改进的宽带指向最小方差空间谱估计算法

宽带测向一直是阵列信号处理领域研究的难点。把指向最小方差宽带测向算法（STMV）应用到均匀线阵上，通过对阵列频域采样数据的空间协方差矩阵的估计和加权平均处理。给出了空间谱估计子的改进形式。与通常的信号子空间宽带测向算法相比。提出的算法不需要对波达方向进行预估计，因此避免了预估计误差对最终估计结果的影响。理论分析和仿真实验证明了测向算法的有效性。     

单参数指数分布定时截尾步加试验TFR模型下参数修正的MLE

给出了单参数指数分布定时截尾样本场合下步加试验TFR模型下参数的修正极大似然估计,并通过模拟表明修正的极大似然估计的精度高于极大似然估计。     

几何分布产品定数截尾场合下参数的点估计

本文给出几何分布产品定数截尾场合下参数点估计的几种方法,并通过随机模拟的方法考察了估计的精度。     

一种鲁棒GNSS矢量跟踪环

复杂环境下导航接收机的连续可用性一直是卫星导航领域的研究重点。针对矢量跟踪环动态适应性不够和误差在通道间传播的问题,提出一种鲁棒全球导航卫星系统(GNSS)矢量跟踪环。基于各通道的伪距、伪距率和伪距加速度状态量构建扩展卡尔曼滤波器(EKF),通过灵活设置过程噪声方差阵,实现跟踪通道的耦合与解耦;采用基于极大似然估计器(MLE)的鉴别器生成码延迟和载波频率偏差观测量;利用滤波值修正并预测伪距率来控制本地数控振荡器(NCO),实现环路的闭合。仿真结果表明,本文设计的矢量跟踪环在保证环路相互辅助的基础上,避免了衰减通道误差在通道间的传播,可以对被遮挡信号保持稳定跟踪,鲁棒性优于传统矢量延迟频率锁定环。     

自适应遗传神经网络算法在推力估计器设计中的应用

为了在全包线内能够准确方便估计出航空发动机推力,提出了一种自适应遗传神经网络算法:将遗传算法和神经网络技术相结合充分发挥遗传算法和神经网络各自的全局收敛性和局部搜索快速性的优点,其中通过自适应概率遗传操作及局部寻优算子直接优化出神经网络拓扑结构及权值(包括阈值),克服了神经网络隐层节点需凭经验尝试的缺点和神经网络对初始权值(包括阈值)敏感的缺点,再应用神经网络对上述优化的权值(包括阈值)进行"精调",最后设计出全包线推力估计器.经验证,此推力估计器具有较高估计精度和良好泛化能力.      

基于PSO-BP神经网络的固冲发动机推力估计器设计

为了对固体火箭冲压发动机的推力进行直接控制，提出了基于PSO（粒子群优化算法）优化BP（back propagation）神经网络的固体火箭冲压发动机推力估计方法。采用SPSO（标准PSO）和三种不同的BBPSO（骨干PSO）寻优神经网络权值，而后以最优权值进行BP网络训练，对其进行精调，如此便可获取推力和燃气流量、飞行马赫数以及飞行高度之间的非线性关系，从而完成推力估计器的设计。利用240组训练集数据对网络进行训练，并用180组测试集数据对网络进行验证。仿真结果表明：在SPSO、BBExp（exploiting BBPSO）、ABPSO^*（modified adaptive BBPSO）和SNPSO（simplified pruning strategy based BBPSO）等四种不同的PSO中，基于SNPSO优化BP神经网络实现推力估计器设计是最为便捷有效的方法，不仅形式简单，而且对于测试集数据而言，其能够将推力相对误差控制在5%以内。     

A high-safety active/passive hybrid control approach for compressor surge based on nonlinear model predictive control

Surge active control can expand the stable operating range of the compressor. However, the difficulty of flow measurement, dynamic uncertainty disturbance, actuator delay characteristics, hard constraints of control variable, and system security measures have not been fully considered in the existing active control system, which significantly hinders its engineering application. Therefore, a nonlinear model predictive surge active control method is first presented based on flow estimator designed by using a continuous-time Kalman filter for dealing with the hard constraint of control variable and the impact of actuator delay of compression system with dynamic uncertainty. Then, a high-safety active/surge passive hybrid control strategy is designed, dominated by the surge active control and supplemented by the surge passive control, to ensure the compression system’s safe and stable operation. Lastly, the simulation results suggest that the flow estimator accurately estimates the compressor flow. When considering the delay impact of the actuators and sensors and measurement noise on the system, the proposed method exhibits stronger robustness than the existing methods. The active/surge passive hybrid control strategy can successfully ensure the compression system's safe and stable operation. This paper is of high practical significance for the engineering application of future compressor surge active control technologies.     

Cramér-rao lower bound for pulsar rotation parameters estimation with X-ray pulsar observation data

In this paper, the Cramér-Rao Lower Bound (CRLB) for estimating the rotation parameters of pulsars using X-ray pulsar observation data is deduced, and the calculation equation is presented. In order to verify the correctness of the deduced equation, we use the X-ray pulsar observation data to estimate pulsar rotation parameters, and obtain the root mean square error (RMSE) of the estimated pulsar rotation parameters through conducting repeated experiments. The experimental results suggest that when the observation time increases, the RMSE gradually approaches the estimated CRLB, and that when the observation time is 2.4 × 10⁶ s, the error between the RMSE of pulsar frequency estimation and the CRLB stays at 10^?11 order of magnitude. This verifies that the CRLB expression deduced in this paper is the theoretical lower bound for estimating pulsar rotation parameters. The deduced CRLB in this paper helps determine the minimum variance estimator for pulsar rotation parameter estimation using X-ray pulsar data, providing a benchmark for the comparison between the minimum variance estimator and other estimators.