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With the rapid development of science and technology, testing equipment and testing methods are constantly updated. Radar detectors have the advantages of losslessness, high efficiency, high resolution, and high-speed radar image capture. They can accurately locate defects in railway tunnels, respond to hidden dangers in time, and provide strong technical support for transportation. This paper proposes to optimize the defect detection of railway tunnel radar through the combination of multisensor technology and active interference suppression algorithm and designs the corresponding sensor system according to the content. This article analyzes several factors that affect the radar detection effect and makes a detailed summary from the detection environment and other aspects. At the same time, it uses the multisensor system combined with active interference suppression algorithm to design a railway tunnel detection simulation experiment. Experimental results show that the use of multisensors combined with active interference suppression algorithm to optimize radar detection can effectively improve the accuracy of railway tunnel defect detection. Through the analysis of the results of tunnel defect detection, the detection accuracy of this paper has reached 98.8%, which can provide an effective reference for the detection of railway tunnels.

computational intelligence and neuroscience

Optimal Defect Detection and Sensing System of Railway Tunnel Radar considering Multisensor System Combined with Active Interference Suppression Algorithm