多星敏感器测量最优姿态估计算法

多数利用星敏感器加陀螺组合的姿态确定方法中,由于星敏感器精度较高,使得系统定姿的精度比较高.然而,姿态确定的算法因观测模型和误差处理不当,导致滤波器观测修正能力下降,从而不能有效地估计陀螺的漂移误差.提出了基于星敏感器观测姿态角的误差建模,研究了多星敏感器组合的最优安装构型和观测融合方法.利用加权最小二乘法对观测数据的预处理,使观测方程定常化.再利用陀螺加星敏感器组合的扩展Kalman滤波(EKF,Extended Kalman Filtering)对航天器姿态和陀螺漂移进行估计.仿真结果表明,提出的多星敏感器最优组合的滤波方法能够有效精确地估计卫星三轴姿态和陀螺漂移,且该方法计算量小,有利于卫星定姿系统的在轨自主运行.     

超磁致伸缩作动器的结构分析

从力学和磁学两方面分析了超磁致伸缩作动器内部结构形式对作动器特性的影响,重点研究了永磁铁式偏置磁场的不同结构形式以及作动器外壳材料对作动器的输出性能及作动器轴向刚度的影响.研究结果表明,环套式永磁铁的结构形式不可避免地在作动器外围产生较大磁场;分段式永磁铁的结构形式,采用钢制外壳时可避免漏磁;但是在芯棒区域的磁场与理想均匀磁场的差异将给作动器的输出位移带来较大损失,对作动器的刚度也会产生不可忽略的影响,二者在设计中必须考虑.在结构分析的同时,基于超磁致伸缩材料的特性提出了磁场与刚度相关联的设计理念,可为超磁致伸缩作动器的结构设计提供参考.     

基于高增益观测器的航迹角自适应反步控制

针对飞行控制系统中状态向量不完全可测量的问题,设计了一种高增益神经网络自适应观测器.在常规高增益观测器的基础上引入径向基(RBF, Radial Basis Function)网络自适应项,对建模误差和外界干扰进行在线估计.将高增益观测器与基于动态面的反步控制相结合,提出了一种神经网络自适应反步控制方法.引入一阶滤波器,避免了传统反步控制中的"计算膨胀"问题.基于Lyapunov稳定性理论,给出自适应输出反馈控制器和RBF网络权值向量的自适应律,并证明了闭环系统是半全局一致有界.从航迹角控制系统仿真结果可以看出,航迹角能够较好地跟踪指令信号,不受建模误差和外界干扰的影响,所设计的观测器具有良好的收敛性,控制系统具有较高的鲁棒性.     

基于双量子比特态测量的量子自适应中值滤波

为了进一步增强去噪时对图像细节的保护能力,并同时提高算法实时性,提出了基于双量子比特态测量的量子自适应中值滤波算法,该算法首先将待处理图像像素转化为量子叠加态,然后依据量子测量原理对此叠加态进行量子测量,最后将测量后的坍缩态转化为输出图像.该算法使用双量子比特态来描述单像素,拓展了单量子比特态与单像素的对应关系.双量子比特态的4个叠加基态增加了被描述像素的信息量,可以更精确地对像素进行操作.该算法根据噪声特点设计双量子比特态的概率密度公式,并根据测量坍缩态自适应地调整滤波窗口尺寸.实验证明,该算法与标准中值滤波和经典自适应中值滤波相比,具有更好的综合滤波能力,既可以有效地滤除噪声点,很好地保护图像细节,又具有很好的实时性.     

Comparison of ionosphere characteristic parameters obtained by ionosonde with IRI-2007 model over Southeast Asia

In this work, the foF2 and hmF2 parameters at the conjugate points near the magnetic equator of Southeast Asia are studied and compared with the International Reference Ionosphere (IRI) model. Three ionosondes are installed nearly along the magnetic meridian of 100°E; one at the magnetic equator, namely Chumphon (10.72°N, 99.37°E, dip angle 3.0°N), and the other two at the magnetic conjugate points, namely Chiang Mai (18.76°N, 98.93°E, dip angle 12.7°N) and Kototabang (0.2°S, 100.30°E, dip angle 10.1°S). The monthly hourly medians of the foF2 and hmF2 parameters are calculated and compared with the predictions obtained from the IRI-2007 model from January 2004 to February 2007. Our results show that: the variations of foF2 and hmF2 predicted by the IRI-2007 model generally show the similar feature to the observed data. Both parameters generally show better agreement with the IRI predictions during daytime than during nighttime. For foF2, most of the results show that the IRI model overestimates the observed foF2 at the magnetic equator (Chumphon), underestimates at the northern crest (Chiang Mai) and is close to the measured ones at the southern crest of the EIA (Kototabang). For hmF2, the predicted hmF2 values are close to the hmF2(M3000F2_OBS) during daytime. During nighttime, the IRI model gives the underestimation at the magnetic equator and the overestimation at both EIA crests. The results are important for the future improvements of the IRI model for foF2 and hmF2 over Southeast Asia region.     

