TY - GEN
T1 - Unsupervised k-means combined with SOFM structure adaptive radar signal sorting algorithm
AU - Su, Shunqi
AU - Fu, Xiongjun
AU - Zhao, Congxia
AU - Yang, Jingfang
AU - Xie, Min
AU - Gao, Zhifeng
N1 - Publisher Copyright:
© 2019 IEEE.
PY - 2019/12
Y1 - 2019/12
N2 - With the overlapping of signal parameters, signal sorting faces great challenges. K-means clustering algorithm and self-organizing Feature Mapping (SOFM) neural network algorithm are widely used in radar signal sorting. However, the cluster number of k-means algorithm needs to be determined in advance, and the initial cluster center also needs to be randomly selected, so it is easy to fall into local optimal. The accuracy of SOFM neural network sorting results is greatly affected by the preset structure. Aiming at the above two problems, this paper introduces the density dynamic clustering into the traditional k-means clustering algorithm and combines it with SOFM neural network to put forward an unsupervised structural adaptive radar signal sorting algorithm. The simulation results show that the algorithm can effectively solve the problem of signal sorting in the case of parameter space overlap and the computation is small.
AB - With the overlapping of signal parameters, signal sorting faces great challenges. K-means clustering algorithm and self-organizing Feature Mapping (SOFM) neural network algorithm are widely used in radar signal sorting. However, the cluster number of k-means algorithm needs to be determined in advance, and the initial cluster center also needs to be randomly selected, so it is easy to fall into local optimal. The accuracy of SOFM neural network sorting results is greatly affected by the preset structure. Aiming at the above two problems, this paper introduces the density dynamic clustering into the traditional k-means clustering algorithm and combines it with SOFM neural network to put forward an unsupervised structural adaptive radar signal sorting algorithm. The simulation results show that the algorithm can effectively solve the problem of signal sorting in the case of parameter space overlap and the computation is small.
KW - SOFM neural network
KW - radar signal sorting
KW - structural adaptation
KW - unsupervised k-means
UR - http://www.scopus.com/inward/record.url?scp=85091934802&partnerID=8YFLogxK
U2 - 10.1109/ICSIDP47821.2019.9172926
DO - 10.1109/ICSIDP47821.2019.9172926
M3 - Conference contribution
AN - SCOPUS:85091934802
T3 - ICSIDP 2019 - IEEE International Conference on Signal, Information and Data Processing 2019
BT - ICSIDP 2019 - IEEE International Conference on Signal, Information and Data Processing 2019
PB - Institute of Electrical and Electronics Engineers Inc.
T2 - 2019 IEEE International Conference on Signal, Information and Data Processing, ICSIDP 2019
Y2 - 11 December 2019 through 13 December 2019
ER -