基于阶次跟踪和BP网络的齿轮箱故障模式识别

在对齿轮箱的原始振动信号进行时域采样的基础上,利用小波包分析对其进行消噪,然后对得到的数据进行角域重采样,得到基于阶次跟踪的采样信号,再对该信号进行特征参量提取,最后利用BP网络对得到的故障特征参量集进行模式识别。该方法能够避免传统分析方法中难以克服的“频率模糊”现象,对于瞬态信号有较好的分析处理能力,是对传统频谱分析法的有力补充。     

基于相控阵雷达自适应波束形成的抗干扰技术

基于相控阵雷达自适应多波束,研究了相控阵雷达抗干扰的新方法,该方法把自适应波束调零控制技术、副瓣对消技术和极化选择抗干扰技术综合应用于相控阵接收多波束形成中,使相控阵雷达具有良好的抗干扰性能。     

基于采样卡尔曼滤波的水下被动目标跟踪

针对水下被动目标跟踪问题中,采用直角坐标系容易出现滤波发散,而修正极坐标系下过程模型强非线性的问题,研究了一种修正极坐标系下的采样卡尔曼滤波算法.采样卡尔曼滤波比传统的扩展卡尔曼滤波更好地逼近状态方程和测量方程的非线性特性,给出更精确的均值和协方差的估计,并且适用于过程噪声与状态估计非线性耦合的情况.在修正极坐标系下,采用3种滤波方法求解被动目标跟踪问题,仿真结果表明,采样卡尔曼滤波的滤波精度优于传统的扩展卡尔曼滤波方法和自适应扩展卡尔曼滤波方法.     

基于SNF的一种检测和跟踪性能优化方法

对于一个监视系统,跟踪性能的优化要求检测系统和跟踪系统通过引入反馈进行联合设计,针对最大量测幅值邻域滤波器(SNF),提出了先验和后验检测跟踪优化准则,通过分析得出先验优化准则不可行这一结论,而利用后验优化准则同时对检测阈值和门值的联合优化,仿真结果表明,用后验优化准则进行检测和跟踪性能优化,不仅具有比恒虚警率更好的跟踪精度,而且其计算代价也大为降低.     

变论域模糊自适应滑模有限时间收敛制导律

针对拦截高速机动目标的需求,研究了一种变论域模糊自适应滑模有限时间收敛制导律。推导了导弹-目标空间拦截模型,设计了三维滑模制导律;根据有限时间收敛制导律专家的经验,采用模糊自适应控制方法对滑模制导律的非切换项进行逼近,并设计了有限时间收敛模糊控制规则;提出了一种新型变论域伸缩因子,设计了基于新型伸缩因子的变论域模糊自适应滑模有限时间收敛制导律。仿真结果表明,所设计的制导律能够使导弹准确命中目标,并能够达到视线角速率有限时间收敛,且与比例制导律相比,具有更高的制导精度和更短的飞行时间。     

Maneuvering target tracking of UAV based on MN-DDPG and transfer learning

Tracking maneuvering target in real time autonomously and accurately in an uncertain environment is one of the challenging missions for unmanned aerial vehicles(UAVs).In this paper,aiming to address the control problem of maneuvering target tracking and obstacle avoidance,an online path planning approach for UAV is developed based on deep reinforcement learning.Through end-to-end learning powered by neural networks,the proposed approach can achieve the perception of the environment and continuous motion output control.This proposed approach includes:(1)A deep deterministic policy gradient(DDPG)-based control framework to provide learning and autonomous decision-making capa-bility for UAVs;(2)An improved method named MN-DDPG for introducing a type of mixed noises to assist UAV with exploring stochastic strategies for online optimal planning;and(3)An algorithm of task-decomposition and pre-training for efficient transfer learning to improve the generalization capability of UAV's control model built based on MN-DDPG.The experimental simulation results have verified that the proposed approach can achieve good self-adaptive adjustment of UAV's flight attitude in the tasks of maneuvering target tracking with a significant improvement in generalization capability and training efficiency of UAV tracking controller in uncertain environments.     

Cooperative interception with fast multiple model adaptive estimation

For the case that two pursuers intercept an evasive target, the cooperative strategies and state estimation methods taken by pursuers can seriously affect the guidance accuracy for the target, which performs a bang For the case that two pursuers intercept an evasive target, the cooperative strategies and state estimation methods taken by pursuers can seriously affect the guidance accuracy for the target, which performs a bang-bang evasive maneuver with a random switching time. Combined Fast multiple model adaptive estimation (Fast MMAE) algorithm, the cooperative guidance law takes detection configuration affecting the accuracy of interception into consideration. Introduced the detection error model related to the line-of-sight (LOS) separation angle of two interceptors, an optimal cooperative guidance law solving the optimization problem is designed to modulate the LOS separation angle to reduce the estimation error and improve the interception performance. Due to the uncertainty of the target bang-bang maneuver switching time and the effective fitting of its multi-modal motion, Fast MMAE is introduced to identify its maneuver switching time and estimate the acceleration of the target to track and intercept the target accurately. The designed cooperative optimal guidance law with Fast MMAE has better estimation ability and interception performance than the traditional guidance law and estimation method via Monte Carlo simulation.     

柴油机间歇性排气噪声自适应有源前馈控制的DSP仿真

分析了柴油机排气噪声的特征,利用自适应有源前馈系统对噪声进行控制;对间歇性噪声的控制进行了建模分析;对柴油机的排气噪声进行了有源消声的初步设计;参考柴油机实际工况,利用高速信号处理芯片TMS320F2812进行了编程及调试;通过实测数据和DSP仿真实验验证了所采用方法的有效性。     

基于坐标转换的卡尔曼交互式多模型滤波算法

为解决舰炮火控系统中在笛卡尔坐标系中测量信息的互相关性,分析了目前舰炮火控系统中所用到的坐标系及其坐标变换,在瞄准线坐标系内建立了自适应滤波的交互式多模型算法,能够充分利用跟踪传感器的量测信息,在卡尔曼滤波中具有较强的自适应能力,通过与标准交互式多模型算法的对比验证,自适应交互式多模型算法在计算精度上明显好于标准交互式多模型算法。     

海面多径环境下雷达目标俯仰角测量提取的研究与应用

在单脉冲测角体制下,由于多径回波信号的干扰,极大地影响了雷达对低空目标俯仰角的测量。通过对多路径反射环境模型分析,同时考虑镜面反射和漫反射的干扰,得出了岸、海基单脉冲雷达低空目标跟踪时俯仰角测量误差的产生原因,将传统的多目标分辨算法(C2算法)与偏差补偿技术相结合应用于低角多径环境下偏轴跟踪目标俯仰角的测量,弥补两种算法各自的不足。在给定的测量环境下对不同高度目标进行仿真,得到良好的仿真结果,表明两种算法结合使用,可较大地提高低空目标偏轴跟踪俯仰角的测量精度。并将其应用于某型雷达对掠海巡航飞行目标测量数据事后俯仰角的提取,与雷达实时输出的俯仰角测量数据相比,验证了该算法的有效性和可实施性。