TY - JOUR
T1 - Radar target recognition based on the compounded density estimation of Gamma-SLC
AU - Zhao, Feng
AU - Zhang, Jun Ying
AU - Liu, Jing
AU - Liang, Jun Li
PY - 2008/3
Y1 - 2008/3
N2 - A novel HRRP probability density estimate method, namely Gamma-SLC, is presented by combining Gamma model and stochastic learning of the cumulative (SLC). The presented method has the advantages of high pertinence and high accuracy from Gamma distribution and high adaptability from SLC, but avoids the disadvantage of both. In addition, a new criterion for evaluating the estimation of probability density is designed based on maximum-entropy non-Gaussian measurement. Experimental results using outfield real data demonstrate the validity of the presented method.
AB - A novel HRRP probability density estimate method, namely Gamma-SLC, is presented by combining Gamma model and stochastic learning of the cumulative (SLC). The presented method has the advantages of high pertinence and high accuracy from Gamma distribution and high adaptability from SLC, but avoids the disadvantage of both. In addition, a new criterion for evaluating the estimation of probability density is designed based on maximum-entropy non-Gaussian measurement. Experimental results using outfield real data demonstrate the validity of the presented method.
KW - High resolution range profile (HRRP)
KW - Maximum-entropy principle
KW - Probability density estimation
KW - Stochastic learning of the cumulative (SLC)
UR - https://www.scopus.com/pages/publications/42549159519
M3 - 文章
AN - SCOPUS:42549159519
SN - 1001-506X
VL - 30
SP - 438
EP - 443
JO - Xi Tong Gong Cheng Yu Dian Zi Ji Shu/Systems Engineering and Electronics
JF - Xi Tong Gong Cheng Yu Dian Zi Ji Shu/Systems Engineering and Electronics
IS - 3
ER -