一种用于实时轨道确定的NPF-SRCKF滤波算法

针对航天器实时轨道确定中建模复杂、计算量大、估计精度低的问题,设计了一种考虑地球J 2 摄动影响的基于NPF-SRCKF的实时轨道确定算法,该算法采用非线性预测滤波(NPF)对模型误差进行补偿修正,利用平方根容积卡尔曼滤波(SRCKF)算法对修正模型误差后的系统进行状态估计。针对单测站、双测站跟踪测量设计了不同的实时轨道确定算法。实验结果显示,将非线性预测滤波和平方根容积卡尔曼滤波结合在一起,运用于简化的实时轨道确定模型,能有效降低计算复杂度,改进数值运算的稳定性,提高状态估计的精度。     

A comparison of different regression models for downscaling Landsat and MODIS land surface temperature images over heterogeneous landscape

Remotely sensed high spatial resolution thermal images are required for various applications in natural resource management. At present, availability of high spatial resolution (<200 m) thermal images are limited. The temporal resolution of such images is also low. Whereas, coarser spatial resolution (∼1000 m) thermal images with high revisiting capability (∼1 day) are freely available. To bridge this gap, present study attempts to downscale coarser spatial resolution thermal image to finer spatial resolution using relationships between land surface temperature (LST) and vegetation indices over a heterogeneous landscape of India. Five regression based models namely (i) Disaggregation of Radiometric Temperature (DisTrad), (ii) Temperature Sharpening (TsHARP), (iii) TsHARP with local variant, (iv) Least median square regression downscaling (LMS_DS) and (v) Pace regression downscaling (PR_DS) are applied to downscale LST of Landsat Thematic Mapper (TM) and Terra MODIS (Moderate Resolution Imaging Spectroradiometer) images. All the five models are first evaluated on Landsat image aggregated to 960 m resolution and downscaled to 480 m and 240 m resolution. The downscale accuracy is achieved using LMS_DS and PR_DS models at 240 m resolution at 0.61 °C and 0.75 °C respectively. MODIS data downscaled from 1000 m to 250 m spatial resolution results root mean square error (RMSE) of 1.43 °C and 1.62 °C for LMS_DS and PR_DS models, respectively. The LMS_DS model is less sensitive to outliers in heterogeneous landscape and provides higher accuracy when compared to other models. Downscaling model is found to be suitable for agricultural and vegetated landscapes up to a spatial resolution of 250 m but not applicable to water bodies, dry river bed sand sandy open areas.     

基于自适应差分进化和BP网络的罗盘误差补偿

To improve the acuuracy of heading angle measured by electronic compass, a new error compensation method is proposed based on adaptive differential evolution algorithm and BP neural network. In the method, the 3 layer BP neural network is used to model heading angle error, and adaptive differential evolution algorithm is adopted to train the weights of network, thus obtaining a more exact error model, and compensating the heading angle error measured by electronic compass. Compared with other compensation methods such as 8 position least squares, BP neural network, differential evolution algorithm for optimizing BP neural network, and so on, its error compensation accuracy is significantly improved, the method has strong global optimization ability, great convergence rate, good stability, and so on. The experimental results show that after compensation, the error range of heading angle is decreased from -16°~30.7° to -0.22° ~0.2°, which satisfies the needs of higher accuracy navigation systems.     

基于L-M算法的分数阶导数粘弹性本构模型的参数求解

引入分数阶导数,建立了类Kelvin体粘弹性本构模型。用最小二乘法法和Levenberg-Marquard（L-M）算法,给出了求解类Kelvin体粘弹性本构模型参数的详细步骤。由实际数据选择初值,保证L-M法不会陷入局部最小。某固体推进剂的粘弹性本构模型参数的计算结果表明：该法可较好地表征推进剂松弛曲线,且模型简单、计算参数少。     

多光谱相机的几何标定方法

对多光谱卫星相机进行标定,应用三组图像,每组图像包括四张不同通道的照片。在每组图像里,识别固定目标并且测量它们的坐标。目标点的坐标通过航测照片提取并用手持GPS定位仪进行测量。应用最小二乘法将图像的坐标转换为适当的实际坐标,并计算相机的内外方位元素。     

