基于模糊卡尔曼滤波的内阻尼姿态算法研究

在系统机动性不强的情况下，传统的平台内阻尼算法将系统本身的速度信息通过阻尼网络加到系统中，达到提高姿态角精度的目的。将这种平台内阻尼的思想引入到捷联惯性航姿系统中，在系统加速度较小的情况下，利用加速度计的输出估计系统姿态角，通过卡尔曼滤波的形式补偿系统姿态误差。由于加速度的大小直接影响滤波器精度，本文设计了模糊自适应卡尔曼滤波算法，根据三轴加速度计的输出调整内阻尼量测误差方差阵，从而避免了滤波器的发散。仿真和实验验证，内阻尼算法可明显抑制舒勒周期振荡和傅科周期振荡，避免了系统姿态漂移，有效提高了捷联惯性航姿系统的精度。     

基于FPGA的M位并行分布式算法的FIR滤波器设计

介绍基于查找表结构的分布式算法的基本原理,提出M位并行分布式算法的实现方法。以2位并行分布式算法结构的FIR滤波器设计为例,在Altera Cyclone系列芯片上实现32阶12位FIR滤波器,并对其性能和资源占用进行分析。     

扩频通信系统中窄带干扰抑制技术的研究

提出一种基于小波包变换抑制窄带干扰的简化方法,利用直接序列扩频信号的功率谱密度分布特点和能量聚集度准则,快速、有效地跟踪输入信号频谱的变化,从而对扩频信号中的干扰进行快速定位;通过自适应改变权系数的方法实现对强、弱窄带干扰的分别抑制。仿真结果表明,这种自适应干扰抑制法既可以有效地清除快速时变的强窄带干扰,又可在处理其他类型干扰时避免或减小有用信息的损失,从而大大提高了直接序列扩频系统在复杂干扰情况下的抗干扰性能。     

Inner Attitude Integration Algorithm Based on Fault Detection for Strapdown Inertial Attitude and Heading Reference System

This article proposes a new inner attitude integration algorithm to improve attitude accuracy of the strapdown inertial attitude and heading reference system(SIAHRS), which, by means of a Kalman filter, integrates the calculated attitude from the accelerometers in inertial measuring unit(IMU), called damping attitudes, with those from the conventional IMU. As vehicle's acceleration could produce damping attitude errors, the horizontal outputs from accelerometers are firstly used to judge the vehicle's motion so as to determine whether the damping attitudes could be reasonably applied. This article also analyzes the limitation of this approach. Furthermore, it suggests a residual chi-square test to judge the validity of damping attitude measurement in real time, and accordingly puts forward proper information fusion strategy. Finally, the effectiveness of the proposed algorithm is proved through the experiments on a real system in dynamic and static states.     

Radio/FADS/IMU integrated navigation for Mars entry

Supposing future orbiting and landing collaborative exploration mission as the potential project background, this paper addresses the issue of Mars entry integrated navigation using radio beacon, flush air data sensing system (FADS), and inertial measurement unit (IMU). The range and Doppler information sensed from an orbiting radio beacon, the dynamic pressure and heating data sensed from flush air data sensing system, and acceleration and attitude angular rate outputs from an inertial measurement unit are integrated in an unscented Kalman filter to perform state estimation and suppress the system and measurement noise. Computer simulations show that the proposed integrated navigation scheme can enhance the navigation accuracy, which enables precise entry guidance for the given Mars orbiting and landing collaborative exploration mission.     

星间相对测量自主导航的改进容积卡尔曼滤波

针对仅利用星间相对位置测量的双星自主导航系统，提出一种基于可观度的改进容积卡尔曼滤波算法。该算法从系统可观度的物理意义出发，通过对预测协方差阵进行在线调整改善标准容积卡尔曼滤波算法对系统可观度敏感和不满足滤波拟一致性等问题。对具体算例进行数值仿真，校验了该改进容积卡尔曼滤波算法在基于星间相对位置测量的双星自主导航系统中的有效性，与标准容积卡尔曼滤波相比趋稳更快，精度更高。     

双T型量子线的电子自旋极化输运性质

文章研究了一个由两个T型异质结串联耦合量子结构的自旋输运性质。该结构中含有Rashba自旋轨道耦合相互作用。在工作中,计算了电子在自旋极化入射和自旋非极化入射两种情况下,电子在出射端的自旋极化率随体系结构的变化。发现通过适当的设计结构,当电子自旋非极化入射时,在出射端可以得到高达0.9的自旋极化率。其物理机制来源于体系结构引起的电子干涉使自旋向上的电子和自旋向下的电子有不同的透射率。     

Modified unscented Kalman filtering and its application in autonomous satellite navigation

In this paper, a modified unscented Kalman filter (UKF) for nonlinear stochastic systems is proposed, and it is applied to autonomous orbit determination for Earth satellites. Based on some standard results about the boundedness of stochastic processes and a new formulation of the unscented transformation (UT), it is demonstrated that the design of the noise covariance matrix plays an important role in enhancing the filter stability. Furthermore, a particular design of the noise covariance matrix is proposed as a modification of the UKF. The modified UKF is less sensitive to the initial error than the usual one. High performance of the modified UKF is illustrated in comparison with the usual one by using the real data obtained from an Earth sensor.     

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.     

不同叶片尾缘结构对流换热特性实验

为了研究不同叶片尾缘结构对对流换热系数的影响规律,设计了三种尾缘结构,并搭建了实验台,采用红外热像仪对叶片尾缘的壁温进行测量。研究结果表明,（1）三种尾缘结构的对流换热系数沿壁面的分布有很大差异,针对实验件I,对流换热系数存在一最大值,且最大值出现的位置随着吹风比的增加而逐渐远离气膜出口;（2）实验件II和III的对流换热系数沿壁面均呈现逐渐降低的趋势,但降低的规律二者又不相同;（3）在相同壁面位置,实验件III的对流换热系数最高,而实验件I的对流换热系数最低,因此可以认为,实验件III所示的尾缘结构更有利于对叶片尾缘更好的冷却。