TY - GEN
T1 - Polarimetric STAP via clutter spectrum reconstruction
AU - Zhao, Kang
AU - Huang, Yulin
AU - Liu, Zhiwen
AU - Xu, Yougen
AU - Shi, Shuli
N1 - Publisher Copyright:
© 2019 Association for Computing Machinery.
PY - 2019/9/20
Y1 - 2019/9/20
N2 - A new polarimetric space-time adaptive processing (pSTAP) approach is proposed to clutter suppression for weak target detection under short data samples. In the method, the target vector (also known as the target polarization-space-time steering vector) is determined based on the maximum likelihood scheme, while the clutter polarization-space-time spectrum (profile) is reconstructed by using a newly developed polarimetric sparse recovery technique. Numerical results are given to illustrate the performance of the proposed method.
AB - A new polarimetric space-time adaptive processing (pSTAP) approach is proposed to clutter suppression for weak target detection under short data samples. In the method, the target vector (also known as the target polarization-space-time steering vector) is determined based on the maximum likelihood scheme, while the clutter polarization-space-time spectrum (profile) is reconstructed by using a newly developed polarimetric sparse recovery technique. Numerical results are given to illustrate the performance of the proposed method.
KW - Polarization-space-time adaptive processing
KW - Sparse dictionary matrix
KW - Spectrum estimation
UR - http://www.scopus.com/inward/record.url?scp=85077216301&partnerID=8YFLogxK
U2 - 10.1145/3364908.3364911
DO - 10.1145/3364908.3364911
M3 - Conference contribution
AN - SCOPUS:85077216301
T3 - ACM International Conference Proceeding Series
SP - 99
EP - 102
BT - SSPS 2019 - 2019 International Symposium on Signal Processing Systems
PB - Association for Computing Machinery
T2 - 2019 International Symposium on Signal Processing Systems, SSPS 2019
Y2 - 20 September 2019 through 22 September 2019
ER -