空时自适应处理张量波束成形器的外积合成法

为了解决空时自适应处理（Space-Time Adaptive Processing，STAP）对足量平稳训练快拍的要求，给出了一种设计STAP张量波束成形器的新算法——空时自适应处理张量子波束合成（TSS-STAP）法。分析表明：STAP中所需要的张量波束成形器，可首先在张量的各个子维度上分别进行子波束成形器的设计，然后再由张量的外积运算合成各子波束成形器而得到。进一步分析表明：由于本文算法可在较低自由度（DoF）的子维度上对张量波束成形器进行设计，因此降低了设计所需要的训练快拍数和计算复杂度，同时也实现了有效的去相关处理，使得其在非均匀杂波环境下有更好的目标检测性能。在仿真实验中，所提算法有效提升了目标检测结果，同时降低了目标检测所消耗的时间。     

Kalman filtering for GPS/magnetometer integrated navigation system

This paper investigated the data processing method for a GPS/IMU/magnetometer integrated system with Kalman filtering (KF). As a result of GPS/IMU/magnetometer land vehicle system, dead-reckoning of magnetometer and accelerometer integrated subsystem bridged very well the GPS signal outage due to the trees on the two sides of the road. Both differential GPS data processing method and the carrier-phase method with magnetometers’ outputs for predicting the car position, velocity, and acceleration (PVA) are presented. The results from DGPS with Kinematical Positioning (KINPOS) software shown that the averages of the north, east, and down direction standard deviation (short for “std”) are 0.014, 0.010, and 0.018 m, respectively. The std of velocities and accelerations derived by the position and velocity differentiation are 10, 7, 13 mm/s, 7, 5, 9 mm/s², respectively. This method for getting velocities and accelerations requires higher accurate position coordinates. But the position accuracy has frequently been degraded in this case when the car drove under the trees or other similar kinematical environments. That caused the larger velocity and acceleration errors. While the results from the carrier-phase method are std of the velocities = 2.1 mm/s, 1.3 mm/s, 3.7 mm/s in north, east, down, and std of the accelerations = 1.5 mm/s², 0.9 mm/s², 2.3 mm/s² for the static test period; as compared with KINPOS software results, std of the velocity difference between the carrier-phase method and the DGPS method = 7 mm/s, 6.9 mm/s, 9.7 mm/s in north, east, down direction, and std of acceleration difference = 5.0 mm/s², 4.5 mm/s², 7.5 mm/s² in north, east, down direction for the kinematical test period. Obviously, errors come from both the carrier-phase method and DGPS velocity and acceleration results derived directly by the position differentiation. In addition, better accuracy of positions than that before KF has been got by means of velocities and accelerations derived by the carrier-phase method after KF.     

Specification of the Earth’s plasmasphere with data assimilation

In this paper we report on initial work toward data assimilative modeling of the Earth’s plasmasphere. As the medium of propagation for waves which are responsible for acceleration and decay of the radiation belts, an accurate assimilative model of the plasmasphere is crucial for optimizing the accurate prediction of the radiation environments encountered by satellites. On longer time-scales the plasmasphere exhibits significant dynamics. Although these dynamics are modeled well by existing models, they require detailed global knowledge of magnetospheric configuration which is not always readily available. For that reason data assimilation can be expected to be an effective tool in improving the modeling accuracy of the plasmasphere. In this paper we demonstrate that a relatively modest number of measurements, combined with a simple data assimilation scheme, inspired by the ensemble Kalman filtering data assimilation technique does a good job of reproducing the overall structure of the plasmasphere including plume development. This raises hopes that data assimilation will be an effective method for accurately representing the configuration of the plasmasphere for space weather applications.     

基于二分法的EKF SLAM算法

针对基于点特征的SLAM算法对实际环境描述运算量大的缺陷,提出了基于二分法的线特征SLAM仿真算法。通过判断机器人点到线特征直线的垂足所在位置选择不同的计算顺序,避免了直接求解带来的较大运算量。算法分析表明,该SLAM算法可以减少运算量,提高计算速度,并增强机器人的构图定位能力。基于该算法进行了仿真实验,实验结果表明,该算法有效地提高了运算速度,使得机器人可以更好地完成构图定位任务。     

软件无线电中FSK信号解调的一种快速算法

本文介绍了采用差分检波解调算法实现软件无线电中移频键控信号(FSK)快速解调方祛，并通过数字信号处理技术验证了该解调方祛。     

连续最小阶奇异滤波器

 本文讨论了当动态噪声统计特性未知时,奇异线性定常连续随机系统最小阶滤波器的设计问题。在系统部分观测量能精确测量的情况下,利用广义逆阵方法选择L矩阵,以消除动态噪声对降阶系统的影响,从而推导出缺动态噪声统计特性时的降阶奇异最优滤波器,其阶数为n-m+r。当量测方程奇异假设条件成立及引理有解时,本文证明了最小阶奇异滤波器必定存在。文中举例说明了这一降阶滤波方法的可行性。     

卡尔曼平滑的自校准技术

介绍了卡尔曼平滑技术的固定区间平滑方法，推导了非线性时变模型的固定区间平滑公式，并将之应用到轨道约束自校准技术中，且导出了相应公式。     

基于STF的Jerk模型自适应机动目标跟踪算法

在Jerk模型的基础上,提出了一种新的机动目标自适应跟踪算法STF-Jerk。该算法通过引入强跟踪滤波器(STF)的渐消因子,实时调节滤波器增益,增强了系统对突发机动的自适应跟踪能力,从而很好地改善了Jerk模型在跟踪机动目标时的跟踪精度。仿真结果表明,提出的STF-Jerk自适应跟踪算法显著提高了Jerk模型自适应算法的机动目标跟踪性能。     

非线性分离算法及其在飞行试验中的应用

 本文根据最小方差估计和分离算法原理,提出一种新的非线性状态估计和偏差辨识的分离算法。并用此算法确定飞行状态和测试仪器的误差,同时U-D分解保证计算效率和数值稳定性。为了得到数据相容性检验的准确结果,本文采用直接离散化的飞机运动模型,以减小模型误差。通过仿真并在我国两种歼击机上实际应用,结果表明本文所给的算法对不同的初值和噪声统计特性都能得到飞行数据相容性检验的一致结果,并能用于低采样率下的数据相容性检验。     

一种基于移动辅助节点的单兵导航系统协同初始化算法

惯性导航系统凭借其自主性强、隐蔽性好、可靠性高的优势,在单兵作战、反恐救援中发挥越来越重要的作用。针对单兵惯性导航系统精度较低,在长期工作后精度下降严重,需要重新初始化的问题,以单兵与无人平台的协同作业为背景,提出了一种基于移动式辅助节点的单兵导航系统协同快速初始化方法。该方法以目标节点的角增量、位移增量信息与测距信息作为输入,采用粒子滤波技术对单兵导航系统的位置和航向进行协同估计。试验表明,该算法最少仅需1个辅助节点即可实现较好的单兵惯导系统位置和航向初始化。