内转式进气道/冯·卡门乘波体一体化设计方法

应用特征线理论设计了内转式轴对称基准流场以及外压缩轴对称基准流场，利用激波交线、流线追踪方法等相关技术提出了一种头部进气式的高超声速飞行器内转式进气道/冯·卡门乘波体一体化设计方法，并对生成的一体化构型进行了数值模拟及分析，数值结果验证了该方法的正确性和有效性。该一体化设计方法基本保留了内转式进气道的优良特性，并以高升阻比乘波体为原型构建较高升阻比的一体化构型，从流场耦合的角度出发为减弱机体与进气道之间复杂的波系干扰，实现飞行器内外流的完全耦合进行了探索。     

基于浸入与不变理论的航天器姿态跟踪自适应控制

针对惯性参数不确定的航天器姿态跟踪控制问题，基于浸入与不变（I&I）方法设计出了一种新的姿态跟踪控制器。研究结果表明，传统的浸入与不变方法运用到姿态跟踪模型，存在参数回归矩阵不可积进而导致偏微分方程无解析解的问题。针对该问题，提出了一种对回归矩阵改造使其满足可积条件的方法，通过动态放缩技术消除了回归矩阵改造前后的差异对闭环系统稳定性的影响，设计出了一种新的航天器姿态跟踪自适应控制器。通过李雅普诺夫稳定性分析方法证明了所设计的控制器能够保证闭环系统的全局渐近稳定性。相对于已有的基于动态放缩法的浸入与不变控制器，设计了一种全新的缩放因子，使得控制器的执行不需要缩放因子的信息，并且也不需要惯量矩阵的先验信息。最后，仿真对比实验进一步验证了所设计控制器的有效性和优越性。     

A novel strong tracking cubature Kalman filter and its application in maneuvering target tracking

The fading factor exerts a significant role in the strong tracking idea. However, traditional fading factor introduction method hinders the accuracy and robustness advantages of current strong-tracking-based nonlinear filtering algorithms such as Cubature Kalman Filter (CKF) since traditional fading factor introduction method only considers the first-order Taylor expansion. To this end, a new fading factor idea is suggested and introduced into the strong tracking CKF method. The new fading factor introduction method expanded the number of fading factors from one to two with reselected introduction positions. The relationship between the two fading factors as well as the general calculation method can be derived based on Taylor expansion. Obvious superiority of the newly suggested fading factor introduction method is demonstrated according to different nonlinearity of the measurement function. Equivalent calculation method can also be established while applied to CKF. Theoretical analysis shows that the strong tracking CKF can extract the third-order term information from the residual and thus realize second-order accuracy. After optimizing the strong tracking algorithm process, a Fast Strong Tracking CKF (FSTCKF) is finally established. Two simulation examples show that the novel FSTCKF improves the robustness of traditional CKF while minimizing the algorithm time complexity under various conditions.     

面向复杂场景的鲁棒KCF行人跟踪方法

经典核相关滤波(Kernel correlation filter,KCF)目标跟踪算法是判别式跟踪算法中效果最好的一种跟踪算法。但该算法不能很好地适应目标尺度的变化,且在遇到目标短暂消失或被其他物体遮挡等复杂情形时不具备处理目标重显的能力,因此,为使得目标跟踪能够有效地应对遮挡情形,本文从提高特征表达能力、增加尺度匹配策略和抗遮挡3个方面对经典KCF算法进行改进,提出了一种鲁棒的KCF行人跟踪算法。首先对方向梯度直方图(Histogram of oriented gradients,HOG)特征和色调、饱和度、值(Hue-saturation-value,HSV)特征的响应分布进行特征融合。其次,设置动态选择尺度池来改进滤波器的固定尺寸匹配。最后,通过滤波器响应最大值的变化率衡量目标的遮挡情况,并根据上一成功帧的目标信息,通过EdgeBoxes和感知哈希算法找回目标,更新滤波器。本文所提方法在公开视频跟踪数据集Benchmark上进行测试,实验结果表明与其他目标跟踪方法相比,本文算法提高了尺度变化、遮挡等复杂情形下跟踪的鲁棒性,确保了较高的跟踪精度。     

