A new algorithm on increasing the sensitivity of microwave radiometer based on nonlinear prediction

Currently, microwave radiometer, which has been one of the most important remote sensors in the land, ocean or atmosphere remote sensing, has played a vital role in space exploration such as the lunar exploration in China. As a passive remote sensor, microwave radiometer receives the noise resembling signals that are generated by microwave radiation while mixed with the systemic noise of the receiver. Therefore, it is the significant subject that how to improve the sensitivity of microwave radiometer that people devotes to study. And on the system noise reduction lies the key. So far, except through choosing low noise element to the receiver, there is no effective alternative to remove the influence of the systemic noise on output uncertainty of microwave radiometer. However, for the purpose of providing or inspiring solution to this problem, this paper inquires into the application of nonlinear predictive method in predication the systemic noise of microwave radiometer. As the substance of the method, neural network shows its function on reducing the systemic noise effectively by estimating and predicating it. Because neural network can improve the estimated precision when estimating the systemic noise, after the noise passes through filter, certain random characters are lost while determinacy are presented to some extent. In fact, the more narrow filter band is, the smaller predictive error will be. The results are of assistance in understanding the intrinsic quality of the systemic noise and offer a new way for improving property of microwave radiometer.     

Nonlinear mixture model of mixed pixels in remote sensing satellite images based on Monte Carlo simulation

A nonlinear mixture model for the interpretation of mixed pixels in remote sensing satellite images is proposed. The proposed model is a Monte Carlo ray-tracing model that takes into account interactions among the ground cover materials (multiple reflections among the materials on the surface). The proposed model also takes into account topographic features (slope) of the ground surface. As an example, Top of the Atmosphere (TOA) radiance of mixed pixels of forested areas which are composed of grasses and trees are simulated with the proposed model and compared to actual remote sensing satellite data of ASTER/VNIR over these forested areas. It was found that the influence due to multiple scattering interactions between trees depends on the tree distance and ranges from 8% to 10%. It is also found that the proposed model is useful to interpret mixed pixels. Namely, it is suggested that actual reflectance of the trees is higher than apparent reflectance that is calculated with the satellite data. Also it is suggested that it is possible to estimate forest parameters such as tree distance, tree shape.     

重力波波包在可压大气中的非线性传播

本文采用二维全隐欧拉(FICE)格式对具有高斯分布的重力波波包在等温、可压大气中的非线性传播过程进行数值模拟和分析.数值分析结果表明:尽管存在非线性效应,在整个传播过程中,波动的等相面向下运动,波包和波相关能量向上传输.波相关扰动速度随高度增加指数增长,并且波与平流会发生非线性相互作用,最后导致平均流场增强.这与线性重力波理论完全一致.重力波波包的传播路径与重力波线性射线理论预言非常接近,但平均水平群速度和平均垂直群速度均明显小于线性射线理论给出的结果,可见波动的非线性过程会改变波相关能量的传输速度.模拟结果首次定量地展示出非线性效应对重力波波包传播的影响,表明建立在线性理论框架中的重力波运动学定义的合理性.      

航空发动机仿真模型参数自适应校正

采用修正因子方法建立自适应仿真模型,运用改进的共轭梯度算法求解非线性规划问题,依据发动机台架试车和空中试飞测量数据,对发动机仿真模型的部件特性参数进行校正,使模型的计算输出与试验测量数据吻合。应用本文方法对某型双转子加力涡喷发动机仿真模型进行校正,获得了满意的仿真精度。     

非线性变结构解耦控制及对再入飞行器的应用

讨论了一类非线性系统的变结构解耦控制在再入飞行器的应用,变结构解耦控制号输入输出线性比相结合得到的控制规律,可对象模型的不确定有鲁棒性,对于再入飞行器再入段存在的多变量非线性和参数不确定,应用了相应的变结构解耦控制的方法,讨论了其滑模面的构造方法和解耦控制条件,在姿态控制中保证了姿态跟踪期望值,在轨迹跟踪中,设计了内外回路在控制律,内回路运用变结构解耦控制保持姿态稳定,外回路通过设计比例微分控制保     

重力波波包在剪切风场中的非线性传播

采用二维全隐欧拉格式,对具有高斯分布的重力波波包在剪切风场中的非线性传播过程进行数据模拟和分析,数值分析结果表明,在没有出现临界层的情况下,尽管存在非线性效应,在整个传播过程中,波动的等相面向下运动,波包和波相关能量仍然能够自由地向上传输。波相关扰动速度随高度增加而增加,并且垂直波长随高度增加而减小。     

一种高动态条件下惯性星光组合定姿方法

针对高动态条件下星图拖尾导致惯性星光组合定姿精度下降甚至无法定姿的问题,提出了一种基于乘性扩展卡尔曼滤波的惯性星光深度组合姿态确定方法.利用星敏感器观测信息修正姿态误差,补偿陀螺漂移,并建立了陀螺输出的角度变化量与星图像移的关系,利用陀螺输出信息估计星图拖尾的模糊参数,采用维纳滤波复原方法对产生拖尾的星图进行复原以提高星图信噪比和观测精度.仿真结果表明该方法可以有效提高星像质心提取精度和星图识别率,对初始姿态误差修正更快,且不存在星图误匹配的情况,保证了惯性星光组合定姿方法在高动态条件下仍能保持较高的精度.     

基于Krylov子空间的多级维纳抗干扰滤波设计

全球卫星导航系统(GNSS, Global Navigation Satellites System)空时抗干扰要求有较好的实时处理能力,常规矩阵求逆的算法由于计算量太大限制了其在GNSS中的应用.在分析多级维纳滤波(MWF,Multi-stage nested Wiener Filter)原理的基础之上,结合Krylov子空间性质,设计出一种应用于GNSS空时抗干扰的自适应多级维纳滤波器,从而实现了在Krylov子空间中降维滤波,避免了矩阵求逆的大运算量.仿真结果表明,该算法在保证抗干扰性能不受影响的前提下,降低了GNSS空时抗干扰算法的计算量,提高了实时处理能力.     

卫星导航调制方式的非线性和兼容性分析

对比研究了最小频移键控（Minimum Shift Keying,MSK）和正交相移键控（Quadrature Phase Shift Keying,QPSK）调制信号的非线性和兼容性。首先建立MSK调制卫星导航信号的时域和频域模型,讨论了MSK调制对码片脉冲形状的影响,指出MSK调制作为卫星导航信号候选调制方式的可行性。然后建立非线性信道模型,仿真了MSK和QPSK调制卫星导航信号的带外功率损耗、相关损耗和码跟踪误差以及与同频段信号的谱分离系数。仿真结果表明,在保证信号跟踪性能的前提下,卫星导航信号采用MSK调制时的非线性和兼容性优于同参数下的QPSK调制。     

航天器相对姿态跟踪的非线性前馈控制

针对航天器相对姿态跟踪过程中严重的非线性及控制器设计的复杂性,建立了基于修正罗德里格斯参数的航天器相对姿态运动学和动力学方程并根据Lyapunov直接法设计了非线性前馈控制律.设计的控制律不仅保证闭环系统稳定,还使得航天器相对姿态跟踪误差快速收敛到零点邻域内.通过在Matlab/Simulink环境下对航天器相对姿态跟踪进行数值仿真,验证了建立模型和设计控制律的有效性.