發(fā)布時(shí)間：2018-06-23 09:02

  本文選題：激光成像雷達(dá) + 相對(duì)位姿估計(jì)　； 參考：《系統(tǒng)仿真學(xué)報(bào)》2017年05期

【摘要】：為解決對(duì)空間未知目標(biāo)的相對(duì)位置、姿態(tài)估計(jì)問(wèn)題,以激光成像雷達(dá)作為測(cè)量敏感器,提出了基于擴(kuò)展Kalman濾波(EKF,Extended Kalman Filter)的相對(duì)位姿估計(jì)算法。采用迭代最近點(diǎn)算法(Iterative Closest Point,ICP)對(duì)激光雷達(dá)的點(diǎn)云測(cè)量數(shù)據(jù)進(jìn)行解算,得到相對(duì)位姿粗值并將其作為位姿估計(jì)算法的測(cè)量輸入。以相對(duì)姿態(tài)、角速度、慣量比、相對(duì)位置、相對(duì)速度和目標(biāo)測(cè)量參考系的位姿作為濾波狀態(tài),算法在對(duì)相對(duì)位置和姿態(tài)估計(jì)的同時(shí),可辨識(shí)出目標(biāo)的未知參數(shù)。為提高數(shù)值仿真的可信度,用Geomagic軟件模擬點(diǎn)云測(cè)量。采用Matlab進(jìn)行數(shù)值仿真,驗(yàn)證了新算法的有效性。
[Abstract]:In order to solve the problem of relative position and attitude estimation of unknown targets in space, a relative attitude estimation algorithm based on extended Kalman filter (EKF) is proposed using laser imaging radar as measurement sensor. The iterative closest Point Point (ICP) algorithm is used to calculate the point cloud measurement data of lidar, and the coarse relative position is obtained and used as the measurement input of the position and attitude estimation algorithm. Using relative attitude, angular velocity, inertia ratio, relative position, relative velocity and position of reference frame of target measurement as filtering states, the unknown parameters of the target can be identified by the algorithm while estimating the relative position and attitude. In order to improve the reliability of numerical simulation, point cloud measurement is simulated with Geomagic software. The validity of the new algorithm is verified by numerical simulation with Matlab.
【作者單位】： 中國(guó)空間技術(shù)研究院錢(qián)學(xué)森空間技術(shù)實(shí)驗(yàn)室;廣東省政府;
【基金】：國(guó)家自然科學(xué)基金(61403392)
【分類(lèi)號(hào)】：TN958.98

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本文編號(hào)：2056601