judgment improvement process based on specific expert knowledge, such as the pulse pressure or spread spectrum system fusion judgment process for the expert knowledge of the radiation source's large time-width bandwidth product characteristics, etc.; the unknown radiation source is improved Regime identification capability, and system identification efficiency for bulk unknown radiation sources.

Description

technical field [0001] The invention belongs to the technical field of radiation source identification, and relates to an automatic identification method for an unknown radiation source system based on similarity expert knowledge. Background technique [0002] With the development of electronic technology, especially the wide application of radar, communication and other technologies, the working system of radiation sources has become complex and diverse, and the electromagnetic environment has become increasingly complex. The radiation source parameters detected by the electronic reconnaissance system are also becoming more and more diverse. Only relying on manual interpretation or simple comparison and query to identify the type or model of the radiation source is time-consuming, labor-intensive, slow in recognition speed, low in recognition accuracy, and unknown radiation source. The system is difficult to identify and other deficiencies, so higher and higher requirements...

AI Technical Summary

Problems solved by technology

The radiation source parameters detected by the electronic reconnaissance system are also becoming more and more diverse. Only relying on manual interpretation or simple comparison and query to identify the type or model of the radiation source is time-consuming, labor-intensive, slow in recognition speed, low in recognition accuracy, and unknown radiation source. The system is difficult to identify and other deficiencies, so higher and higher requirements are put forward for the automatic identification of radiation sources. On the one hand, it is required to gradually strengthen the automatic classification and identification capabilities for known or unknown radiation sources; The demand for systematic identification of unknown radiation sources is increasingly urgent, and the automatic identification of unknown radiation sources is an important way to further understand and master unknown radiation sources

[0003] At present, there are many researches on radiation source identification methods based on pattern recognition, which can be generally divided into three categories: comparative query, neural network, and fuzzy set multi-attribute theory. These methods can be applied to the known radiation source based on the constructed radar knowledge base. Identification and discrimination of unknown radiation sources, but the automatic identification of unknown radiation sources is often not directly applicable in complex situations with many parameter changes

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