Research on Real Time Evaluation Technology of Jamming Effect of Laser Directional Jamming Equipment Based on LSTM

A real-time evaluation method for jamming effect of laser directional jamming equipment based on impact point prediction is proposed. By conducting research on the characteristics of precision guided weapons, establishing a six degree of freedom model, using Simulink for trajectory simulation, and establishing its motion characteristic database. An impact point prediction model is established based on long short-term memory (LSTM) neural network. The sample data in the motion characteristic database is divided into label pairs using repeated segmentation and sliding window method, and input into the neural network for offline training. After training, the network processes the trajectory data of precision guided weapons under interference conditions obtained from real-time positioning, predicts their trajectory and impact point, calculates the probability of damage, and combines the jamming effect evaluation criteria to achieve real-time effectiveness evaluation of electro-optical countermeasures. The experimental results show that the prediction error of the impact point is 8.75m. The target killing probability calculated based on the predicted impact point and the actual impact point is consistent, indicating that the jamming effect evaluation result is effective. The relevant research results can provide some reference for the real-time evaluation of the effectiveness of optoelectronic countermeasures.