摘要
由于杂波非高斯特性和相关特性的影响,传统的动目标检测(moving target detection,MTD)技术的检测性能严重下降,针对该问题,基于对称α稳定分布(symmetricαstable,SαS)杂波模型和自回归(auto regressive,AR)模型理论,提出了一种基于ARSαS模型参数估计的雷达目标检测方法。该方法基于SαS模型,通过幂变换抑制杂波的非高斯特性,以及通过基于广义尤拉-沃克方程参数估计的AR模型白化杂波,应用快速傅里叶变换实现对目标信号的积累,以提高信杂比。仿真实验和实测数据验证表明,所提方法在非高斯相关杂波背景下的检测性能明显优于传统的MTD方法。
The detection performance of the moving target detection （MTD） method descends badly in non- Gaussian correlated clutter background. Therefore, a radar target detection method based on parameter estima- tion for auto regressive symmetric α stahle（ARSαS） model is proposed, which is obtained by the a-stable distri- bution clutter model and the AR model. The proposed method suppresses the non-Gaussian clutter by the signed power and whitens the correlated clutter by the AR model estimated by the Yule-Walker equation. Finally the fast Fourier transform is used to accumulate the target signal and get higher signal clutter ratio. Simulations and real data results show that the detection performance of the proposed method obviously outperforms the MTD method in non-Gaussian correlated clutter background.
出处
《系统工程与电子技术》
EI
CSCD
北大核心
2015年第4期782-788,共7页
Systems Engineering and Electronics
基金
国家自然科学基金(61179014)资助课题
关键词
非高斯相关杂波
Α稳定分布
自回归模型
杂波白化
non Gaussian correlated clutter
α-stable distribution
auto regressive （AR） model
clutter whitening
