Accuracy analysis of GNSS-IR snow depth inversion algorithms

In recent years, with the continuous development of Global Navigation Satellite System (GNSS), it has been applied not only to navigation and positioning, but also to Earth surface environment monitoring. At present, when performing GNSS-IR (GNSS Interferometric Reflectometry) snow depth inversion, Lomb-Scargle Periodogram (LSP) spectrum analysis is mainly used to calculate the vertical height from the antenna phase center to the reflection surface. However, it has the problem of low identification of power spectrum analysis, which may lead to frequency leakage. Therefore, Fast Fourier Transform (FFT) spectrum analysis and Nonlinear Least Square Fitting (NLSF) are introduced to calculate the vertical height in this paper. The GNSS-IR snow depth inversion experiment is carried out by using the observation data of P351 station in PBO (Plate Boundary Observatory) network of the United States from 2013 to 2016. Three algorithms are used to invert the snow depth and compared with the actual snow depth provided by the station 490 in the SNOTEL network. The observations data of L1 and L2 bands are respectively used to find the optimal combination between different algorithms further to improve the accuracy of GNSS-IR snow depth inversion. For L1 band, different snow depths correspond to different optimal algorithms. When the snow depth is less than 0.8 m, the inversion accuracy of NLSF algorithm is the highest. When the snow depth is greater than 0.8 m, the inversion accuracy of FFT algorithm is higher. Therefore, according to the different snow depth, a combined algorithm of NLSF + FFT is proposed for GNSS-IR snow depth inversion. Compared with the traditional LSP algorithm, the inversion accuracy of the combined algorithm is improved by 10%. For L2 band data, the results show that the accuracy of snow depth inversion of various algorithms do not change with the variations of snow depth. Among the three single algorithms, the inversion accuracy of FFT algorithm is better than that of LSP and NLSF algorithms.     

基于功率裕度的某型发动机全寿命性能研究

随着使用时间不断增加,研究飞行队所有选装ARRIEL2S系列发动机全寿命性能变化趋势的必要性突显.针对SRRIEL2S系列发动机全寿命性能参数变化特点,提出使用基于可几误差舍弃理论处理发动机功率校验数据,分区间描绘该系发动机全寿命性能指标变化趋势,给出该系发动机全寿命性能特点,为机务工程人员监控该系发动机提供有利依据；提出延长功率校验间隔的假设,并在理论上做了充分论证,为节约该系发动机运行成本提供一个明确及可行的方向.     

频域内参数估计

研究了在频域中利用方程误差法结合递推的傅里叶变换技术进行线性系统实时参数估计的方法。分别从频域中的方程误差法、递推的傅里叶变换和计算频率范围选择三个地参数估计进行了较详细地分析。通过结某型战斗机进行模拟计算，结果表明：该方法能自动过滤噪声；占用计算机内存固定；计算量小；不需要输入任何初值并在计算中调整任何参数；所估计的参数值能够在系统模态周期１．０￣１．５倍的时间内逼近真值，即使在信号水平较低的情     

用于人机耦合振荡探测的操纵振荡特征确定

为了实现人机耦合振荡的在线探测，提出了适于实时计算的滑动窗口Fourier变换递推算法和与人机耦合振荡相关的飞机操纵振荡特征，并通过人机耦合振荡试飞数据的计算，分析了操纵振荡特征的合理、有效性。最后指出拟进一步开展的研究工作及建议。     

飞控-飞机低阶等效系统的在线辨识

以飞控—飞机低阶等效系统为背景，采用Taylor展开法研究了带纯延迟环节的二阶系统的在线辨识。采取了对低信息点进行抛弃，变步数起动等算法对传统的最小二乘法加以改进，大大减少了辨识过程中产生的误差，更适合于实时辨识。实际应用结果表明：该方法可以有效地对具有时变特性的带纯延迟的非线性系统加以辨识，辨识结果满足工程要求。     

