TY - JOUR
T1 - An Efficient Radon Fourier Transform-Based Coherent Integration Method for Target Detection
AU - Lang, Ping
AU - Fu, Xiongjun
AU - Dong, Jian
AU - Yang, Jian
N1 - Publisher Copyright:
© 2004-2012 IEEE.
PY - 2023
Y1 - 2023
N2 - The radon Fourier transform (RFT)-based coherent integration is an important target detection method. However, the computational cost of parameter searching and blind-speed sidelobe (BSSL) remain the main challenges in actual RFT applications. In this letter, we propose a Whale optimization algorithm-based RFT (WOA-RFT) to accelerate the parameter searching process and improve BSSL suppression performance. First, the discrete RFT signal model is derived; WOA-RFT is then proposed to speed up the RFT and suppress BSSL. The simulation results demonstrate that our proposed method has a better performance in terms of parameter estimation accuracy, BSSL suppression capability, and computational cost, compared to some existing methods.
AB - The radon Fourier transform (RFT)-based coherent integration is an important target detection method. However, the computational cost of parameter searching and blind-speed sidelobe (BSSL) remain the main challenges in actual RFT applications. In this letter, we propose a Whale optimization algorithm-based RFT (WOA-RFT) to accelerate the parameter searching process and improve BSSL suppression performance. First, the discrete RFT signal model is derived; WOA-RFT is then proposed to speed up the RFT and suppress BSSL. The simulation results demonstrate that our proposed method has a better performance in terms of parameter estimation accuracy, BSSL suppression capability, and computational cost, compared to some existing methods.
KW - Coherent integration
KW - Whale optimization algorithm (WOA)
KW - radar target detection
KW - radon Fourier transform (RFT)
UR - http://www.scopus.com/inward/record.url?scp=85149368920&partnerID=8YFLogxK
U2 - 10.1109/LGRS.2023.3246051
DO - 10.1109/LGRS.2023.3246051
M3 - Article
AN - SCOPUS:85149368920
SN - 1545-598X
VL - 20
JO - IEEE Geoscience and Remote Sensing Letters
JF - IEEE Geoscience and Remote Sensing Letters
M1 - 3501905
ER -