TY - GEN
T1 - Target and Interference Signal Recognition Method for FM Proximity Detector Based on Multidimensional Feature Fusion
AU - Yan, Xiaopeng
AU - An, Tai
AU - Wang, Yongzhou
AU - Kong, Zhijie
AU - Dai, Jian
N1 - Publisher Copyright:
© 2024 IEEE.
PY - 2024
Y1 - 2024
N2 - 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.
AB - 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.
KW - FM proximity detector
KW - Interference recognition
KW - feature extraction
KW - support vector machine
UR - https://www.scopus.com/pages/publications/86000008055
U2 - 10.1109/ACTCE65085.2024.00104
DO - 10.1109/ACTCE65085.2024.00104
M3 - Conference contribution
AN - SCOPUS:86000008055
T3 - Proceedings - 2024 International Seminar on Artificial Intelligence, Computer Technology and Control Engineering, ACTCE 2024
SP - 481
EP - 487
BT - Proceedings - 2024 International Seminar on Artificial Intelligence, Computer Technology and Control Engineering, ACTCE 2024
PB - Institute of Electrical and Electronics Engineers Inc.
T2 - 2024 International Seminar on Artificial Intelligence, Computer Technology and Control Engineering, ACTCE 2024
Y2 - 28 September 2024 through 29 September 2024
ER -