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。     

频标比对中一种新的测量方法

在用比相法测量频率时 ,一般都是在 0°～ 360°范围内进行 ,由于在靠近 0°和 360°时存在有“死区”和非线性 ,使得系统的测量准确度和稳定性受到影响。为了解决这个问题 ,本文介绍一种新的测量方法 ,能够在测量中避开非线性区域 ,达到提高测量准确度和稳定性的目的 ,自校稳定性可达 2 6× 10 - 13 /s。     

非线性系统干扰解耦方法在拦截问题中的应用

利用非线性系统干扰可解耦的条件及干扰解耦控制方法，可以对一个导弹拦截运动学系统进行解耦，从而得到一种不受目标切向机动干扰影响的导引规律。     

基于Wiener过程的发动机多阶段剩余寿命预测

针对现阶段发动机的寿命预测研究没有考虑到非线性与多阶段的问题,提出了基于多阶段非线性Wiener过程的航空发动机实时剩余寿命预测的方法。该方法融合了同类型发动机的历史性能退化监测数据与个体发动机的实时监测数据。首先,考虑了发动机性能退化非线性的特点,并采用多阶段Wiener过程建立发动机的性能退化模型。然后,根据发动机的历史性能监测数据,利用极大似然估计和一维搜索方法进行参数先验分布的估计。再次,在先验分布和个体发动机的退化数据的基础上,用贝叶斯方法对参数分布更新。最后,得到个体发动机剩余寿命的实时预测值。通过实例验证本文方法预测的准确性。      

高超声速飞行器建模与控制的一体化设计

针对高超声速飞行器纵向模型具有非线性、强耦合及不确定性等特点,提出 高超声速飞行器建模与控制一体化设计方法。该方法首先以具有典型结构的高超声速飞行器 几何外形为研究对象,结合高超声速空气动力学的有关理论,建立飞行器的非线性纵向模型 方程;然后在不同飞行条件下获取多个平衡点,分析飞行的气动特性,进而在每一个平衡点 上设计具有非线性解耦控制能力的控制器,并将得到的多平衡点控制参数结合起来,进行插 值计算,实现多平衡点的连续飞行;最后的仿真结果表明,本文提出的方法是切实可行的。