基于ARLPM改进的海面目标检测新方法

New Method of Target Detection in the Improved Sea on the ARLPM

舰载(或岸基)雷达对海面小目标检测是一个重要而且困难的课题。最大极点幅度检测(ARLPM)是目前实用性较强的一种方法,特别在短时检测方面有着不错的效果。但该算法的缺陷在于只利用了海杂波AR谱的最大幅度极点的谱宽特性,文中在ARLPM的基础上提出了一种新的基于AR模型的方法——双参量检测,它同时利用到了极点的谱宽和谱峰。最后,利用真实海杂波数据对该方法作了实验,通过比较表明,双参量检测优于原方法。

Ship-based （or bank-based） radars encounter a important and difficult problem of small targets detection in sea clutter. The autoregressive largest pole magnitude （ ARLPM） is strong practical method, especially in the area of short time detection. But ,the shortcoming of the arithmetic is that only using the pole＇s Spectral width of AR Spectral. The paper advances a new method based on AR model from ARLPM two paramemter detection. , which uses both the spectral width and the spectral height, there has a simulate experiment using the true sea clutter data . The compare shows the two parameter detection method is better than the ARLPM.