摘要
近年来,随着空间技术的进步,大部分国家逐渐开始关注深空小天体探测,这属于典型空间非合作目标探测任务.与合作目标相比,空间非合作目标具有典型的特征,如无先验知识、无合作标识和无通信等.但是在附着之前,必须获取空间非合作目标的必要信息.如何通过非接触的方式获取目标的姿态、角速度和惯性参数是深空小天体探测的重要技术之一.研究工作提出了一种估计未知非合作目标姿态、运动与惯量特性的新方法,仿真证明了在不同目标特性与状态工况下的方法有效性.此外,主惯量参数比的准确率能够达到90%.在所有这些工况中,非常重要的环节是视觉算法必须保证良好且精确的目标特征点信息.总之,本文给出了一种有前景与有效的用于小天体附着前的运动与参数辨识方法,此方法非常高效且适合星上应用.
Recently, with advances in aerospace technology, most countries have gradually shifted their attention to detecting small celestial bodies, which belong to the noncooperative space target task. In contrast to the cooperative space target, the noncooperative space target has typical characteristics, such as no prior knowledge, no cooperative sign, and no communication. However, necessary information on the noncooperative space target must be acquired before capturing.Obtaining the attitude, angular velocity, and inertia parameters of targets without contacting them is becoming a prominent technology for detecting small celestial bodies. This work proposes a new method for estimating the attitude,motion, and inertia properties of an unknown noncooperative space object. Simulations are presented to verify the method for targets with different properties and states. Moreover, the accuracy of the ratios of the principal inertia parameters can reach 90%. In some cases, the most important step is that the computer vision algorithm must assure good and precise information about the feature points on the target. In summary, this paper presents a promising and valuable method for identifying the motion and parameters of noncooperative space targets before the landing of small celestial bodies. The proposed method is highly efficient and suitable for spacecraft applications.
作者
邓润然
葛东明
史纪鑫
邹元杰
朱卫红
李佳宁
DENG RunRan;GE DongMing;SHI JiXin;ZOU YuanJie;ZHU WeiHong;LI JiaNing(Beijing Institute of Spacecraft System Engineering,Beijing 100094,China)
出处
《中国科学：物理学、力学、天文学》
CSCD
北大核心
2022年第1期90-100,共11页
Scientia Sinica Physica,Mechanica & Astronomica
基金
国家重点研发计划(编号:2019YFA0706500)
国家自然科学基金(编号:U20B2055,61525301,61690215,61640304,61573060,61203093)资助项目。
关键词
小天体探测
非合作目标
参数辨识
序列图像
detection of small celestial bodies
non-cooperative target
parameters identify
sequence images