运载火箭风场高精度拟合方法

针对运载火箭风场传统拟合方法精度低的问题，提出一种基于最少参数神经网络的高精度拟合方法。该方法将运载火箭飞行高度作为网络输入，将风场的速度和朝向作为网络输出，在满足精度要求下使用最少的网络层数和神经元个数完成风场拟合，并给出了隐层节点数的下界公式。和传统的最小二乘多项式拟合及其分段形式相比，最少参数神经网络只使用一套框架即可完成风速和风向的拟合，并提高了拟合精度。大量仿真结果充分说明了所提出方法的有效性、简洁性和鲁棒性。     

基于非合作低轨卫星的测向交叉定位技术

根据非合作低轨卫星的特点，可以被动测量多颗卫星信号的来向，通过测向交叉的方式进行定位。但是通过星历解算出的卫星位置位于地心地固坐标系，用户测量的方位角和俯仰角基于站心坐标系。针对非合作低轨卫星测向交叉定位时目标用户角度信息与卫星位置基于不同坐标系的问题，提出了一种迭代最小二乘定位算法，通过迭代的方式不断收敛定位结果，能够在目标用户角度信息与卫星位置基于不同坐标系的情况下，解决非合作低轨卫星的测向交叉定位问题。仿真结果表明，基于迭代最小二乘定位算法能够实现非合作低轨卫星仅利用角度定位，并分析了测角精度、卫星轨道高度、参与定位卫星数与定位误差之间的关系。针对迭代的计算方法，分析了迭代过程中不同收敛条件下迭代次数与定位误差之间的关系。在保证定位精度的情况下，将迭代收敛范围设置为8~30 km，可以降低2~3次迭代次数。     

MEMS陀螺仪的高精度标定方法

为了提高微机电(MEMS)陀螺仪的测量精度，研究了一种同时标定陀螺非正交误差和加速度敏感漂移误差的标定方法。设计了16位置的转台标定方案，分别以地球自转角速率和重力加速度作为角速率和加速度激励源，利用两组角速率数据迭代求解非正交误差和加速度敏感漂移误差，并以陀螺仪对地球自转角速率的敏感误差作为校正效果的评估依据。试验结果表明，该方法能够有效校正MEMS陀螺仪的非正交误差和加速度敏感漂移误差，提高了陀螺仪的测量精度，且易于工程实现。     

机动发射弹道导弹集群诸元快速规划

针对机动发射条件下弹道导弹集群的飞行诸元快速规划问题，将神经网络预测与最小二乘优化相结合，提出了一种弹道导弹发射诸元快速规划方法。首先分析了弹道导弹助推段飞行策略并选取适当的发射诸元，以发落点信息为输入，设计双隐藏层诸元预测网络，通过弹道仿真获取弹道数据建立数据集完成网络训练，利用该网络可以得到发射诸元迭代初值。在此基础上，为了消除数据集中样本数据不平衡对发射诸元规划精度的影响，以落点射程、横程、高程偏差最小为指标函数，结合最小二乘优化方法进行迭代获得发射诸元精确解。最后在典型发射场景下，进行了弹道导弹集群机动快速发射仿真验证。结果表明，该方法相较于传统方法可显著提高计算速度与精度，且在给定的大范围机动条件下，能够满足弹道导弹集群对远距离、多目标的快速精确打击。     

Installation error calibration for MEMS angular measurement system in hypersonic wind tunnel

The accuracy of model attitude measurement has an important impact on wind tunnel test results. Microelectromechanical System Inertial Measurement Unit (MEMS IMU) provides a feasible way to measure model attitudes with high accuracy. However, the installation error between MEMS IMU coordinate system and the body coordinate system of test models can make the accuracy of the model attitude measurement decrease. In wind tunnel tests, the installation error depends on the relationship between the IMU and the model mechanism before tests. Therefore, in-field calibration in wind tunnel tests is necessary to reduce installation errors. To improve attitude measurement accuracy, the least squares quaternion calibration method based on MEMS IMU and six-position calibration procedure are proposed. High-precision three-axis turntable tests are performed. The pitch accuracy after calibration is higher than that before calibration in the angle of attack sweeping tests. The Root-Mean-Square Errors (RMSE) in the roll and yaw are within 0.01°, which are smaller than those before calibration. In the roll sweeping tests, RMSE of three attitude angles decrease significantly. In hypersonic wind tunnel tests, the pitch errors before and after calibration are within 0.05° and 0.02° in the angle of attack sweeping tests without wind. In five angle of attack sweeping tests with wind, the deviation between the mean of the pitch and the pitch after the elastic angle correction is within 0.03° and the standard deviation of five tests is within 0.01°. The proposed method is confirmed to enhance the accuracy of attitude measurement effectively, which is convenient for engineering applications.