密集杂波背景下模糊编队识别和质心点求取算法研究样本VIP专享

下载后可任意编辑密集杂波背景下模糊编队识别和质心点求取算法讨论熊 伟, 邢凤勇, 王海鹏(海军航空工程学院信息融合讨论所, 山东, 烟台, 264001)摘要: 该文以传感器分辨力较低, 编队成员之间距离较近, 杂波密度大, 出现测量模糊, 不能有效识别出编队成员数量和队形结构为背景, 讨论了编队成员测量值的识别提取和编队质心点确定问题。针对编队成员识别问题, 采纳了以测量值之间距离为门限的循环分割法, 将分布较为密集的测量点作为编队成员提取出来; 针对编队质心点求取问题, 提出了一种基于遗传算法的编队目标质心点确定算法。该文以两个相互交叉的编队为仿真环境, 仿真验证, 循环分割法能够正确的识别出编队成员, 与编队成员坐标平均法相比, 遗传算法能够更为精确的求出编队的质心点, 大大减轻了编队质心点互联的负担, 提高了编队目标跟踪精度。关键词: 编队识别; 测量模糊; 遗传算法; 循环分割中图分类号: TN401; TP391Algorithm Research on Identification and Centroid Obtain of Fuzzy Formation Based on Dense Clutter Background Xiong Wei, Xing Feng-yong, Wang Hai-peng( Research Institute of Information Fusion, Naval Aeronautical Engineering Institute, Yantai ,264001) Abstract: Taking the low sensor resolution, the short distance of the formation member and the dense clutter density as the background, in which condition, the formation structure and 下载后可任意编辑formation member number can not be effectively identified, researched the formation member identification and extraction and the centroid obtain problems. Loop segmentation algorithm based on the threshold of measurement distance was used for the identification of the formation member problem; An algorithm based on genetic algorithm was proposed in order to get the centroid of the formation. In this paper, the two cross-cutting formations were used for the simulation environment, the simulation result proved that Loop segmentation algorithm can recognize the formation member correctly, and compared wi...