UKF参数估计在航天器气动辅助变轨问题中的应用

为快速精确地求解气动辅助变轨问题,提出一种基于无损卡尔曼滤波(UKF)参数估计的数值求解方法。首先,针对气动辅助变轨问题,利用极大值原理将其转化为对应的两点边值问题;然后,以协态变量的初值作为估计参数,以末端条件为期望观测值,将该两点边值问题转化为参数估计问题,并应用UKF滤波算法求解。该算法基于估计理论,避免了计算传统数值方法所需要的梯度矩阵,同时克服了猜测协态变量初值的困难,降低了求解气动辅助变轨问题的难度。数值仿真表明,该算法结构简单,求解效率高,具有良好的鲁棒性。     

Track-to-object association algorithm based on TLE filtering

This paper focuses on the track-to-object association problem based on the two-line elements (TLE) set. The TLE’s short-term propagation error characteristics are analyzed to capture its uncertainty. Further, a four-step track-to-object association algorithm is designed for the optical observation data. First, for too-short arc tracklets, a circular orbit determination algorithm is proposed to calculate the inclination and the right ascension of the ascending node. Second, the TLEs are filtered based on these results. Nearly 96% of the TLEs can be filtered, which significantly improves the association efficiency. The last two steps consist of two association processes. A first-order association process is implemented first to get candidate objects, with the angles root mean square error as the metric. Then a precise association process checks the candidate objects and gives the final association result. The proposed approach is tested with simulated and observed data, respectively. With simulated data, the true positive rate is 98.7%. With the observed data, the association results were validated using the precise orbit ephemerides.     

Design of on-board calibration methods for a digital sun sensor based on Levenberg–Marquardt algorithm and Kalman filters

Digital sun sensor is one of the most important sensors used in the Attitude Determination System (ADS) of the satellite. Due to the harsh environmental conditions that exist in the space, various distortions may occur in the sun sensor optical system that lead to the reduced accuracy of this equipment. So, it is necessary to recalibrate the optical parameters of the aforementioned sensors. For this purpose, first a novel attitude independent error model is proposed for the SS-411 sun sensor that includes the central point of the CCD array, installation error, filter thickness and sensor misalignment. So, the mutual interfaces between the sensor parameters are considered in the developed model. In order to extract the sensor parameters, a nonlinear optimization technique called the Levenberg–Marquardt is applied to the developed model as a batch algorithm. In addition, the Extended Kalman Filter (EKF) and the Unscented Kalman Filter (UKF) have been utilized as sequential strategies. It will be shown that by considering a worst case of variation amount for sensor parameters, an accuracy improvement of about 17° is achieved by the developed calibration algorithms. Comparison between the developed algorithms represents that UKF has higher accuracy, shorter time convergence but higher computational load.     

数据链航迹延迟与 ESM点迹间断融合跟踪

数据链与电子支援措施(Electronic Supporting Measures,ESM)融合跟踪是 1种典型的异类多传感器信息融合。针对数据链航迹存在延迟和 ESM点迹间断情况下的数据链航迹与 ESM点迹融合跟踪,提出了复杂情况下的数据链与 ESM融合跟踪方法,并对融合跟踪的精度进行分析研究。首先,对数据进行时间对准,保证数据链和 ESM数据率一致;然后,通过构造基于不敏变换(Unscented Transformation,UT)的非线性量测转换和误差估计方法,将数据链数据对准到 ESM数据;最后,通过引入随机补偿机制对数据链延迟进行补偿,并与 ESM数据进行关联融合。实验结果表明,有延迟补偿时的融合跟踪精度取决于延迟补偿均值与实际延迟的贴近程度。结果可为信息综合处理装备的发展和设计提供借鉴。     

Interlaced optimal-REQUEST and unscented Kalman filtering for attitude determination

 Aimed at low accuracy of attitude determination because of using low-cost components which may result in non-linearity in integrated attitude determination systems, a novel attitude determination algorithm using vector observations and gyro measurements is presented. The various features of the unscented Kalman filter (UKF) and optimal-REQUEST (quaternion estimator) algorithms are introduced for attitude determination. An interlaced filtering method is presented for the attitude determination of nano-spacecraft by setting the quaternion as the attitude representation, using the UKF and optimal-REQUEST to estimate the gyro drifts and the quaternion, respectively. The optimal-REQUEST and UKF are not isolated from each other. When the optimal-REQUEST algorithm estimates the attitude quaternion, the gyro drifts are estimated by the UKF algorithm synchronously by using the estimated attitude quaternion. Furthermore, the speed of attitude determination is improved by setting the state dimension to three. Experimental results show that the presented method has higher performance in attitude determination compared to the UKF algorithm and the traditional interlaced filtering method and can estimate the gyro drifts quickly.     

