空間碎片光學觀測中若干問題研究

孫榮煜

(中國科學院紫金山天文臺南京210008)

空間碎片光學觀測中若干問題研究

孫榮煜?

(中國科學院紫金山天文臺南京210008)

地基光學觀測是探測空間碎片的重要手段.本文從目標搜索方案的制定、目標質心提取、目標精密定位以及目標關聯(lián)4方面入手,研究提升設備探測能力、提高目標觀測精度的方法.

首先,為了滿足對GEO(Geosynchronous Orbit,地球同步軌道)空間碎片探測的要求,克服長時間曝光CCD像元飽和溢出的問題,使用多幀連續(xù)曝光圖像疊加的方法,增加圖像的寬容度,同時保證系統(tǒng)的探測能力.實驗表明,疊加10幀連續(xù)圖像,有效消除了像元飽和的情況,提升目標信噪比約3.2倍,提升探測能力約2.5 mag,使用底片常數(shù)的均值計算目標位置,精度符合要求.使用星像幾何形態(tài)檢測與線性關聯(lián)的方法,處理了IADC(Inter-Agency Space Debris Coordination Committee)AI23.4的光學聯(lián)測數(shù)據(jù),關聯(lián)139個目標弧段,其中116個弧段對應星表中99個目標,并得到這些目標的實測星等、初軌半長徑、軌道升交點經度、軌道傾角分布.

其次,提出了一種基于先驗信息的探測方法.該方法通過先驗信息,在圖像中碎片星像的鄰域設置波門,計算波門內的局部背景閾值,輔以相關的判據(jù)檢測目標,隨后使用矩方法及線性平移計算碎片質心在整幅圖像中的位置.實驗表明:該方法復雜度低,計算精度優(yōu)于0.5 pixel,計算時間短于0.5 s,可以高效地探測空間碎片.為了解決空間碎片光學觀測圖像中的拖尾與星像重疊問題,使用數(shù)學形態(tài)學算子處理了星像.結果表明,該方法較好地去除了圖像中的拖尾、分離了圖像中的恒星星像與目標星像,提高了目標的檢測效率與定位精度.

再次,基于數(shù)學形態(tài)學算子,結合全局閾值分割圖像、矩方法計算星像質心,實現(xiàn)了一套星像信息提取算法.大量實測數(shù)據(jù)的實驗結果表明,該方法對于1 K×1 K圖像處理時間約為0.2 s,處理低軌與高軌目標的精度分別為適合于空間碎片觀測數(shù)據(jù)的實時處理.為了減小圖像退化對處理精度的影響,使用數(shù)學形態(tài)學算子,沿圖像多個方向卷積,最后疊加所有處理過的圖像得到最終結果.實驗表明,該方法提高了圖像中目標與恒星的信噪比及定位精度.

最后,由于GEO空間目標視運動速度較慢,給目標快速自動關聯(lián)帶來難度.基于Lucas-Kanade算法,在星像鄰域開窗,統(tǒng)計星像的移動速度,給定閾值判別,實現(xiàn)了相鄰幀短曝光圖像間GEO目標的自動關聯(lián).實驗表明:該算法穩(wěn)健可靠,星像位移計算精度為10?3,計算時間快于0.1 s.

Space debris has been recognized as a serious danger for operational spacecraft and manned space fl ights.Discussions are made in the methods of high order position precision and high detecting efficiency for space debris,including the design of surveying strategy,theextraction of object centroid,the precise measurement of object positions,the correlation and catalogue technique.

To meet the needs of detecting space objects in the GEO(Geosynchronous Orbit),and prevent the saturation of CCD pixels with a long exposure time,a method of stacking a series of short exposure time images is presented.The results demonstrate that the saturation of pixels is eliminated e ff ectively,and the SNR(Signal Noise Ratio)is increased by about 3.2 times,the detection ability is improved by about 2.5 magnitude when 10 seriate images are stacked,and the accuracy is reliable to satisfy the requirement by using the mean plate parameters for the astronomical orientation.A method combined with the geometrical morphology identi fi cation and linear correlation is adopted for the data calibration of IADC (Inter-Agency Space Debris Coordination Committee)AI23.4.After calibration,139 tracklets are acquired,in which 116 tracklets are correlated with the catalogue.The distributions of magnitude,semi-major axis,inclination,and longitude of ascending node are obtained as well.

A new method for detecting space debris in images is presented.The algorithm sets the gate around the image of objects,then several criterions are introduced for the object detection,at last the object position in the frame is obtained by the barycenter method and a simple linear transformation.The tests demonstrate that this technique is convenient for application,and the objects in image can be detected with a high centroid precision.In the observations of space objects,the shutter of camera is often removed,and the smear noise is ineluctable.Based on the di ff erences of the geometry between the stars and the smear noise,two operators of the mathematic morphology are presented to resolve this problem. Tests carried out indicate that the smear noise can be removed e ff ectively,and the detection rates of the objects and stars are improved distinctly.Due to the relative movement between space debris and background stars,the blending of objects and stars is ineluctable.In view of the geometric di ff erences between the stars and the objects,a technique for separating the blended objects based on the mathematical morphology is presented.It’s sufficiently fl exible to be applied,and the blended images can be separated e ff ectively with a high degree of centroid precision.

Here we present an automatic technique which optimally detects and measures the sources from the images of optical space debris observations.Tests demonstrate that the technique performs well from the point of view of the fast and accurate detection.An automatic image reconstruction method is also presented,the variable structural elements along multiple directions are adopted for the image convolution,and then all the corresponding convolved images are stacked.With this method,the position accuracies of background stars are improved distinctly.

A technique based on the Lucas-Kanade algorithm is presented to detect the GEO objects between two short exposure time frames automatically.The experiments demonstrate that this method works e ff ectively and robustly,the displacement precision of object images is about 10?3,and the computing time is less than 0.1 s.

Research on Optical Observation for Space Debris

SUN Rong-yu
(Purple Mountain Observatory,Chinese Academy of Sciences,Nanjing 210008)

10.15940/j.cnki.0001-5245.2015.01.010

?2013-07-07獲得博士學位,導師:紫金山天文臺趙長印研究員;rysun@pmo.ac.cn