复杂背景下目标模板更新算法研究

在匹配跟踪算法中,模板更新策略是跟踪成败的关键。从复杂背景下的目标跟踪出发,指出固定模板和逐帧模板更新的不足之处,介绍几种性能较好的模板更新策略,并在此基础上提出改进的模板更新方法。同时,为了更好地克服背景光照带来的影响,对普通最小平均绝对差值函数MAD(M in imum Absolute D ifference)方法进行了改进。仿真实验结果表明,该算法能克服诸如烟尘干扰、背景光照变化、地貌起伏等不利因素,能在复杂背景中稳定和精确地进行目标跟踪。     

基于ECEF的误差配准与目标跟踪算法

考虑量测噪声和地球曲率对配准的影响,提出了一种基于地心坐标系(ECEF)的扩展卡尔曼滤波(EKF)配准与目标艰踪算法.根据坐标系转换关系,给出误差配准计算公式,建立目标的动态方程,用EKF方程进行估计.仿真结果表明:该法能同时有效估计目标运动状态和传感器配准误差,可用于远距离的传感器配准和目标跟踪.     

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.     

飞行器自适应控制参考模型建立方法研究

针对模型参考自适应控制中参考模型的建立问题,探讨了三种模型设计方法:经典控制设计、最优化控制设计和利用Wonham可控标准型设计,并通过仿真算例比较了三种方法在飞行品质、飞机特性、匹配性和算法性能上的优劣,为模型参考自适应控制系统中参考模型的建立提供了理论依据.     

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.     

基于自适应的变形式陆空机器人转域过程飞行控制

针对一种变形式四旋翼陆空两栖机器人，研究空陆转域飞行控制方法，为实现陆空机器人从空中到地面的连续机动奠定了基础。建立了等效于变形式四旋翼陆空两栖机器人的飞行及转域系统结构模型和动力学模型，针对转域变形过程中转动惯量的改变及复杂飞行环境中负载变化和机体质量受损问题，在设计了基于线性二次型调节器（LQR）算法的姿态控制器和基于比例-积分-微分（PID）算法的高度控制器基础上，设计加入模型参考自适应系统（MRACS）解决模型参数不确定性问题。利用Adams/MATLAB联合仿真，首先得到空陆转域变形角度的极限值，然后对比仿真有无自适应补偿器的控制效果验证了该控制方法的高效性。研制了转域飞行样机，对空陆转域变形角度极限值和飞行控制方法进行了试验验证。     

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。     

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.     

基于空域滤波的二维全极化散射中心快速提取

在全极化逆合成孔径雷达(ISAR)体制下,二维相干极化几何绕射(CP-GTD)模型能够精确描述雷达目标高频电磁极化散射特性。针对CP-GTD模型,提出了一种基于空域滤波的二维全极化散射中心参数快速提取方法。该方法利用空域滤波将二维全极化散射中心参数提取问题分解为多个一维全极化散射中心提取问题,进而利用一维旋转不变技术(1D-ESPRIT)分步对全极化散射中心各维参数进行联合估计,最后利用最小二乘方法获得相干极化散射矩阵的估计。此外,采用这样的分步估计过程,可以实现二维参数的自动配对。复杂度分析和仿真实验表明:该方法不仅能够显著降低运算量,并且还能获得较好的估计精度,可以有效地用于目标全极化散射中心提取。     

Simultaneous spacecraft attitude and orbit estimation using magnetic field vector measurements

Based on magnetometer measurements only, three-axis attitude, rate, and orbit estimation are successfully achieved. A single Augmented Dynamics Extended Kalman Filter (ADEKF) is configured by combining the spacecraft nonlinear attitude dynamics and quaternion kinematics with orbital mechanics. The filter design is adopted for three-axis stabilized spacecraft in low Earth orbits where the aerodynamic drag is the dominant source of disturbances in addition to the spacecraft magnetic residuals. To reduce the computational burden, another Interlaced Extended Kalman Filter (IEKF) is developed to uncouple the attitude/rate from the orbit dynamics. Both filters are implemented using the magnetometer measurements and their corresponding time derivatives. As a part of EgyptSat-1 flight scenario, detumbling and standby modes are used for performance testing of the ADEKF. The concept of local observability is applied to the basic filter and the stability is investigated by incorporating extensive Monte Carlo simulations with uniformly distributed initial conditions. The filter shows the capability of estimating the attitude better than 5 deg and rate of order 0.03 deg/s in each axis. In orbit estimation, the filter is capable of estimating the position with accuracy less than 8 km and velocity upto 5 m/s in each axis.