非合作机动目标天基测角定轨研究

在对空间非合作目标天基测角卡尔曼滤波定轨中,目标机动会导致常规卡尔曼滤波器发散.提出一种无迹卡尔曼滤波(UKF)结合带次优渐消因子的无迹卡尔曼滤波(SFUKF)的滤波定轨方法,目标无机动时使用UKF,在目标机动时使用SFUKF,给出了目标机动的判断准则.仿真结果表明,此滤波方法在目标无机动时有较高的状态估计精度,在目标...     

高斯粒子滤波器及其在非线性估计中的应用

为了解决非线性、非高斯系统估计问题,讨论了一种新的滤波方法——高斯粒子滤波算法。通过基于重要性采样和蒙特卡罗模拟方法得到一高斯分布来近似未知状态变量的后验分布。在符合高斯假设和一定的粒子数的情况下,谈算法可以获得近似最优解。与粒子滤波算法相比,其优点是不需要重采样步骤和不存在粒子退化现象。在滤波精度、运算时间等方面与扩展卡尔曼滤波、Unscented滤波、高斯厄米特滤波及一般的粒子滤波进行了比较分析,仿真结果表明该算法性能优于其他算法。     

非线性估计理论的最新进展

扩展Kalman滤波(EKF)是应用最广的非线性估计方法，然而它存在实现性差、计算量大、估计精度低等缺陷，这些问题起源于。EKF采用了Taylor展开近似。在阐明非线性估计的本质，剖析EKF等传统方法的特点及缺陷的基础上，从非线性估计革新的两条发展思路——非Taylor展开的线性变换及非线性变换出发，分别对插值滤波、Unscented滤波、粒子滤波和神经网络滤波这四种近年来最具特色的新方法进行介绍和评述。通过分析这些方法的工作原理、性能特点、必要性和可行性，将非线性估计最新进展的思想传承、本质内涵、地位与作用予以展现，指出各方法的现存问题、发展潜力和最具可实现性的发展方向。同时强调了各种算法的选取须根据具体应用场合和条件，在主要性能指标之间综合权衡。     

基于UKF和信息融合的航天器自主导航方法

X射线脉冲星导航利用X射线辐射脉冲到达时间 (Time of Arrival, TOA)作为信息输入,星敏感器导航利用星光角距等作为信息输入,是两种不同机理的天文导航方法。提出一种将脉冲星TOA和星敏感器星光角距测量结合的信息融合天文自主导航方法,设计了一种利用激光光量子模拟脉冲星X射线辐射光子的半物理仿真系统用于算法验证,并基于无迹卡尔曼滤波(Unscented Kalman Filter, UKF)使用真轨道参数做了仿真试验。结果表明,基于UKF的信息融合方法比基于EKF（Extended Kalman Filter）的信息融合方法性能更好,与仅使用脉冲星或星敏感器的导航方法相比,能将位置估计精度分别提高52.7%和43.6%,速度估计精度分别提高82.2%和70.5%。     

Radio beacons/IMU integrated navigation for Mars entry

High precision entry navigation capability is essential for future Mars pinpoint landing missions, together with the entry guidance and aerodynamic lift control. This paper addresses the issue of Mars entry navigation using inertial measurement unit (IMU) and orbiting or surface radiometric beacons. The range and Doppler information sensed from orbiting or surface radio beacons and the entry vehicle state information derived from IMU are integrated in Unscented Kalman filter to correct the inertial constant bias and suppress the navigation measurement noise. Computer simulations show that the integrated navigation algorithm proposed in this paper can achieve 50 m position error and 2 m/s velocity error, which satisfies the need of future pinpoint Mars landing missions.