三维AoA目标跟踪的二次约束卡尔曼滤波算法

在基于到达角(angle of arrival, AoA)的三维目标跟踪中, 伪线性卡尔曼滤波具有稳定性高和计算复杂度低的优点, 但是严重的偏差问题使其跟踪精度迅速下降。针对该问题, 提出一种二次约束卡尔曼滤波(quadratic constraint Kalman filter, QCKF)算法。首先引入涉及所有观测噪声项的增广矩阵, 然后建立与线性卡尔曼滤波等价的目标函数并且附加含有二次项的约束条件, 以此降低偏差影响, 实现更准确的状态更新。QCKF算法采用广义特征值分解求解约束优化问题, 无法直接通过状态更新表达式推导其协方差矩阵, 因此利用约束条件以及矩阵扰动方法完成协方差矩阵更新。仿真分析表明, QCKF算法相较于其他非线性滤波算法具有更优的跟踪性能, 不仅在低噪声条件下可达到后验克拉美罗下界, 而且当噪声严重时能够显著降低跟踪误差, 并且计算开销不高。     

用于联盟链的布隆过滤器优化

布隆过滤器常用于联盟链Hyperledger Fabric状态数据库LevelDB的读性能优化，但布隆过滤器本身存在误报现象，且LevelDB只能对布隆过滤器进行统一配置而无法自适应调整。为此，提出一种单元化的部分计数式布隆过滤器（partial counting Bloom filter,PCBF）构造方案，设计可并行计算的元素插入与查询机制并结合双重哈希及非加密哈希来实现快速插入与查询；基于开启过滤器单元与访问次数构建排序字符串表优先级，使用时间片轮询算法对过滤器单元进行自适应调整，实现了资源的合理分配。实验结果表明： PCBF具有较高的插入效率，并能减少20%左右的误报数量，适用于联盟链的高并发场景。     

基于串扰判决反馈信道均衡算法的语音通信系统设计

在强电磁干扰环境下,由于语音通信受到通信信道的快速时变衰落和码间干扰的影响,导致信道不均衡,降低了语音通信质量。提出一种基于串扰判决反馈信道均衡的语音通信系统的设计方法。该方法采用横向滤波器进行电磁干扰滤波器设计,利用语音通信信息传输信道频率特性的逆大于信息自身带宽的特征,通过调整均衡器参数进行,进行串扰判决反馈设计,结合信道自适应均衡处理技术,进行强干扰环境下语音通信信道均衡,以达到语音通信系统的优化。系统仿真结果表明,该语音通信优化系统具有抗电磁干扰能力及滤波性能较好、输出信噪比高、通信距离远、通信速度快、可靠性高等优点。     

Processing and characterization of the microstructure and mechanical properties of Al6061–TiB2 composite

In the present research, aluminum metal matrix composites were processed by the stir casting technique. The effects of TiB2 rein-forcement particles, severe plastic deformation through accumulative roll bonding (ARB), and aging treatment on the microstructural charac-teristics and mechanical properties were also evaluated. Uniaxial tensile tests and microhardness measurements were conducted, and the micro-structural characteristics were investigated. Notably, the important problems associated with cast samples, including nonuniformity of the rein-forcement particles and high porosity content, were solved through the ARB process. At the initial stage, particle-free zones, as well as particle clusters, were observed on the microstructure of the composite. However, after the ARB process, fracturing phenomena occurred in brittle ceramic particles, followed by breaking down of the fragments into fine particles as the number of rolling cycles increased. Subsequently, com-posites with a uniform distribution of particles were produced. Moreover, the tensile strength and microhardness of the ARB-processed com-posites increased with the increase in the reinforcement mass fraction. However, their ductility exhibited a different trend. With post-deforma-tion aging treatment (T6), the mechanical properties of composites were improved because of the formation of fine Mg2Si precipitates.     

