【作者】 吴振辉； 董朝阳；

【Author】 WU Zhen-hui1, DONG Chao-yang2 (1.School of Aerospace Science and Engineering, Beihang University, Beijing 100083, China; 2. School of Automation, Beihang University, Beijing 100083, China)

【机构】 北京航空航天大学航空科学与工程学院； 北京航空航天大学自动化科学与电气工程学院；

【摘要】 提出一种基于H∞滤波器的主被动雷达的最小方差数据融合算法。由于噪声方差在实际测量过程中是随时间变化的,甚至在有些干扰情况下是剧烈变化的。针对这一问题首先设计了一个H∞滤波器,该滤波器通过调节参数来增强其对外界干扰的鲁棒性,然后采用H∞滤波器分别对主被动雷达测量数据进行滤波,最后将滤波结果进行最小方差数据融合,较大的提高了融合算法对测量噪声干扰的适应性和鲁棒性。仿真结果表明,采用提出的算法所得到的滤波误差方差较小,且对外界大噪声具有很强的鲁棒性。更多还原

【Abstract】 A minimum mean variance data fusion algorithm using H∞ filter based on active/passive radar was proposed. In the application, the noise variance is time-varying, even intensively varying under disturbance conditions. First, an H∞ filter was designed, which keeps its robustness by constantly adjusting parameter. Then the measurements from active/passive radar were filtered by the H∞ filter. Finally, minimum mean variance data fusion algorithm was used to fuse the filtered data, so the adaptability and robustness to measurement noise was significantly improved. Simulation results show that the resulted error variance is small and it is robust to external disturbance.更多还原