Regular Section
Passive Localization Algorithm for Spaceborne SAR Using NYFR and Sparse Bayesian Learning
2019 Volume E102.A Issue 3 Pages 581-585
Details
2019 Volume E102.A Issue 3 Pages 581-585
A novel Nyquist Folding Receiver (NYFR) based passive localization algorithm with Sparse Bayesian Learning (SBL) is proposed to estimate the position of a spaceborne Synthetic Aperture Radar (SAR).Taking the geometry and kinematics of a satellite into consideration, this paper presents a surveillance geometry model, which formulates the localization problem into a sparse vector recovery problem. A NYFR technology is utilized to intercept the SAR signal. Then, a convergence algorithm with SBL is introduced to recover the sparse vector. Furthermore, simulation results demonstrate the availability and performance of our algorithm.
