非相干有源诱偏抗反辐射武器效果分析

从反辐射武器导引头瞄准误差的角度,对非相干有源诱偏抗反辐射武器的干扰效果进行分析。     

对空中运动目标的时差定位精度影响因素分析

基于三站对辐射源联合时差定位的原理,分析了影响空中运动目标定位精度的因素,研究了相对位置关系、信号噪声及多普勒频移对定位误差的影响,解决了空中运动目标定位误差定量评估的部分理论问题,并利用计算机仿真验证了研究成果。     

基于MEP-UKF的组合导航滤波算法

针对目前应用于SINS／GPS组合导航系统中的扩展卡尔曼滤波(Extended Kalman
Filter, EKF)存在精度低、实时性差的缺点,提出一种基于模型误差预测(Model Error
Prediction, MEP)的Unscented 卡尔曼滤波(Unscented Kalman Filter,
UKF)。MEP-UKF滤波算法将惯性器件测量误差作为模型误差使用MEP进行实时预测的同时,采 用UKF估计载体的姿态、速度及位置等误差信息,并反馈给SINS系统来校正导航参数。MEP-U KF不仅克服了UKF必须假设惯性器件误差为高斯白噪声的局限性,而且降低了SINS／GPS组合 导航系统状态变量的维数,大大缩短了导航解算的时间。仿真结果表明,MEP-UKF的收敛速 度和滤波精度均明显优于EKF,更好地满足了工程应用中对导航精度和实时性的要求。     

星敏感器光轴测量的锥面误差模型及其应用

星敏感器是卫星高精度姿态测量系统中的重要器件,根据其测量可以建立不同形式的星敏感器测量模型,准确分析测量模型中测量误差的特性是保证卫星姿态确定精度的重要条件。本文针对广泛采用的星敏感器光轴矢量测量方程,从几何角度出发,结合实际情况,提出了一种新颖的星敏感器光轴测量的锥面误差模型。在两个锥面参数分别服从一定的概率分布的条件下,对测量误差特性进行了深入分析,确定出新的测量误差协方差矩阵。上述研究能够在不增加算法计算量的前提下,从新的角度,更为直观地建立了星敏感器光轴矢量测量模型。最后在仿真实验中,将新的锥面误差测量模型应用于基于扩展卡尔曼滤波（EKF）的姿态确定方法中,结果表明了利用该测量模型进行姿态确定的有效性。     

星载ScanSAR天线指向稳定度对辐射校正的影响

基于均匀加权天线模型,推导星载ScanSAR天线指向不稳定引起的多普勒中心频率估计误差,建立多普勒中心频率估计误差与图像辐射校正精度之间的数学模型,进而提出星载ScanSAR辐射校正对天线指向稳定度的要求。最后,通过计算机仿真,验证了理论分析的正确性。     

Integral inversion of GRAIL inter-satellite gravitational accelerations for regional recovery of the lunar gravitational field

We present an integral-based approach for high-resolution regional recovery of the gravitational field in this article. We derive rigorous remove-compute-restore integral estimators relating the line-of-sight gravitational acceleration to an arbitrary order radial derivative of the gravitational potential. The integral estimators are composed of three terms, i.e., the truncated integration, the low-frequency line-of-sight gravitational acceleration, and the high-frequency truncation error (effect of the distant zones). We test the accuracy of the integral transformations and of the integral estimators in a closed-loop simulation over the Montes Jura region on the nearside of the Moon. In this way, we determine optimal sizes of integration radii and grid discretisation. In addition, we investigate the performance of the regional integral inversion with synthetic and realistic GRAIL observations. We demonstrate that the regional inversion results of the disturbing gravitational potential and its first order radial derivative in the Montes Jura mountain range are less contaminated by high-frequency noise than the global spherical harmonic models.     

大气总温传感器误差修正方法研究

大气总温的准确测量对民用飞机的飞行安全至关重要。以古德里奇公司的102CP2AG总温传感器为例．详细论述了总温测量过程中对恢复系数、时间常数、自加热、防冰加热等误差的修正原理与使用方法。     

粒子拖尾长度对高频DPIV测量误差的影响

基于连续激光源的高采样频率DPIV系统在进行曝光时可能会产生粒子拖尾现象。明渠湍流试验和数值模拟试验结果显示，粒子拖尾长度的增加会导致平均流速减小和湍流强度增大。分析表明，导致平均流速误差的原因之一是诊断窗口边缘局部粒子图像的缺失，且图像缺失程度会随着粒子拖尾长度增加而增大，从而使平均速度随粒子拖尾长度增加而减小；粒子拖尾的另一个直接后果是增大了粒子图像的有效粒径，从而导致湍流强度增大。通过增大第二个诊断窗口的尺寸，进行相关函数标准化和相关系数补偿等方法，可以消除粒子拖尾长度引起的误差。     

基于最小二乘支持向量机的工具误差分离与折合

制导工具误差分离与折合是导弹精度评定中的重要问题,提出了利用支持向量机方法获得工具误差系数估计和进行弹道误差折合的新方法,由于支持向量机综合考虑了结构风险和经验风险,使得模型的泛化能力增强。仿真计算表明,与最小二乘和主成分方法相比,最小二乘支持向量机获得的误差系数估计与真值更加接近,折合得到的全程弹道遥外差更加准确。     

Central difference predictive filter for attitude determination with low precision sensors and model errors

Attitude determination is one of the key technologies for Attitude Determination and Control System (ADCS) of a satellite. However, serious model errors may exist which will affect the estimation accuracy of ACDS, especially for a small satellite with low precision sensors. In this paper, a central difference predictive filter (CDPF) is proposed for attitude determination of small satellites with model errors and low precision sensors. The new filter is proposed by introducing the Stirling’s polynomial interpolation formula to extend the traditional predictive filter (PF). It is shown that the proposed filter has higher accuracy for the estimation of system states than the traditional PF. It is known that the unscented Kalman filter (UKF) has also been used in the ADCS of small satellites with low precision sensors. In order to evaluate the performance of the proposed filter, the UKF is also employed to compare it with the CDPF. Numerical simulations show that the proposed CDPF is more effective and robust in dealing with model errors and low precision sensors compared with the UKF or traditional PF.