基于蒙特卡罗法的卡尔曼滤波算法在无人直升机探测中的应用  

Application of Monte Carlo Method Based Kalman Filtering Algorithm in Unmanned Helicopter for Target Detection

作　　者：谷晓星 李雷[1] 孙黎静 张宇 邱忠围 GU Xiao-xing;LI Lei;SUN Li-jing;ZHANG Yu;QIU Zhong-wei(China Helicopter Research and Development Institute,Jingdezhen 333000,China)

机构地区：[1]中国直升机设计研究所

出　　处：《电光与控制》2019年第6期89-91,共3页Electronics Optics & Control

摘　　要：无人直升机技术的迅猛发展,使得无人直升机越来越频繁地应用于实际作战。使用无人直升机辅助舰艇进行探测,可以大大扩展舰艇的探测范围,为指挥人员提供更全面的战场信息。近年来,卡尔曼滤波算法在通信、导航、制导与控制等多领域均有所应用,各种改良卡尔曼滤波算法也相继被提出。为提高无人直升机的探测精度,提出一种基于蒙特卡罗法的卡尔曼滤波算法,并对其精度进行了分析。With the rapid development of unmanned helicopter technology,the unmanned helicopters are used more and more frequently in battlefield.When using the unmanned helicopters to aid the warships for target detection,the detection range can be enlarged greatly,which can supply more comprehensive battlefield information to the commanders.In recent years,Kalman filtering are finding applications in the areas of communication,navigation,guidance and control,and various improved Kalman filtering algorithms have been proposed.In order to improve the detection precision of the unmanned helicopter,a Kalman filtering algorithm based on Monte Carlo method is presented here,and an analysis is made to its precision.

关 键 词：无人直升机 卡尔曼滤波 精度分析 目标探测 

分 类 号：V279[航空宇航科学与技术—飞行器设计]