Comparison of strapdown inertial navigation algorithm based on rotation vector and dual quaternion

 For the navigation algorithm of the strapdown inertial navigation system, by comparing to the equations of the dual quaternion and quaternion, the superiority of the attitude algorithm based on dual quaternion over the ones based on rotation vector in accuracy is analyzed in the case of the rotation of navigation frame. By comparing the update algorithm of the gravitational velocity in dual quaternion solution with the compensation algorithm of the harmful acceleration in traditional velocity solution, the accuracy advantage of the gravitational velocity based on dual quaternion is addressed. In view of the idea of the attitude and velocity algorithm based on dual quaternion, an improved navigation algorithm is proposed, which is as much as the rotation vector algorithm in computational complexity. According to this method, the attitude quaternion does not require compensating as the navigation frame rotates. In order to verify the correctness of the theoretical analysis, simulations are carried out utilizing the software, and the simulation results show that the accuracy of the improved algorithm is approximately equal to the dual quaternion algorithm.     

基于稳定约束的自适应随机共振转子故障检测方法

为解决应用传统遗传算法优化的随机共振(Stochastic resonance, SR)方法易出现的计算发散问题,提出一种基于稳定约束的自适应随机共振方法。对求解随机共振的Langevin方程进行了稳定性分析,得到了考虑输入信号的条件下,使系统输出稳定的频率压缩比R的约束公式。将该稳定性条件应用于遗传算法参数的寻优过程,将原来的无约束最优化问题转化为有约束最优化问题。将改进后的自适应随机共振方法应用于转子早期碰摩故障检测,分析结果表明,该方法确保了系统输出的稳定性,寻优过程中的频率压缩比R的取值均在约束值以下,避免了计算发散现象,实现了在强噪声条件下对微弱故障信号的提取。      

Cooperative task assignment of multiple heterogeneous unmanned aerial vehicles using a modified genetic algorithm with multi-type genes

The task assignment problem of multiple heterogeneous unmanned aerial vehicles （UAVs）, concerned with cooperative decision making and control, is studied in this paper. The heterogeneous vehicles have different operational capabilities and kinematic constraints, and carry limited resources （e.g., weapons） onboard. They are designated to perform multiple consecutive tasks cooperatively on multiple ground targets. The problem becomes much more complicated because of these terms of heterogeneity. In order to tackle the challenge, we modify the former genetic algorithm with multi-type genes to stochastically search a best solution. Genes of chromo- somes are different, and they are assorted into several types according to the tasks that must be performed on targets. Different types of genes are processed specifically in the improved genetic operators including initialization, crossover, and mutation. We also present a mirror representation of vehicles to deal with the limited resource constraint. Feasible chromosomes that vehicles could perform tasks using their limited resources under the assignment are created and evolved by genetic operators. The effect of the proposed algorithm is demonstrated in numerical simulations. The results show that it effectively provides good feasible solutions and finds an optimal one.     

调压阀快速开关定位控制算法研究

介绍了针对某车载气动试验设备中配置的特种高压调压阀而开发的一种控制算法,目的是将调压阀用于快速开关定位控制与压力调节双重任务。配置有快速阀和调压阀的系统,对调节过渡时间有严格的要求。调压阀用于根据实际系统工艺的要求,改变调压阀后的压力,以跟踪系统气源压力的变化。快速阀用于快速接通系统工作介质。由于受车载空间限制,通过本方案的改造,可以使系统不需使用快速阀,减小系统空间的占用,适合车载系统等对空间要求苛刻的场所。笔者提出的调压阀快速开关控制算法,经过实际验证,证明方法可行,效果良好,满足实际的需要。     

A faster optimization method based on support vector regression for aerodynamic problems

In this paper, a new strategy for optimal design of complex aerodynamic configuration with a reasonable low computational effort is proposed. In order to solve the formulated aerodynamic optimization problem with heavy computation complexity, two steps are taken: (1) a sequential approximation method based on support vector regression (SVR) and hybrid cross validation strategy, is proposed to predict aerodynamic coefficients, and thus approximates the objective function and constraint conditions of the originally formulated optimization problem with given limited sample points; (2) a sequential optimization algorithm is proposed to ensure the obtained optimal solution by solving the approximation optimization problem in step (1) is very close to the optimal solution of the originally formulated optimization problem. In the end, we adopt a complex aerodynamic design problem, that is optimal aerodynamic design of a flight vehicle with grid fins, to demonstrate our proposed optimization methods, and numerical results show that better results can be obtained with a significantly lower computational effort than using classical optimization techniques.     

