Angular super-resolution using sparse multi-layer iterative algorithm for sparse arrays
摘要
This paper proposes a two-dimensional(2D)angular super-resolution framework for sparse arrays under the single snapshot condition.The azimuth-elevation 2D angular super-resolution model is established,which shows the relationship between the 2D angular super-resolution image and the signal.Using this model,the 2D angular super-resolution problem is transformed into the beyond linear optimization problem.In order to efficiently and accurately address this optimization problem,we propose the sparse multi-layer iterative(SMLI)algo-rithm based on beyond linear signal processing(BLiSP)theory.During the layered iterative process,the solution region is con-tinuously narrowed.The constructed nonlinear weighting matrix and sparse constraint coefficient enhance the ability to differenti-ate between the effect of signal and noise in solving the beyond linear optimization problem.Additionally,the nonlinear weight-ing matrix can be adaptively updated during the solving process,ensuring high-performance angular super-resolution results under different signal-to-noise ratios(SNRs).Experiments con-firm the proposed method's effectiveness and robustness.
年，卷(期)：
2026, 37(4)
机标分类号：
TP391.41
O157.5
S232.4
在线出版日期：
2026年9月10日