基于跟瞄和加表PI滤波近程相对导航方法

针对由于加速度计存在漂移和目标星加速度未知,基于C-W(Clohessey-Whiltshire)方程递推的近程相对导航无法长时间使用的问题,提出了一种基于跟瞄相对测量信息修正相对位置/相对速度误差和估计加表漂移的方法,并给出了比例积分(PI)滤波近程相对导航算法。最后,进行了工程应用方式分析和仿真验证。相对位置误差估计精度优于50 m。仿真结果表明:该方法既能确保相对位置和相对速度输出的连续性,又可抑制跟瞄观测噪声并消除长时间积分累积误差。基于PI滤波的近程相对导航方法计算简单,易于工程实现,且已通过在轨考核验证。     

大气层外多拦截器协同跟踪与制导算法

针对大气层外多弹头多诱饵的进攻场景，采用多拦截器全拦截策略，提出了带故障诊断的协同跟踪算法、时间协同中制导律以及消除脱靶量的末制导律。首先，基于最小二乘算法以及误差传播理论，实现了局部信息融合以及测量方程的线性化，简化了非线性跟踪滤波算法的设计；并依托滤波算法，设计了传感器故障诊断算法，以排除其对跟踪效果的影响。然后，基于对拦截器和目标受力的合理简化，给出了相对运动解析解，设计了有限推力下的多拦截器时间协同中制导律以及末制导律，实现对多个目标的同时击毁。仿真结果显示，本文设计的协同跟踪与制导算法，可以有效估计目标的状态并排除故障传感器的干扰，实施对多个目标的时间协同拦截。     

Performance limitations in trajectory tracking control for air-breathing hypersonic vehicles

An integrated approach that considers the performance limitations of tracking control systems for air-breathing hypersonic vehicles is proposed. First, a set of ascent trajectories is obtained as candidates for tracking control through a trajectory design method that considers the available acceleration. Second, the basic theory of performance limitations, which is adopted to calculate the limits on control performance through the trajectory, is integrated. The open-loop dynamics of air-breathing hypersonic vehicles is responsible for these limits on the control system. Comprehensive specifications on stability, tracking accuracy, and robustness are derived, and the flight envelope with constraints and control specifications is identified. Simulation results suggest that trajectory design should consider restrictions on control performance to obtain reliable solutions.     

A Poisson multi-Bernoulli mixture filter with spawning based on Kullback–Leibler divergence minimization

In the classical form, the Poisson Multi-Bernoulli Mixture (PMBM) filter uses a PMBM density to describe target birth, surviving, and death, which does not model the appearance of spawned targets. Although such a model can handle target birth, surviving, and death well, its performance may degrade when target spawning arises. The reason for this is that the original PMBM filter treats the spawned targets as birth targets, ignoring the surviving targets’ information. In this paper, we propose a Kullback–Leibler Divergence (KLD) minimization based derivation for the PMBM prediction step, including target spawning, in which the spawned targets are modeled using a Poisson Point Process (PPP). Furthermore, to improve the computational efficiency, three approximations are used to implement the proposed algorithm, such as the Variational Multi-Bernoulli (VMB) filter, the Measurement-Oriented marginal MeMBer/Poisson (MOMB/P) filter, and the Track-Oriented marginal MeMBer/Poisson (TOMB/P) filter. Finally, simulation results demonstrate the validity of the proposed filter by using the spawning model in these three approximations.     

基于PXI平台的半球谐振子相位幅度控制

半球谐振子作为半球谐振陀螺的核心部件之一，其振动参数的测试对自身结构设计与加工过程的参数优化具有至关重要的作用。作为测试系统的重要组成部分，本文设计并实现了基于PXI平台应用LabVIEW编程的半球谐振子相位幅度控制系统，针对测试中存在的谐振频率的漂移和振幅衰减等问题给出了解决方案。实物测试结果表明：该测试系统能有效地实现半球谐振子的相位跟踪及能量控制，可解决开环测试方案下谐振子的频率漂移问题以及初始振幅不一致对谐振子振动性能参数测试的影响，具有快速性好、控制精度高、功能扩展便捷等优点，极大提高了半球谐振子批量化生产与测试效率。     

稳定跟踪平台的FKAPID控制算法

针对传统PID控制算法在稳定跟踪平台控制中的诸多问题,提出一种带有卡尔曼滤波器的基于前馈补偿和抗积分饱和PID(FKAPID)控制的控制方法。计算机仿真实验表明,控制方法使系统的单位阶跃响应的超调量减小到6%,调节时间缩短至1.4 s,跟踪误差的均方差值减小了1个数量级以上,动态响应性能、对周期性信号的跟踪性能和对干扰的抑制能力明显提高。