Abstract
In response to the anti-interference problem faced by FM proximity detectors, this paper proposes an accurate identification method for target and interference signals based on multidimensional feature fusion for forwarded interference. By analyzing the working principle of detection, target echo characteristics, and detector response under interference, feature parameters of detector echo signals are extracted. Support vector machines are used to classify samples and complete the classification and recognition of targets and interference. Through verification in this article, the classification accuracy of this method can reach 99%, which is a recognition method that can greatly improve the anti-interference ability of short-range detectors.