Dynamic electromagnetic spectrum posture method and system based on tensor and neural network

Abstract

The invention discloses a tensor and neural network-based dynamic electromagnetic spectrum posture method and system. The method comprises the steps of obtaining spectrum data of an area surrounded by current unmanned aerial vehicle flight; performing analog-to-digital conversion on the frequency spectrum information, then reading the frequency spectrum information after performing fast Fourier transform, and checking whether the frequency spectrum data displayed for one time is full or not; then an original matrix is constructed, and the constructed original matrix is visualized; performing data completion on the visualized original matrix to obtain an optimized final completion matrix; and inputting the optimized final completion matrix result value into a BP neural network for fuzzification processing to obtain a final completion matrix value, drawing a completed spectrum posture two-dimensional graph by using the final completion matrix value, drawing a three-dimensional posture spatial resolution graph, and displaying a spectrum posture signal of the dynamic signal according to time and frequency changes. According to the invention, by monitoring the radio signal and the electromagnetic spectrum posture, the purposes of eliminating electromagnetic interference and improving the spectrum utilization rate are achieved.

Description

technical field [0001] The invention belongs to the technical field of communication engineering, and in particular relates to a tensor and neural network-based dynamic electromagnetic spectrum posture method and system. Background technique [0002] Early spectrum monitoring systems mainly relied on fixed monitoring stations, aiming to monitor illegal radio signals in communication, traffic, broadcasting, etc., so as to eliminate electromagnetic interference and improve spectrum utilization. However, each fixed monitoring station needs to be equipped with professionals, and it is impossible to monitor for a long time in a monitoring environment that cannot be stationed for a long time. In addition, the cost of fixed monitoring stations is relatively high, the construction period is long, and it is generally difficult to achieve large-scale deployment. [0003] At this stage, the spectrum situation generation technology is based on spectrum sensing to further analyze and pr...

AI Technical Summary

Problems solved by technology

However, each fixed monitoring station needs to be equipped with professionals. For monitoring environments that cannot be stationed for a long time, it is impossible to monitor for a long time

In addition, the cost of fixed monitoring stations is relatively high, the construction period is long, and it is generally difficult to achieve large-scale deployment

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