Digital signal processing and numerical analysis for radar in geophysical applications

Numerical solutions for signal processing are described in this work as a contribution to study of echo detection methods for ionospheric sounder design. The ionospheric sounder is a high frequency radar for geophysical applications. The main detection approach has been done by implementing the spread-spectrum techniques using coding methods to improve the radar’s range resolution by transmitting low power. Digital signal processing has been performed and the numerical methods were checked. An algorithm was proposed and its computational complexity was calculated.     

Systematic examination of the geomagnetic storm sudden commencement using multi resolution analysis

Geomagnetic storm sudden commencements (SSC) contain a wealth of information which is useful in many applications. It is important to point out that the SSCs used in this study are sampled at the rate of one sample per second in order get use of such high resolution data. In this paper, two studies are made on the geomagnetic SSC and an SSC onset automatic detection algorithm is introduced. The first study is about finding the relationship between the SSC rise time and its amplitude. Where it is found that there is a positive correlation between the amplitude and the amplitude gradient which is the amplitude divided by rise time. The second study is checking the spectrum of the SSC, starting from its onset until the end of the SSC rise time. This check had proved that the SSC contains both low and high frequency regions. This led us to introduce a new term, namely the SSC variation rate (VR). This VR is defined as the maximum rate of change of the field in the higher-frequency region of the SSC. These two studies were the guide to build an SSC automatic detector of one sample per second data using multi resolution analysis (MRA) of the discrete wavelet transform (DWT). The data set contains 134 SSCs with different VRs that were collected from the Circum-pan Pacific Magnetometer Network (CPMN). It is found that the standard deviation of the detection error is 41 s and that the average error is 9 s. From the calculated error distribution function, it is found that the detection error is within the range of −1.5 to 3 min. The detection process, as will be shown in the article, takes 70 s for one station and 3 min if the decision is related to the detection(s) of other stations. These results demonstrate the superiority of the proposed algorithm over other algorithms in which the detection error ranges between −8 and 5 min and the detection process takes 2–10 min. In addition to being faster and more accurate than the other algorithms, the proposed algorithm is the first algorithm that automatically detects the SSC onset times from high-resolution data unlike previous studies that focused on determining the SSC times automatically using one-minute resolution data.     

Modelling and observing Jovian electron propagation times in the inner heliosphere

The propagation of Jovian electrons in interplanetary space was modelled by solving the relevant transport equation numerically through the use of stochastic differential equations. This approach allows us to calculate, for the first time, the propagation time of Jovian electrons from the Jovian magnetosphere to Earth. Using observed quiet-time increases of electron intensities at Earth, we also derive values for this quantity. Comparing the modelled and observed propagation times we can gauge the magnitude of the transport parameters sufficiently to place a limit on the 6 MeV Jovian electron flux reaching Earth. We also investigate how the modelled propagation time, and corresponding Jovian electron flux, varies with the well-known ∼13 month periodicity in the magnetic connectivity of Earth and Jupiter. The results show that the Jovian electron intensity varies by a factor of ∼10 during this cycle of magnetic connectivity.     

Testing the three-dimensional IRI-SIRMUP-P mapping of the ionosphere for disturbed periods

This paper describes the three-dimensional (3-D) electron density mapping of the ionosphere given as output by the assimilative IRI-SIRMUP-P (ISP) model for three different geomagnetic storms. Results of the 3-D model are shown by comparing the electron density profiles given by the model with the ones measured at two testing ionospheric stations: Roquetes (40.8°N, 0.5°E), Spain, and San Vito (40.6°N, 17.8°E), Italy. The reference ionospheric stations from which the autoscaled foF2 and M(3000)F2 data as well as the real-time vertical electron density profiles are assimilated by the ISP model are those of El Arenosillo (37.1°N, 353.3°E), Spain, Rome (41.8°N, 12.5°E), and Gibilmanna (37.9°N, 14.0°E), Italy. Overall, the representation of the ionosphere made by the ISP model is better than the climatological representation made by only the IRI-URSI and the IRI-CCIR models. However, there are few cases for which the assimilation of the autoscaled data from the reference stations causes either a strong underestimation or a strong overestimation of the real conditions of the ionosphere, which is in these cases better represented by only the IRI-URSI model. This ISP misrepresentation is mainly due to the fact that the reference ionospheric stations covering the region mapped by the model turn out to be few, especially for disturbed periods when the ionosphere is very variable both in time and in space and hence a larger number of stations would be required. The inclusion of new additional reference ionospheric stations could surely smooth out this concern.