摘要
SL0算法采用最速下降法和梯度投影原理,将选取的平滑函数逼近0l范数,以求解最优化问题实现信号重建。针对平滑函数逼近性能、算法精确度和算法运算量3个方面进行研究,该文提出一种高效地实现信号重构的算法ICTF-SL0算法。首先,选取复合三角函数作为平滑函数,同时以加权的方式引入全变差(Total Variation,TV)设定约束条件;其次,采用Chaotic迭代代替矩阵分解实现梯度投影。仿真结果证明,相比SL0及其他改进算法,ICTF-SL0能够提高成像精度,降低运算负担,实现稀疏阵列MIMO雷达单快拍成像。
Smoothed l0 （SL0） norm algorithm, using the steepest descent method and gradient projection principle, approaches to l0 norm with selected smooth function, so as to solve the optimization problem and achieve signals reconstruction. A reconstruction algorithm- Improved Composite Trigonometric Function （ICTF-SL0） is proposed, researching approximation of smooth function, precision and calculation load of the algorithm. Firstly, composite trigonometric function is chosen as the smooth one, meanwhile constraint condition is designed by adding Total Variation （TV） as a weight value. And then, matrix decomposition is alternated by using Chaotic iteration to accomplish gradient projection. Finally, by contrast with origin SL0 algorithm and other improved algorithms, simulation results demonstrate that ICTF-SL0 algorithm can availably improve imaging precision, decrease calculation load and achieve signal snapshot imaging under sparse array MIMO radar.
出处
《电子与信息学报》
EI
CSCD
北大核心
2017年第12期2803-2810,共8页
Journal of Electronics & Information Technology
基金
国家自然科学基金(6157010318)~~
