摘要
在非高斯相关杂波背景、参数随机或未知的情况下,通常难以甚至无法建立统计检测模型。针对此问题,基于粒子滤波方法,根据未知参数的概率分布函数抽取粒子,将复杂积分运算转化为求和运算求取似然函数,给出了一种雷达目标似然比检测的通用模型,较好地解决了非高斯相关杂波条件下无法得到检测统计量的问题。此外,以复SG-Alpha稳定分布作为非高斯相关杂波分布模型,给出了基于粒子滤波的检测统计模型,并对本文方法与传统的检测方法在高斯相关杂波和非高斯相关杂波背景下的检测性能进行了仿真比较,验证了算法的有效性。
It is not easy to establish statistical test model in correlated non-Gaussian clutter backgrounds when parameter is stochastic or unknown. Based on the particle filtering, the proposed method calculates the likelihood function by transforming the integral operation to the sum operation according to the probability distribution function of unknown parameter, and a general radar target likelihood-ratio detec- tion model is established. This method solves the difficulties that it is unable to establish statistical test model in correlated non-Gaussian clutter backgrounds. Taking SG-Alpha stable distribution as the model of correlated non-Gaussian clutter, a statistical test method based on particle filtering is established. Moreover, simulations show that the detection performances of the proposed method are better than the traditional method both in correlated Gaussian and non-Gaussian clutter backgrounds.
出处
《电波科学学报》
EI
CSCD
北大核心
2012年第5期1005-1011,共7页
Chinese Journal of Radio Science
基金
国家自然科学基金资助项目(No.60872156
No.61179014)
关键词
非高斯相关杂波
粒子滤波
统计检测
似然函数
概率分布
correlated non-Gaussian clutter
particle filtering
statistical test
like-lihood function
probability distribution
