| 引用本文: | 鲁亚飞,吴岸平,陈清阳.无人机对地目标多帧融合定位与误差收敛特性分析.[J].国防科技大学学报,2021,43(2):66-73.[点击复制] |
| LU Yafei,WU Anping,CHEN Qingyang.Analysis of UAV multi-frame fusion location and error convergence characteristic for ground target[J].Journal of National University of Defense Technology,2021,43(2):66-73[点击复制] |
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| 无人机对地目标多帧融合定位与误差收敛特性分析 |
| 鲁亚飞1,吴岸平1,2,陈清阳1 |
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(1. 国防科技大学 空天科学学院, 湖南 长沙 410073;2. 中国空气动力研究与发展中心 超高速空气动力研究所, 四川 绵阳 621000)
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| 摘要: |
| 对地目标高精度定位是无人机开展目标侦察、火力引导、效能评估等的重要前提,然而无人机对地目标定位精度受到误差因素多、传递链长等因素的制约。采用基于卡尔曼滤波的图像多帧配准对地面目标定位的方法,通过融合无人机获取的多帧目标图像,基于卡尔曼滤波方法,研究无人机对地目标高精度融合定位方法,并引入蒙特卡洛法进行仿真,分析基于卡尔曼滤波法多帧融合定位的误差收敛性、大小和分布,分析观测间隔、视线俯仰角等对误差收敛性的影响,形成若干提高定位精度的建议。 |
| 关键词: 无人机 对地定位 卡尔曼滤波 误差收敛性 |
| DOI：10.11887/j.cn.202102010 |
| 投稿日期：2019-08-26 |
| 基金项目:湖南省自然科学基金资助项目(2017JJ3366)；基础加强计划技术领域基金资助项目(2019JCJQJJ210) |
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| Analysis of UAV multi-frame fusion location and error convergence characteristic for ground target |
| LU Yafei1, WU Anping1,2, CHEN Qingyang1 |
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(1. College of Aerospace Science and Engineering, National University of Defense Technology, Changsha 410073, China;2. Hypervelocity Aerodynamics Institute, China Aerodynamics Research and Development Center, Mianyang 621000, China)
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| Abstract: |
| High-precision positioning of the ground target is an important premise for the UAV (unmanned aerial vehicle) to carry out target reconnaissance, firepower guidance, effectiveness evaluation, etc. However, the accuracy of the UAV′ s target positioning is limited by factors such as many error factors and long transmission chain. The method of multi-frame image registration method based on Kalman filter for ground target location was studied. By combining the multi-frame target image acquired by UAV, the high-precision fusion positioning of UAV to ground target was studied based on Kalman filter. Monte Carlo method was introduced to simulate the error convergence, value and distribution of multi-frame fusion location method based on Kalman filter. The influence of observation interval and line-of-sight elevation angle on error convergence was analyzed. Several suggestions for improving the positioning accuracy were proposed. |
| Keywords: unmanned aerial vehicles target location Kalman filter error convergence |
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