A CNN-Based Electromagnetic Interference Source Identification and Location System

An electromagnetic environment monitoring system can measure the spectrum in a given environment, find abnormal signals and alarms, and find the direction of interference signals, which is of great significance in both military and civilian fields. However, with the rapid development of radio technology, a variety of radio equipment has appeared, making the electromagnetic environment more complex and also producing a variety of broadband electromagnetic interference sources (EMIS) that are extremely difficult to locate. This work presents an EMIS identification and location system design based on convolutional neural network (CNN) for the airport electromagnetic environment. The single-channel direction-finding antenna array (DFAA) is used to find the direction of EMIS. Then, the location of EMIS is obtained by interactive positioning technology. The designed system is demonstrated on-site near the airport, and the results show that it can realize the accurate identification and location of EMIS, which provides the basis for quickly finding EMIS.