I ain’t afraid of no ghost

This paper criticizes the traditional philosophical account of the quantization of gauge theories and offers an alternative. On the received view, gauge theories resist quantization because they feature distinct mathematical representatives of the same physical state of affairs. This resistance is overcome by a sequence of ad hoc modifications, justified in part by reference to semiclassical electrodynamics. Among other things, these modifications introduce ”ghosts”: particles with unphysical properties which do not appear in asymptotic states and which are said to be purely a notational convenience. I argue that this sequence of modifications is unjustified and inadequate, making it a poor basis for the interpretation of ghosts. I then argue that gauge theories can be quantized by the same method as any other theory. On this account, ghosts are not purely notation: they are coordinates on the classical configuration space of the theory—specifically, on its gauge structure. This interpretation does not fall prey to the standard philosophical arguments against the significance of ghosts, due to Weingard. Weingard’s argumentative strategy, properly applied, in fact tells in favor of ghosts’ physical significance.     

行驶受扰延迟下配送车辆调度的干扰管理决策模型

针对行驶受扰延迟下配送车辆的调度问题,提出了基于多相量子粒子群算法的两阶段干扰管理决策方法.首先以最小化用户时间窗偏离度和最小化配送成本为目标,建立了问题的数学模型;然后对车辆配送发生干扰事件可能采取的干扰管理模式进行了归纳和分类,并在选定模式基础上提出了用多相量子粒子群算法进行路线选择的方法;最后在Solomon算例的基础上通过实验仿真,对所提出方法的性能进行测试,并与全局重调度方法进行对比分析,验证了本文方法不仅达到了优化目标的目的,还满足了干扰管理的实用性要求.     

基于模型参数在线辨识技术的SOC估算方法

针对遗传算法(genetic algorithm，GA)存在收敛速度慢、易陷入局部最优以及难以实现在线应用的问题，面向如动力电池等效电路模型一类非线性较强、实时性要求高的模型辨识问题，提出一种能够快速缩小搜索空间，且有效避免陷入局部最优的在线快速搜索的优化辨识框架，实现电动汽车动力电池等效电路模型参数在线快速辨识，扩展全局搜索优化算法的应用范围.进一步，将此算法应用于电池剩余荷电状态(SOC)估算问题，提出基于改进GA参数辨识技术的无迹粒子滤波SOC估算方法(IGA-UPF).并将此SOC估算方法与基于最小二乘参数辨识技术的无迹粒子滤波的SOC估算算法(LS-UPF)作比较，结果验证了本文提出的在线快速参数辨识框架具有更好的模型参数辨识精度.     

基于遗传算法优化神经网络的拼焊板压边力预测

通过数值模拟与神经网络技术对拼焊板盒形件拉深成形过程中的压边力预测问题进行研究.运用数值模拟分析压边力加载形式对拼焊板盒形件成形性能的影响，找到一种较优的变压边力加载方式.建立适用于拼焊板盒形件拉深成形压边力预测的BP神经网络模型.采用遗传算法对神经网络模型进行优化，在基因选择过程中加入精英保留策略，最终通过基于遗传算法优化的神经网络模型获取了理想的压边力曲线，用以预测随拉深行程变化的压边力数值，为实现智能化冲压奠定了技术基础.     

厚尾噪声条件下星凸形扩展目标student’s t滤波器

针对非线性非高斯厚尾噪声条件下的不规则形状的扩展目标跟踪问题,提出了基于随机超曲面模型(RHM)的星凸形扩展目标student’s t滤波算法.首先,在带有非高斯厚尾过程噪声和厚尾量测噪声的系统中, 基于student’s t分布给出鲁棒student’s t滤波器.其次,利用随机超曲面模型描述任意星凸形扩展目标的量测源分布, 提出带厚尾噪声的星凸形扩展目标student’s t滤波器.最后通过仿真验证了所提方法的正确性和有效性.     

基于改进灰狼算法的粒子滤波算法研究

针对传统粒子滤波算法易出现粒子贫化与权值退化现象和为了实现对非线性系统较为准确的状态估计,通常需要大量粒子的参与的问题,提出了基于改进灰狼算法的新型粒子滤波方法,该算法用粒子表征灰狼个体,模拟狼群捕猎的过程,使粒子向后验概率的高似然区域移动,提高粒子分布的合理性。在灰狼寻优算法中引入了莱维飞行策略,提高灰狼算法的收敛速度;在部分重采样前采用了权值自适应调整策略,增加粒子的多样性。仿真实验结果表明:改进的方法提高了粒子滤波的估计精度、保证了粒子的多样性与粒子分布的合理性、降低了状态估计所需的粒子数量。