Design Of Magnetic Detection Module And Research On Typical Target Recognition Algorithm

With the increasing complexity of the modern battlefield environment.Improving the anti-jamming capability and target recognition capability of the weapon system is of great significance to the precise strike of the target.The missile-borne magnetic detection module is a target detection device capable of passive detection.When the magnetic detection module detects the target,it can obtain the magnetic anomaly information in the space around the target so as to realize the judgment and recognition of the armored target.Geomagnetic detection has the characteristics of strong anti-interference ability,immunity from battlefield soot,high spatial resolution and good detection sensitivity.It has important research and application value in military applications.This article takes the armor target as the research object.Through the research on the working principle of geomagnetic detection,the influence of armored targets on the surrounding magnetic field is analyzed.And the mathematical calculation of the magnetic anomaly intensity around the armored target.Based on the analysis of target detection performance,the overall scheme of the magnetic detection module is designed.Focus on the completion of the magnetic detection module signal receiving circuit,analog signal conditioning circuit and main control circuit design,and simulate and verify each part of the signal conditioning circuit,obtain the implementation plan of each module circuit and complete the PCB drawing,produced a physical magnetic detection module.And cooperate with relevant units to complete the debugging of the magnetic detection module.At the same time,a magnetic detection module placed on the head of the projectile is used as the detection device.Aimed at the problem of low target recognition probability in geomagnetic detection.A target recognition algorithm based on dynamic threshold,fuzzy inference and BP neural network is designed.The algorithm uses wavelet denoising and moving average filtering on the magnetic anomaly signals of the target collected by the magnetic detection module to digitally filter the signals,calculate the appropriate threshold.Determine whether there is a target through a target detection algorithm based on a dynamic threshold.On this basis,the characteristic value of the target magnetic anomaly signal is extracted.Compare the detected target feature information with the real target feature parameters.The target recognition algorithm based on fuzzy reasoning and BP neural network is designed to obtain the final recognition probability of the target.Experimental and simulation results show that this method can effectively complete the recognition of armored targets,with a recognition probability of 87.3%.