一种基于FPGA的超高速32k点FFT处理器

采用FPGA(Field Programmable Gate Arrays)实现了一个超高速的32k点的流水线FFT(Fast Fourier Transform)处理器.FPGA的工作频率为125MHz,可以处理连续的1Gs/s(1 Giga-samples per second)的复数数据.该FFT处理器主要基于二维分解算法,采用MDF(Multi-path Delay Feedback)流水线结构,并结合MDC(Multi-path Delay Commutator)及SDF(Single-path Delay Feedback)结构的特点.处理器的内存资源消耗相对MDC结构有所减少,而运算速度相对SDF结构有所提高.建立了处理器的算法和设计模型,并根据模型对处理器的3个组成模块进行了优化以减小资源消耗.利用VHDL语言在Xilinx ISE工具上进行了设计,FPGA的布局布线结果验证了设计的可行性.     

Optimal solar sail trajectory approximation with finite Fourier series

The heliocentric transfer of a solar sail-based spacecraft is usually studied from an optimal perspective, by looking for the control law that minimizes the total flight time. The optimal control problem can be solved either with an indirect approach, whose solution is difficult to obtain due to its sensitivity to an initial guess of the costates, or with a direct method, which requires a good estimate of a feasible (guess) trajectory. This work presents a procedure to generate an approximate optimal trajectory through a finite Fourier series. The minimum time problem is solved using a nonlinear programming solver, in which the optimization parameters are the coefficients of the Fourier series and the positions of the spacecraft along the initial and target orbits. Suitable constraints are enforced on the direction and magnitude of the sail propulsive acceleration vector in order to obtain feasible solutions. A comparison with the numerical results from an indirect approach shows that the proposed method provides a good approximation of the optimal trajectory with a small computational effort.     

动态系统元器件失效率的矩独立重要性测度分析

针对不确定性元器件失效率对动态系统失效概率影响程度的度量问题,研究了动态系统元器件失效率的重要性分析方法。分析了不确定性情况下动态系统失效概率的特点;依据Borgonovo的矩独立灵敏度分析思想,提出了两种新的矩独立不确定性重要性测度,给出了基于蒙特卡罗数值仿真的一般求解方法,分别用来分析系统工作时间给定和在区间变化两种情况下元器件失效率不确定对系统失效概率分布函数的贡献程度;建立了重要性测度的高效算法,通过稀疏网格积分技术将多元函数的积分问题转化成一元函数积分的张量积组合,通过Edgeworth级数方法将响应量分布函数的求解问题转化为基于其前四阶矩的失效概率估计,从而有效降低了功能函数的调用次数,提高了重要性测度的求解效率。最后,通过两个算例验证了所提方法的合理性和算法的高效性。     

基于直升机平台SAR的方位重影抑制方法

直升机合成孔径雷达(SAR)已成为遥感领域的重要探测工具。针对平台微小高频振动导致方位重影,造成图像质量降低的问题,提出了一种振动相位补偿算法。首先利用回波录取的几何构型,推导基于直升机振动平台的SAR回波表达式,并引入雅可比-安格尔恒等式,对回波完成一阶贝塞尔级数展开,获得高频振动误差与方位向重影的关系式。然后,从直升机SAR实测数据入手,对方位相位进行差分、提取和快速傅里叶变换,得到振动频点信息,并对频点信息进行反演,得到高频误差相位。最后,利用高频误差相位对原始回波进行补偿,抑制成对回波模糊现象,从而消除方位重影。基于实测数据的成像处理结果验证了所提方法的有效性。     

HCKF性能评估及其在传递对准中的应用

针对高阶容积卡尔曼滤波(HCKF)算法在传递对准中的应用问题,提出综合运用多变量函数泰勒级数展开和计算复杂度分析的性能评估方法。基于高阶球面-径向容积准则建立HCKF算法模型,并对其估计精度和计算量进行量化和对比分析：HCKF具有5阶泰勒级数展开精度且计算复杂度为O(n 4),综合性能优于高斯厄米特积分滤波(GHQF)和无迹卡尔曼滤波(UKF)。将三种非线性滤波算法应用到舰机大失准角传递对准系统中,摇摆台试验结果表明：HCKF的估计精度比UKF高17%,计算量比GHQF小2个数量级,与HCKF性能评估结果一致。