基于自适应遗传BP算法神经网络数据融合的空中目标识别

空中目标识别是现代防空作战的重要研究内容。本文利用不同类型目标产生的多类型传感器的数据信息对目标进行识别。为了训练神经网络目标识别分类器,将遗传算法和BP算法相结合,提出了一种新的自适应遗传BP算法,利用这种神经网络来确定指标的权值。仿真试验结果表明,基于自适应遗传BP算法神经网络的识别是一种简单、可靠的目标识别方法,具有很好的目标识别效果。     

电液力伺服系统的神经网络并行自适应预测 PI 控制

考虑电液伺服系统的复杂非线性和不确定性特性,提出一类基于神经网络的并行自适应预测PI控制结构,该结构使控制参数的调整和系统的实时控制操作可并行进行,不仅做到了神经模型和控制器的在线辨识和设计,而且避免了神经网络方法通常存在的实时控制的困难,使复杂系统的在线学习控制成为可能。仿真结果表明该控制器具有良好的适应性和鲁棒性。      

An adaptive turbo-shaft engine modeling method based on PS and MRR-LSSVR algorithms

In order to establish an adaptive turbo-shaft engine model with high accuracy, a new modeling method based on parameter selection (PS) algorithm and multi-input multi-output recursive reduced least square support vector regression (MRR-LSSVR) machine is proposed. Firstly, the PS algorithm is designed to choose the most reasonable inputs of the adaptive module. During this process, a wrapper criterion based on least square support vector regression (LSSVR) machine is adopted, which can not only reduce computational complexity but also enhance generalization performance. Secondly, with the input variables determined by the PS algorithm, a mapping model of engine parameter estimation is trained off-line using MRR-LSSVR, which has a satisfying accuracy within 5&. Finally, based on a numerical simulation platform of an integrated helicopter/ turbo-shaft engine system, an adaptive turbo-shaft engine model is developed and tested in a certain flight envelope. Under the condition of single or multiple engine components being degraded, many simulation experiments are carried out, and the simulation results show the effectiveness and validity of the proposed adaptive modeling method.     

无人机涡喷发动机的神经网络自适应PID控制

将基于RBF神经网络的辨识网络与基于BP网络的控制器相结合，组成自适应PID神经网络控制系统。RBF神经网络采用离线学习在线修正权值和阈值，为加快收敛速度，应用带惯性项的梯度下降法。大量仿真结果表明，RBF网络较ELM，标准BP及改进的BP等网络具有明显优点。对某型无人机涡喷发动机控制系统的仿真结果表明此控制方式具有鲁棒性好、响应速度快、稳态误差小等优点。     

VS-CMA盲均衡算法在短波数据通信中的应用研究

在美军标MIL-STD-188-110B基础上,改进短波（HF）数据通信发送端数据流结构,以便接收端对信号进行盲均衡处理。基于8PSK调制信号的峰度为恒定值的统计特性,提出采用均衡输出信号的峰度与理想信号的峰度差异,以调整恒模算法（CMA）的步长因子;并针对国际电联推荐的短波信道参数,进行了算法的性能仿真。仿真分析表明该算法对慢衰落的短波信道具有较好的均衡效果,对快衰落信道的均衡能力有限;应对快速衰落信道,算法还有待进一步改进。     

Adaptive Gaussian sum squared-root cubature Kalman filter with split-merge scheme for state estimation

The paper deals with state estimation problem of nonlinear non-Gaussian discrete dynamic systems for improvement of accuracy and consistency. An efficient new algorithm called the adaptive Gaussian-sum square-root cubature Kalman filter（AGSSCKF） with a split-merge scheme is proposed. It is developed based on the squared-root extension of newly introduced cubature Kalman filter（SCKF） and is built within a Gaussian-sum framework. Based on the condition that the probability density functions of process noises and initial state are denoted by a Gaussian sum using optimization method, a bank of SCKF are used as the sub-filters to estimate state of system with the corresponding weights respectively, which is adaptively updated. The new algorithm consists of an adaptive splitting and merging procedure according to a proposed split-decision model based on the nonlinearity degree of measurement. The results of two simulation scenarios（one-dimensional state estimation and bearings-only tracking） show that the proposed filter demonstrates comparable performance to the particle filter with significantly reduced computational cost.     

总体最小二乘算法在自适应信道均衡中的应用研究

分析了最小二乘解产生偏差的原因,推导出了最小二乘解偏差项的数学表达式。提出了一种基于瑞利商的变步长总体最小二乘求解方法。仿真试验表明,总体最小二乘算法的性能优于加权递归最小二乘算法,是一种适用于输入信号端含有噪声的自适应信道均衡算法。     

基于规划航迹的“三自”光纤惯导系统航向耦合效应抑制技术

目前,国内"三自"(自标定、自对准、自检测)光纤惯导系统在长航时高精度自主导航领域已逐渐开展应用,但光纤陀螺安装误差、安装不正交度以及标度因数等参数稳定性大大限制了"三自"光纤惯导系统精度的提升,其主要原因是载体运动诱发的航向耦合效应严重影响了旋转调制效果。从航向耦合效应机理分析入手,指出了"三自"惯导系统航向耦合效应的不可解耦性,但针对无人飞行器和无人潜航器等通常需要规划航迹的载体,提出了一种基于规划航迹的旋转方案自适应调整技术,有效地抑制了航向耦合效应。试验结果表明,该方法可将系统的导航精度提升80%以上。     

A new steering approach for VSCMGs with high precision

A new variable speed control moment gyro (VSCMG) steering law is proposed in order to achieve higher torque precision. The dynamics of VSCMGs is established, and two work modes are then designed according to command torque:control momentum gyro (CMG)/reaction wheel (RW) hybrid mode for the large torque case and RW single mode for the small. When working in the CMG/RW hybrid mode, the steering law deals with the gimbal dead-zone nonlinearity through compensation by RW sub-mode. This is in contrast to the conventional CMG singularity avoidance and wheel speed equalization, as well as the proof of definitely hyperbolic singular property of the CMG sub-mode. When working in the RW single mode, the motion of gimbals will be locked. Both the transition from CMG/RW hybrid mode to RW single mode and the reverse are studied. During the transition, wheel speed equalization and singularity avoidance of both the CMG and RW sub-modes are considered. A steering law for the RWs with locked gimbals is presented. It is shown by simulations that the VSCMGs with this new steering law could reach a better torque precision than the normal CMGs in the case of both large and small torques.     

基于双摄像机的立体视觉图像预处理研究

针对立体图像对的亮度差异问题和图像噪声问题研究图像的强化处理,图像预处理主要完成图像对极线校正和图像质量增强.极线校正部分以对极几何为基础研究立体图像对的校正算法.图像质量增强部分主要研究了立体图像对特有的亮度差异问题,并提出了应用直方图均衡化来校正亮度的方法.之后本文对图像噪声进行了深入的分析,并针对立体图像特点使用均值滤波和Gauss滤波平滑图像.在实验中,验证了算法的可行性,取得了良好的应用效果.