本文選題：非合作 + 旋轉(zhuǎn)目標(biāo)　； 參考：《光學(xué)精密工程》2017年04期

【摘要】：若要實現(xiàn)空間失效衛(wèi)星、空間碎片等非合作目標(biāo),尤其是具有自旋運動特性的目標(biāo)的在軌服務(wù)或者離軌清除,需要精確測量追蹤航天器與目標(biāo)之間的相對姿態(tài)。當(dāng)目標(biāo)旋轉(zhuǎn)一周后,對重訪區(qū)域的閉環(huán)檢測與位姿優(yōu)化是減小累積誤差,提高測量精度的重要保證。首先,本文介紹了視覺詞袋庫的建立和基于視覺詞袋的非合作目標(biāo)閉環(huán)檢測策略。然后,基于相似性變換,對圖像序列關(guān)鍵幀集和當(dāng)前幀進行了聯(lián)合位姿圖優(yōu)化,實現(xiàn)了對剛體變換矩陣的校正。最后對不同運動角速度下的不同目標(biāo),采用不同相機進行地面模擬測試實驗,驗證了方法的有效性和可靠性。實驗結(jié)果表明:對于以12(°)/s角速度運動的非合作目標(biāo),當(dāng)測量穩(wěn)定后,絕對角度誤差約為1(°),相對角度誤差約為1%,平均角速度誤差約為0.12(°)/s。可以滿足非合作目標(biāo)相對姿態(tài)測量的任務(wù)需求。
[Abstract]:In order to achieve non-cooperative targets such as space failure satellites, space debris, especially the on-orbit service or de-orbit clearance of targets with spin motion, it is necessary to accurately measure the relative attitude between the tracking spacecraft and the target. When the target rotates for one week, the closed-loop detection and pose optimization of the re-visit region is an important guarantee to reduce the cumulative error and improve the measurement accuracy. Firstly, this paper introduces the establishment of visual word bag database and the closed loop detection strategy of non-cooperative target based on visual word bag. Then, based on the similarity transformation, the key frame set of the image sequence and the current frame are optimized by the joint pose graph, and the correction of the rigid body transformation matrix is realized. Finally, the effectiveness and reliability of the method are verified by using different cameras to test different targets at different angular speeds on the ground. The experimental results show that the absolute angle error is about 1 (擄), the relative angle error is about 1, and the average angular velocity error is about 0.12 (擄/ s) for the non-cooperative target moving at the angular velocity of 12 (擄/ s). It can meet the task requirement of relative attitude measurement of non-cooperative target.
【作者單位】： 哈爾濱工業(yè)大學(xué)電氣工程及自動化學(xué)院;上海航天控制技術(shù)研究所;上海市空間智能控制技術(shù)重點實驗室;
【基金】：上海市青年科技啟明星計劃(No.16QB1401000)
【分類號】：V528;V44
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本文編號：1883155