引用本文: | 吴岸平,鲁亚飞,郭正,等.采用改进Sage-Husa自适应滤波的运动目标三维定位方法[J].国防科技大学学报,2023,45(2):146-154.[点击复制] |
WU Anping,LU Yafei,GUO Zheng,et al.Three-dimensional localization for moving target using modified Sage-Husa adaptive filter[J].Journal of National University of Defense Technology,2023,45(2):146-154[点击复制] |
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采用改进Sage-Husa自适应滤波的运动目标三维定位方法 |
吴岸平1,2,鲁亚飞1,郭正1,侯中喜1 |
(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: |
提出不依赖于测距信息,利用两架基于视觉的无人机对运动目标进行三维交会定位的方法。采用多模型交互方法实现在不预知目标运动模式的条件下对运动目标的实时定位;采用改进的Sage-Husa自适应滤波算法,综合协方差匹配技术和正定性判断,提高了定位精度。为评估这些方法的性能,模拟真实观测条件进行仿真。结果表明,提出的方法可以实时对运动目标的三维坐标进行估计。改进的Sage-Husa自适应滤波算法可以显著提高定位精度,在90°观测夹角下,平均估计误差从27.13 m降低到14.62 m。仿真研究了两无人机观测夹角对定位的影响,结果表明:过小的夹角不利于定位精度的提高;较大的夹角对无滤波定位方法有较好的效果,但对基于改进的Sage-Husa自适应滤波算法的定位方法影响并不明显。 |
关键词: 无人机 运动目标定位 三维交会模型 自适应滤波 多模型交互 |
DOI:10.11887/j.cn.202302017 |
投稿日期:2021-05-31 |
基金项目:国家自然科学基金资助项目(61801495);基础技术强化计划资助项目(2019JCJQJJ210) |
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Three-dimensional localization for moving target using modified Sage-Husa adaptive filter |
WU Anping1,2, LU Yafei1, GUO Zheng1, HOU Zhongxi1 |
(1. Colloege 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: |
A three-dimensional intersection localization method for moving target using two vision-based UAVs (unmanned aerial vehicles), which did not rely on the distance information from the target point to the UAV was proposed. An interacting multiple model estimator was adopted to the localization method to solve the problem of not knowing the motion form of the moving target. A modified Sage-Husa adaptive filtering algorithm that synthesized the covariance matching technique and the positive definiteness judgment was used to improve the accuracy of localization. To assess the performance of these approaches, a set of simulations that carried out under realistic conditions were presented. Results show that the method proposed can get the accurate three-dimensional coordinates of the target. The modified Sage-Husa adaptive filtering algorithm can improve the localization accuracy significantly, with the average estimation error reduced from 27.13 m to 14.62 m under the intersection angle of 90°. The influence of the intersection angle on localization was studied in the simulation, which shows that too small intersection angle is not conductive to the improvement of localization accuracy, a larger intersection angle is good for the localization method without filtering, but the effect on the method with the modified Sage-Husa adaptive filtering algorithm is not significant. |
Keywords: UAVs moving target localization three-dimensional intersection model adaptive filter interacting multiple model |
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