脉冲噪声下基于梯度加权平均的变步长NLMP算法

针对非高斯 α 稳定分布噪声环境下的自适应滤波问题,提出一种新的基于梯度加权平均的变步长归一化最小平均p范数(VSS-NLMP)算法。该算法基于梯度矢量能够跟踪自适应过程的均方权值偏差(MSD)这一特点,通过对梯度矢量的平滑减小梯度噪声的影响,然后利用平滑梯度矢量的欧氏范数和系统误差的分数低阶矩控制步长的变化。文中给出了新算法的迭代过程,然后对其收敛性进行简要分析,仿真结果表明,本文新算法较现有变步长NLMP算法具有更快的收敛速度和更高的稳态精度。     

一种基于非圆相干信号的波束成形算法

空间平滑是一种传统去相干算法,此算法是基于圆信号提出的,同时存在孔径损耗问题。针对非圆相干信号,提出了一种全阵加权扩展空间平滑波束成形算法。首先将扩展空间平滑的子阵分解思想引入波束成形算法中,从理论上证明了算法的去相干特性,并通过分析证明了算法比传统空间平滑算法在可适用信源数上的提高。为了更好地去除期望信号与干扰间的相干性,利用虚拟波束得到权值对子阵进行加权。最后设计了一种转换矩阵,可将子阵波束权矢量扩展至全阵波束权矢量,从而避免了扩展空间平滑带来的孔径损耗问题。仿真结果表明了算法的可行性及优越性。     

一种基于有限记忆算法的干涉仪解模糊纠错方法

针对在通道相位误差较大时常规干涉仪测角解模糊算法频繁出错的问题,提出了一种基于有限记忆算法的干涉仪解模糊检测与纠错方法。利用干涉仪逐次递推测角算法解模糊的结果估计出角度和整周模糊值的初始值,在此基础上进行角度和整周模糊值的有限记忆递推,识别并纠正逐次递推测角算法中出错的解模糊测角数据,期望得到正确的解模糊结果,以保证后续角度数据的处理精度。仿真结果表明,有限记忆纠错算法能够有效地识别并纠正逐次递推解模糊测角算法中存在的模糊值出错问题,降低干涉仪解模糊的出错概率。此方法对其它体制的相位干涉仪测角解模糊纠错也具有一定指导意义。     

改进高斯混合粒子滤波的纯方位目标跟踪算法

针对纯方位跟踪系统非线性较强、传统跟踪滤波方法收敛速度慢且容易发散的问题,提出了一种基于改进高斯混合粒子滤波的纯方位跟踪算法。该算法基于Sigma点卡尔曼滤波(SPKF)和粒子滤波的特点,用有限的高斯混合模型来近似后验状态密度、系统噪声和观测噪声的分布。利用贪心EM算法实现模型的降阶,一定程度上克服了EM算法假定混合成分数为已知、迭代的结果需要依赖初始值、可能收敛到局部最大点和可能收敛到参数空间的边界的缺点,从而改善粒子枯竭的问题。仿真实验结果表明在纯方位跟踪领域,与传统粒子滤波(PF)和基于EM的高斯混合粒子滤波相比,该算法在保持高精度估计能力的同时,具有较强的鲁棒性,是解决非线性系统状态估计问题的一种有效方法。     

SpaceWire星载网络通信协议设计

SpaceWire是ESA和NASA推荐的新一代星载数据总线标准,其应用方向之一是构建统一总线星载网络。星载网络是典型的实时系统,它对网络信息的传输时延具有严格要求。然而,传统SpaceWire网络多源、异步、事件触发的特性使它难以提供确定的信息传输时延,这制约了它在统一总线星载网络中的应用。本文为克服SpaceWire的上述应用瓶颈,提出一种基于时间触发的SpaceWire星载网络通信协议,并提出相应的节点通信调度算法,通过合理的规划使节点在确定的时间窗口发送通信数据,从而避免了网络资源冲突,使信息传输时延的确定性得到保证。