Research On Electromagnetic Situation Visualization And Prediction Method

In recent years,with the rapid development of modern high technology,various types of new weapons have emerged endlessly,and command operations are facing huge challenges.Therefore,commanders need to have a complete understanding of multiple sources in a complex battlefield environment while coexisting capabilities and wisdom.And extremely uncertain situation knowledge to meet the requirements of modern battlefield operations fast and accurate,accurate understanding of situation knowledge can scientifically and efficiently assist in commanding operations.The different geographic locations of the battlefield cause different degrees of interference.In the battlefield,the electromagnetic waves sent by the tower may encounter terrain and other terrain during the transmission process,thus blocking the propagation of some signals and weakening the strength of the waves.The battlefield You need to know the causes of these problems as much as possible,and the most intuitive is to get the results through visual methods.At the same time,the prediction of the change trend of the electromagnetic situation is of great significance for the commander to accurately understand the electromagnetic situation and reduce the risk of decision-making.This article mainly studies the algorithm of terrain occlusion signal visualization and situation trend prediction.The main research contents are as follows:(1)An integrated visualization method for terrain occlusion electromagnetic waves is proposed.The terrain occlusion scene is divided into two situations,and different visualization methods are applied in combination with the terrain of different situations,and finally the PNPoly algorithm is combined to achieve the effect of displaying terrain occlusion in the visualization system.(2)In view of the fact that a single BP neural network model cannot accurately predict the historical trend of long-term sequences,an improved original BP network model is proposed.The GRU neural network is combined into the BP model to form the GRU-BP combination model.The influence of GRU on the correlation of time series data also includes the self-learning and adaptive ability of BP neural network,which makes the situation prediction analysis in a longer time more accurate.(3)According to the actual project requirements,the design and realization of the electromagnetic situation visualization and prediction system.Applying the above two methods to the system further verifies the effectiveness and feasibility of the algorithm.Through the application of signal occlusion visualization and electromagnetic situation prediction in the electromagnetic situation visualization system,we can see the importance of the overall visualization system of situation prediction and terrain occlusion electromagnetic waves in simulating battlefield confrontation systems,and we can intuitively observe what happens to the electromagnetic situation Predict trends in various situations.It has reference significance for future research on battlefield visualization system.