引用本文: | 韦道知,赵岩,黄树彩,等.复合导引头多源异步信息融合精确拦截算法[J].国防科技大学学报,2016,38(3):154-159.[点击复制] |
WEI Daozhi,ZHAO Yan,HUANG Shucai,et al.Precise interception method of multi-source asynchronous information fusion for combined seeker[J].Journal of National University of Defense Technology,2016,38(3):154-159[点击复制] |
|
|
|
本文已被:浏览 7519次 下载 5757次 |
复合导引头多源异步信息融合精确拦截算法 |
韦道知1, 赵岩1, 黄树彩1, 陈宸2 |
(1.空军工程大学 防空反导学院, 陕西 西安 710051;2.空军装备研究院地面防空装备研究所, 北京 100085)
|
摘要: |
针对单一制导体制难以满足现代战场作战需求且多传感器数据更新率不同步的问题,建立一种新的微惯导/毫米波/红外复合制导体制,研究了该体制下多传感器异步信息融合的时间同步和空间配准问题;提出一种自适应无迹卡尔曼滤波算法,该算法采用预测残差构造状态模型误差统计量,通过自适应因子调整状态模型信息对状态参数估值的贡献,有效控制状态模型噪声异常对状态参数估值的影响。将提出的算法应用到微惯导/毫米波/红外复合制导系统中进行仿真验证,结果表明,提出的自适应无迹卡尔曼滤波算法的解算精度高于标准扩展卡尔曼滤波和无迹卡尔曼滤波算法,能有效提高导弹的制导的解算精度。 |
关键词: 复合制导 地空导弹 信息融合 非线性滤波 |
DOI:10.11887/j.cn.201603026 |
投稿日期:2015-05-04 |
基金项目:航空科学基金资助项目(20130196004) |
|
Precise interception method of multi-source asynchronous information fusion for combined seeker |
WEI Daozhi1, ZHAO Yan1, HUANG Shucai1, CHEN Chen2 |
(1. Air and Missile Defense College, Air Force Engineering University, Xi′an 710051, China;2. The Air Force Armaments Academy Equipment Institute of Land-based Air Defence, Beijing 100085, China)
|
Abstract: |
In view of the problems that sole guide system cannot meet the modern battlefield demand and data update of multi-sensor is not synchronized, a new MIMU/MMW/IR (miniature inertial measurement unit/ millimeter wave/infrared) composite guidance system was built and the time synchronization and space match problems of multi-sensor asynchronous information fusion in this system were studied. A novel adaptive UKF (unscented Kalman filter) algorithm was presented. The statistics of status model error was built by prediction error in this algorithm; contribution of status model information to status parameter estimation was adjusted by adaptive factor. So the influence of status model noise is effectively regulated. The proposed algorithm was applied to the MIMU/MMW/IR compound guidance system and the algorithm performance was tested. The simulation results show that the adaptive UKF is better than the standard UKF and extended Kalman filter, and it can improve the positioning precision effectively. |
Keywords: composite guidance surface to air missile information fusion nonlinear filtering |
|
|