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充分利用探测环境的先验信息是提高雷达探测能力的有效途径之一。先验信息必须在雷达检测算法设计阶段确定下来,因此先验信息与当前探测环境之间可能存在不一致性。以复合高斯杂波中的、利用纹理分量先验信息的知识辅助(KA)检测器作为研究对象,首先建立了该检测器检测性能与先验分布参数失配之间的量化关系,然后根据给定的杂波探测环境模型参数,分析了先验模型失配对检测性能的影响。分析结果表明:知识辅助检测器的稳健性与当前探测环境模型参数有关。进一步给出了先验模型失配的容许区间,当先验模型参数在这个区间内,知识辅助检测器性能优于不使用先验信息的检测器性能。
Making full use of the priori information of the detection environment is one of the effective ways to improve the radar detection capability. Prior information must be determined at the radar detection algorithm design stage, so there may be inconsistencies between the prior information and the current detection environment. Taking knowledge aided (KA) detector which uses a priori information of texture components in composite Gaussian clutter as the research object, a quantitative relationship between the detection performance of the detector and the mismatch of prior distribution parameters is established. Then, The clutter detection environment model parameters are analyzed, and the influence of the prior model mismatch on the detection performance is analyzed. The analysis results show that the robustness of the knowledge-based detector is related to the parameters of the current detection environment model. Furthermore, the allowable interval of prior model mismatch is given. When the parameters of the prior model are in this interval, the performance of the knowledge-based detector is better than that of the detector without prior information.