基于改进最大期望算法迭代相位检测器的研究

近年来出现的基于最大期望(EM)迭代算法的相位同步算法具有比传统非数据辅助(NDA)相位估计算法更低的相位误差,是适合于Turbo编码系统的一种相位同步算法。然而,EM迭代算法对初值的选取比较敏感,收敛性较差。为了克服EM迭代算法收敛性较差的缺点,提出一种基于改进EM算法的Turbo编码系统迭代相位同步算法。针对EM算法的缺点,用数据辅助(DA)和NDA结合的方法得到的相位估计作为EM算法的初值。数值仿真显示,该方法具有比随机初始化EM算法更好的相位检测性能。     

Golay码的神经网络译码算法

本文提出了Golay码的一个神经网络译码器N(23,12),证明了Golay码的最大似然译码等价于N(23,12)收敛于能量函数的全局稳定状态。N(23,12)是一个异步的组合逻辑电路,能用12个大数逻辑门和77个异或门电路来实现。根据Golay码的循环结构,本文还提出了一个神经网络译码算法。计算机模拟表明,该算法达到了Golay码的纠错能力,并且,译码速度优于Kasami的修正捕错译码算法。新算法作为一种完全译码算法,不仅适用于Golay码,而且适用于任何循环码,特别是平方剩余码的译码。     

人的二维目标拾取运动试验设计及分析

在借鉴前人研究的基础上,设计并进行了较为全面的二维目标拾取运动实验,取得了大量有价值的实验数据.在理论研究和实验分析的基础上,提出了新的描述人的二维目标拾取运动的理论数学模型,并采用所获得的实验数据对本理论模型进行了实验系数确定,结果表明:该模型具有良好的适用性,不仅可以描述二维目标拾取运动,而且适用于一维情况;不仅可以描述手的目标拾取运动,而且还适用于其它肢体.     

存储器抗辐射加固的矩阵纠错码研究

为了纠正辐射环境中的高能粒子对存储器造成的多位翻转,研究了一种矩阵纠错码电路,对存储器进行有效的抗辐射加固。提出了一种矩形循环校验法构造校验位,并设计了纠错码的译码算法和相应的译码电路。根据校验位构造了检测位。对数据的输入顺序进行排列,确保了冗余位发生翻转时纠错码电路仍可以正常工作。在16位宽的码字中,所研究的矩阵纠错码可以纠正数据宽度为5位的多位翻转。同目前已知的二维纠错码在相同条件下进行比较,其获得了更高的平均失效时间。     

自适应预测补偿的迭代制导方法及其应用研究

针对迭代制导完成后入轨参数或终端程序角修正问题,研究一种基于模型参考的自适应预测补偿迭代制导算法在运载火箭上的应用。该算法在经典迭代制导算法的基础上,根据预测的迭代终端程序角和飞行视加速度的参考模型,对关机点参数进行补偿,依据补偿后的终端指标重新规划飞行轨迹,进而得出满足入轨参数或终端程序角偏差修正的制导指令,提升迭代制导对入轨参数偏差或终端程序角的修正能力。此外,阐述了经典迭代制导的基本算法,概括了自适应预测补偿迭代制导算法的基本原理,并以大推力直接入轨、终端程序角大偏差以及满足终端程序角约束为例,给出相应工况的自适应预测补偿的迭代制导算法。仿真结果表明：该算法对入轨参数和终端程序角偏差具有一定的修正能力。     

基于改进PSO算法的PID控制器参数优化

针对PID控制器参数设计问题,提出了一种基于改进PSO算法的优化方法。该方法将初始的粒子群分成两组搜索方向相反、相互协同的主、辅子群,在保持种群小规模情况下,增强算法全局探索能力,实现高精度的优化结果。仿真结果表明,该方法相比于传统算法,所得到的控制器参数使控制系统获得了更好的动态响应特性和满意的控制效果。     

基于路网匹配的多源自主组合导航技术研究

针对惯性/里程计组合导航易受环境影响的情况,引入路网匹配方法,以惯导/里程计组合导航历史轨迹数据与路网数据库进行全局匹配比较,从而得到当前导航位置的匹配点。将匹配点作为组合导航卡尔曼滤波器的量测输入,其滤波结果用于反馈校正惯导误差,通过不断迭代优化后,惯性/里程计/路网匹配组合导航能够提供高精度的位置信息。试验验证结果表明,该方法能将大部分定位误差控制在10m左右,证明了该方法的有效性与适用性。     

Comprehensive optimization design of aerodynamic and electromagnetic scattering characteristics of serpentine nozzle

Comprehensive optimization design of serpentine nozzle with trapezoidal outlet was studied to improve its aerodynamic and electromagnetic scattering performance. Serpentine nozzles with different center offsets and different ratios of the bases of the trapezoidal outlet were generated based on curvature control regulation. Computational Fluid Dynamics (CFD) simulations have been conducted to obtain the flow field in the nozzle, and Forward-Backward Iterative Physical Optics (FBIPO) method was applied to study the electromagnetic scattering characteristics of the nozzle. Guarantee Convergence Particle Swarm Optimization (GCPSO) algorithm based on Radial Basis Function (RBF) neural network was used to optimize the geometry of the nozzle in consideration of its aerodynamic and electromagnetic scattering characteristics. The results show that the GCPSO method based on RBF can be used to optimize the aerodynamic characteristics of the internal flow and the scattering characteristics of the cavity of the serpentine nozzle with irregular outlet. The optimized model has a higher center offset and a lower ratio of the bases of the trapezoidal outlet after optimization compared to the original model. The optimized model leads to a slight change in aerodynamic performance, with a total pressure recovery coefficient increase of 0.31% and a discharge coefficient increase of 0.41%. In addition, the Radar Cross Section (RCS) decreases also by around 83.33% and the overall performance is significantly improved, with a decrease of the optimized objective function by around 38.74%.     

基于AI+神经网络的数字化故障电弧识别方案研究

线路故障电弧的特征随着电力电子技术的提高更趋复杂，传统的故障电弧识别方式已无法应对新型用电系统。对比传统故障电弧识别方案，研究故障电弧产生类型和新型检测技术，提出基于谐波因素、总谐波畸变率、电流零休时间、电流变化速率、电流周期性等典型时域、频域特征的AI+神经网络的数字化故障电弧识别方案。该方案运用回归算法向量机对特征图进行分类处理，通过正向传输运算、反向传输运算和迭代回归运算三个步骤执行卷积神经网络，频繁迭代回归以获得最佳特征识别图。本文以调光器的故障电弧识别为例，对故障识别方案进行验证，结果表明采用此方案可实现更高效、更精准、更稳定地识别故障电弧。     

Autonomous navigation for lunar final approach based on gravity gradient measurements

Lunar final approach navigation is critical for pin-point lunar landing in future missions. This study investigates the use of lunar gravity gradient measurements for autonomous navigation of a lunar probe during the final approach phase. As the spacecraft approaches the Moon, the strength of gravity gradient signals improves. A spaceborne gravity gradiometer can precisely measure local gravity gradients, and the latest lunar gravity model GL1500E is used to provide reference values. The employed truncation degree and order of the gravity model are increased stepwise considering the decreasing altitude of the spacecraft in order to reach a compromise between computational costs and model accuracy. An iterative Kalman filter is developed for coupled orbit and attitude estimation using gravity gradient measurements and attitude quaternions obtained from star sensors. A simulated spacecraft with a gradiometer noise level of 0.01 E is considered. Simulation results show that the spacecraft’s position converges rapidly and achieves an accuracy of less than 100 m at the last epoch.