【摘要】 在多部雷达同时跟踪低空 /超低空飞行的机动小目标时 ,因受低空杂波、电子干扰和雷达自身探测精度等因素影响 ,易使部分雷达探测的数据不完整、不精确、不可靠 ,甚至相互矛盾 ,结果造成融合中心数据处理精度下降。针对这一情况 ,本文应用灰色系统理论的绝对关联度定义和性质 ,提出了一种改进的绝对关联度计算方法。并在此基础上将多部雷达经一次融合后的数据作为特征数据进行优势分析 ,把每时送入融合中心比较差的雷达数据用特征数据替换 ,再进行二次融合。仿真结果表明 ,应用改进的绝对关联度对雷达数据进行灰色优势分析和二次融合 ,可进一步提高雷达系统的跟踪精度和可靠性更多还原

【Abstract】 When multi radars track low altitude or super low altitude flying maneuvering little targets at the same time, as they are influenced by low altitude mix waves, electronic jamming and probe precision of radars themselves factors, it usually makes some radar probe data uncompleted, imprecise, unreliable and even mutual contradictory. Result makes the precision of the fusion center data processing descend. Aiming at this case, this paper uses the definition and property of absolute correlation degree of the grey system theory, presents a improvable computation method of absolute correlation degree. In addition, the first fusion data is regarded as the character data using superior analysis to replace the precision lower radar data with the first fusion data per time, and then makes them fusion again. Simulational results indicate that the reliability and the tracking precision of the system can be improved by using improvable absolute correlation degree to grey superior analysis and the second data fusion.更多还原