尖前缘一体化高温热管启动性能计算分析

针对尖前缘高温热管工程设计与启动性能评估需求,基于描述碱金属高温热管启动过程的“温度锋面”模型,建立了一种用于分析不规则外形且承受非均匀瞬态气动加热的一体化尖前缘高温热管启动性能工程计算方法。该方法结合尖前缘气动加热环境分布特点进行计算节点划分,采用热管基本理论和局部能量守恒原理计算热管温度分布及“温度锋面”位置,实现尖前缘热管启动过程的理论预测。同时,采用均匀受热圆柱热管和尖前缘一体化热管启动试验结果对计算方法进行了验证。最后针对某尖前缘一体化高温热管结构在气动加热环境下的启动性能进行计算分析,提出了减小尖前缘高温热管启动时间的可能方法和措施：尖前缘高温热管启动后等温性良好,通过控制热管总长、壳体厚度、工质充装量等设计参数或调整热管初始温度可进一步缩短热管启动时间。     

惯性辅助的北斗导航故障自适应方法研究

北斗导航系统完好性是指北斗导航系统不能用于导航服务或导航精度超出给定范围时,具备及时发现故障并通知用户的能力.针对北斗导航完好性检测问题,为改善北斗导航定位系统的精度、连续性、完好性和可用性,研究了基于惯性辅助的北斗导航故障检测方法,设计了北斗导航系统的量测修正与故障检测实现方案,构建了基于新息正交性的自适应滤波北斗/SINS紧组合导航架构,根据滑动窗口内新息动态变化特性修正系统量测噪声方差,在北斗导航信号受到较大干扰、发生异常的情况下,对品质较差的卫星测量信号进行识别,并对检测超出一定阈值的突变卫星信号实现故障隔离,从而提高系统适应能力,增强北斗/SINS紧组合导航系统容错性.构建了北斗/SINS组合导航系统仿真验证模型,结果表明,基于惯性辅助的北斗导航方法能够有效检测出卫星信号故障,提高了系统的适应性和定位精度.     

A novel two-stage extended Kalman filter algorithm for reaction flywheels fault estimation

This paper investigates the problem of two-stage extended Kalman filter(TSEKF)-based fault estimation for reaction flywheels in satellite attitude control systems(ACSs). Firstly, based on the separate-bias principle, a satellite ACSs with actuator fault is transformed into an augmented nonlinear discrete stochastic model; then, a novel TSEKF is suggested such that it can simultaneously estimate satellite attitude information and actuator faults no matter they are additive or multiplicative; finally, the proposed approach is respectively applied to estimating bias faults and loss of effectiveness for reaction flywheels in satellite ACSs, and simulation results demonstrate the effectiveness of the proposed fault estimation approach.     

Cubature Kalman filter with closed-loop covariance feedback control for integrated INS/GNSS navigation

Cubature Kalman Filter (CKF) offers a promising solution to handle the data fusion of integrated nonlinear INS/GNSS (Inertial Navigation System/Global Navigation Satellite System) navigation. However, its accuracy is degraded by inaccurate kinematic noise statistics which originate from disturbances of system dynamics. This paper develops a method of closed-loop feedback covariance control to address the above problem of CKF. In this method, the posterior state and its covariance are fed back to the filtering process to constitute a closed-loop structure for CKF covariance propagation. Subsequently, based on the maximum likelihood principle, a control scheme of the prior state covariance is established by using the feedback state and covariance within an estimation window and further adopting a proportional coefficient to amplify the feedback terms in recent time steps for the full use of new information to reflect actual system characteristics. Since it does not directly use kinematic noise covariance, the proposed method can effectively avoid the adverse impact of inaccurate kinematic noise statistics on filtering solutions. Further, it can also guarantee the prior state covariance to be positive semi-definite without involving extra measures. The efficacy of the proposed method is validated by simulations and experiments for integrated INS/GNSS navigation.     

A practical filter error method for aerodynamic parameter estimation of aircraft in turbulence

It is common for aircraft to encounter atmospheric turbulence in flight tests. Turbulence is usually modeled as stochastic process noise in the flight dynamics equations. In this paper, parameter estimation of nonlinear dynamic system with both process and measurement noise was studied, and a practical filter error method was proposed. The linearized Kalman filter of first-order approximation was used for state estimation, in which the filter gain, along with the system parameters and the initial states, constituted the parameter vector to be estimated. The unknown parameters and measurement noise covariance were estimated alternately by a relaxation iteration method, and the sensitivities of observations to unknown parameters were calculated by finite difference approximation. Some practical aspects of the method application were discussed. The proposed filter error method was validated by the flight simulation data of a research aircraft. Then, the method was applied to the flight tests of a subscale aircraft, and the aerodynamic stability and control derivatives were estimated. All the estimation results were compared with the results of the output error method to demonstrate the effectiveness of the approach. It is shown that the filter error method is superior to the output error method for flight tests in atmospheric turbulence.     

任意谱宽随机白噪声条件下直接序列扩频体制抗干扰性能分析

依据匹配滤波器理论,对任意谱宽的随机白噪声条件下任意调制体制,特别是直接序列扩频体制的抗干扰性能进行了理论分析,推导出适用于任意谱宽噪声干扰的信噪比普适计算公式。最后指出,这一工作对电子对抗技术具有重要的实际意义。     

数字滤波器在定点DSP上的实现

介绍 FIR(Finite Impulse Response)和 IIR(Infinite Impulse Response)数字滤波器的网络结构及其在定点 DSP(Digital Signal Processing)上的实现方法 ,同时对定点 DSP软件设计中的关键问题——定标作了详细的阐述 ,并以二阶 IIR滤波器为例介绍定标的方法     

两传感器最优信息融合Kalman滤波器及其在跟踪系统中的应用

针对两传感器信息融合，提出了一种在标量加权下的最优信息融合Kalman滤波器。该信息融合滤波器考虑了局部滤波误差的相关性，避免了局部滤波误差方差阵的逆短阵的计算，也避免了加权短阵的计算，只要求计算加权系数，便于实时应用。一个跟踪系统的仿真例子验证了其有效性。     

自校正卡尔曼滤波及其在组合导航中的应用

自校正卡尔曼滤波可在状态估计的同时对状态方程的参数及卡尔曼增益进行辨识，从而提高了适应能力。文中讨论了它在组合导航中的应用。     

基于INS辅助的GPS接收机完善性监测算法研究

以惯性导航系统输出的数据作为辅助信息 ,对 GPS完善性监测算法进行了研究。该法以卡尔曼滤波新息序列为依据 ,对 GPS卫星的伪距测量值是否出现故障进行的检测 ,并给出了计算机仿真算例。仿真结果表明 :该方法能够及时准确地检测出 GPS故障星