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Radar target detection method based on particle filter theory under correlated non-Gaussian clutter backgrounds

机译:相关非高斯杂波背景下基于粒子滤波理论的雷达目标检测方法

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It is not easy to establish statistical detection model under 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 detection model is established. This method resolves the difficulties that it is almost unable to establish statistical detection model under correlated non-Gaussian clutter backgrounds. Simulations show that the detection performances of the proposed method are better than the traditional method under both the correlated Gaussian clutter and correlated non-Gaussian clutter backgrounds.
机译:当参数随机或未知时,在相关的非高斯杂波背景下建立统计检测模型并不容易。基于粒子滤波,所提出的方法通过根据未知参数的概率分布函数将积分操作转换为总体操作来计算似然函数,并且建立了一般的雷达目标似然比检测模型。该方法解决了在相关的非高斯杂波背景下几乎无法建立统计检测模型的困难。仿真表明,所提出的方法的检测性能优于相关高斯杂波和相关的非高斯杂波背景下的传统方法。

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