高温燃气加热器热特性研究

介绍了高温燃气加热器的工作原理,推导了结构在高温燃气作用下的二维共轭传热方程,应用Fluent软件对头锥结构在高温燃气作用下的流动传热特性进行了数值模拟,得到了不同来流温度和速度条件下结构温度分布情况以及外流场流动及传热特性,为高温燃气对流加热试验技术提供依据。     

Low-cost precise measurement of oscillator frequency instability based on GNSS carrier observation

Global navigation satellite systems (GNSS) receivers can be used in time and frequency metrology by exploiting stable GNSS time scales. This paper proposes a low-cost method for precise measurement of oscillator frequency instability using a single-frequency software GNSS receiver. The only required hardware is a common radio frequency (RF) data collection device driven by the oscillator under test (OUT). The receiver solves the oscillator frequency error in high time resolution using the carrier Doppler observation and the broadcast ephemeris from one of the available satellites employing the onboard reference atomic frequency standard that is more stable than the OUT. Considering the non-stable and non-Gaussian properties of the frequency error measurement, an unbiased finite impulse response (FIR) filter is employed to obtain robust estimation and filter out measurement noise. The effects of different filter orders and convolution lengths are further discussed. The frequency error of an oven controlled oscillator (OCXO) is measured using live Beidou-2/Compass signals. The results are compared with the synchronous measurement using a specialized phase comparator with the standard coordinated universal time (UTC) signal from the master clock H226 in the national time service center (NTSC) of China as its reference. The Allan deviation (ADEV) estimates using the two methods have a 99.9% correlation coefficient and a 0.6% mean relative difference over 1–1000 s intervals. The experiment demonstrates the effectiveness and high precision of the software receiver method.     

一种多级助推段弹道导弹跟踪算法

针对多级助推段弹道导弹存在多个加速度突变点、机动性强导致跟踪难度大的问题,提出一种基于量测转换的强跟踪输入估计（STMIE）弹道导弹跟踪算法。在对多级助推段弹道导弹动力学特性分析的基础上,推导出雷达站东北上（ENU）坐标系下弹道导弹的运动方程,并通过将修正的无偏量测转换（MUCM）与STMIE算法融合,使得在导弹跟踪中应用STMIE算法成为可能。以典型的多级助推段弹道导弹为跟踪目标进行仿真校验,结果表明,本文算法对多级助推段弹道导弹目标跟踪性能优越,且算法复杂度较低,效费比高。     

一种面向临近空间高超声速再入滑翔目标跟踪算法

针对临近空间高超声速再入滑翔目标的跟踪问题,提出了一种基于回顾成本输入估计的无偏转换量测卡尔曼滤波(Retrospective cost input estimation-unbiased converted measurements Kalman filter, RCIE-UCMKF)。首先,根据再入滑翔目标的飞行特性,将加速度看成是未知的确定输入构建运动学跟踪模型;然后,对目标的非线性量测信息进行无偏转换,并将得到的噪声协方差矩阵进行解耦,降低算法的复杂度;最后,利用回顾成本的输入估计对未知加速度进行重构,采用递推最小二乘法更新输入估计器的参数矩阵,同时将估计的加速度引入到卡尔曼滤波框架下,实现对高超声速再入滑翔目标状态的准确估计。仿真结果表明了该算法的有效性和可行性。     

香港国际机场航空交通量的无偏灰色马尔科夫预测

针对香港国际机场航空交通量的灰色性和随机波动性,本文采用无偏灰色GM(1,1)代替传统灰色GM(1,1)模型,分析了2001—2012年香港机场航空交通量的数据,预测出2013年香港机场的航空交通量,然后用加权马尔科夫模型对预测结果进行优化。利用Matlab计算得后验差检验C值小于0.35,P值为1,拟合精度等级为好,表明动态无偏灰色马尔科夫能消除传统灰色GM(1,1)模型的固有误差,提高预测精度。加权马尔科夫模型对灰色预测结果优化得2013年香港航空交通量在352 241~370 780架次之间。     

基于CAE仿真的两轴柔性滚弯过程的应变分析

介绍了两轴柔性滚弯的工作原理和技术优势.为便于对滚弯过程中弹性层的受力进行分析,提出了折算弹性模量的概念,来定义柔性滚弯过程中聚氨酯橡胶随成形改变的弹性模量,并推导了聚氨酯橡胶折算弹性模量的计算公式.利用非线性有限元分析软件MARC建立了两轴柔性滚弯过程的有限元模型,模拟了板料滚弯成形加工过程,得出了在不同刚性滚直径和不同压入深度下板料与弹性层的应变分布.基于CAE的仿真分析,可以对柔性滚弯过程工艺参数的选取提供依据.     

一种基于三维到达角的无偏伪线性卡尔曼滤波

为了解决大场景下基于三维到达角的目标跟踪问题，提出了一种具有无偏性的伪线性卡尔曼滤波。首先，基于三维到达角信息对目标运动模型与量测模型进行建模；之后，对量测模型进行了伪线性化处理，得到了线性形式的目标量测模型。为了解决伪线性卡尔曼滤波存在的有偏性问题，提出了一种结合EKF（extend Kalman filter）的三维伪线性无偏卡尔曼滤波。仿真实验表明，该模型能够对非机动目标与机动目标有效跟踪，对于百公里级别的目标，当角测量误差从0.1°变化到0.5°，算法在仿真时间结束时均能将绝对位置误差降低至10 km以内，且算法的运行速度与EKF为同一个量级，同时兼顾了抗干扰能力、定位跟踪精度、运行效率的要求，能够为大场景下的目标跟踪提供有效方法。     

A Tracking Filter in Spherical Coordinates Enhanced by De-noising of Converted Doppler Measurements

Tracking problem in spherical coordinates with range rate (Doppler) measurements, which would have errors correlated to the range measurement errors, is investigated in this paper. The converted Doppler measurements, constructed by the product of the Doppler measurements and range measurements, are used to replace the original Doppler measurements. A de-noising method based on an unbiased Kalman filter (KF) is proposed to reduce the converted Doppler measurement errors before updating the target states for the constant velocity (CV) model. The states from the de-noising filter are then combined with the Cartesian states from the converted measurement Kalman filter (CMKF) to produce final state estimates. The nonlinearity of the de-noising filter states are handled by expanding them around the Cartesian states from the CMKF in a Taylor series up to the second order term. In the mean time, the correlation between the two filters caused by the common range measurements is handled by a minimum mean squared error (MMSE) estimation-based method. These result in a new tracking filter, CMDN-EKF2. Monte Carlo simulations demonstrate that the proposed tracking filter can provide efficient and robust performance with a modest computational cost.