基于降维稀疏重构的高效数据域STAP算法研究

摘要

本文基于信号稀疏重构技术，研究利用待检测样本直接进行动目标检测的高效空时自适应处理（STAP ）方案。该方案对时域降维的阵元-多普勒域数据采用空域稀疏重构技术估计高分辨率角度-多普勒谱，进而基于稀疏空时谱研究知识辅助的动目标检测算法。理论分析和仿真实验结果表明：本文算法能有效抑制杂波实现慢动目标检测，且运算量小易于实时并行处理。%An efficient direct data domain STAP scheme based on a sparse reconstruction of the primary data is presented to effectively detect ground moving targets .To reduce the computational complexity ,the proposed method obtains the high resolution angle-Doppler spectrum by finding the sparsest coefficients using the reduced-dimension data in element-Doppler domain .There-fore ,based on the distinct image features of clutter and targets signals ,a knowledge-aided moving targets detection algorithm is also introduced .The effectiveness of the proposed approach is shown by both theoretical analysis and simulation results .This scheme is computationally efficient for real-time parallel processing .