相控阵雷达的系统反应时间研究

研究了相控阵雷达的系统反应时间,提出了当采用TWS和TAS两种跟踪方式时,计算相控阵雷达反应时间的公式,揭示了反应时间与搜索、跟踪和截获方式及其参数之间的关系.研究了截获参数的优化.比较了采用两种跟踪方式时的系统反应时间.实验结果说明,采用TWS跟踪方式时,反应时间主要决定于搜索帧周期和目标的速度,与目标个数无关;采用TAS跟踪方式时,反应时间主要取决于目标个数和速度,与搜索帧周期关系不大.      

一种多目标测控资源动态优化分配方法

为使有限的测控设备资源能够满足未来多目标测控能力的需求,对测控设备的初始跟踪目标分配、跟踪极限范围确定、引导信息优选和目标信息区分等关键技术展开研究,提出一套适用于多目标测控的资源动态优化分配方案,使得有限的测控设备资源得以充分利用,解决了多目标连射试验时由于测控资源数量有限和分配方案相对固定导致测控能力下降的问题,有利于规避多目标测控中测控资源短缺带来的风险。仿真结果表明,与传统固定资源分配方法相比较,该方法提高了测控资源利用率,且使引导数据切换更平稳,适应多目标测控技术的发展需求。     

铝合金板广布损伤裂纹扩展顺序的数值分析

在三排45孔铝合金板广布疲劳损伤试验基础上,对模型进行了有限元计算,系统研究了广布损伤裂纹尖端相互影响因子分布和裂纹扩展顺序规律。结果表明:裂纹尖端相互影响因子βi,当受两个裂纹参数ai和aj影响时,其随着aj的增加而增加,随着ai的增加而减小;当受三个参数ai、aj和ak影响时,其随着aj和ak的增加而增加,随着ai的增加而减小。循环数N相等时,模式I扩展最快,模式II最慢,模式III的扩展间于模式I模式II之间,但比较接近模式II,这是由于模式III下孔裂纹比较接近于模型中间位置,受模型边界的影响较小。以上结论表明,在实际工程应用中,多裂纹出现在模型中间要比靠近边界安全。     

帧差法和Mean shift算法融合的高速无人机目标跟踪

为实时跟踪高速飞行无人机,图像跟踪算法必须满足快速性和准确性要求。文章给出一个融合算法,将帧差法和 Mean shift算法的优势结合起来。2个算法平行运行,差帧法实现快速跟踪,Mean shift算法则用于对帧差法结果进行准确度修正。还利用 Kalman滤波技术对计算周期内的无人机运动位移进行补偿,进一步提高实时跟踪的准确性,并给出 Matlab仿真例子验证本文方法的有效性。     

基于变分贝叶斯的星载雷达非线性滤波

星载雷达由于其探测范围广、距离远、全天候等优点,在预警防御系统中占有十分重要的地位。然而,由于观测平台的高速运动以及摄动干扰、传感器观测非线性等问题,使得星载雷达目标高精度跟踪带来严峻挑战。针对星载雷达非线性状态估计问题,采用一种基于变分贝叶斯的非线性滤波方法,该方法通过将非线性状态估计问题转化为优化问题,通过迭代优化获得了闭环解析解。此外,针对坐标变换中俯仰角量测缺失问题,提出了一种基于先验目标高度的俯仰角估计方法。通过数值仿真,验证了所提方法较传统非线性滤波方法,如扩展卡尔曼滤波、不敏卡尔曼滤波、转换量测卡尔曼滤波,具有更好的估计精度。     

A reduced order model for coupled mode cascade flutter analysis

A Reduced Order Model(ROM) based analysis method for turbomachinery cascade coupled mode flutter is presented in this paper. The unsteady aerodynamic model is established by a system identification technique combined with a set of Aerodynamic Influence Coefficients(AIC). Subsequently, the aerodynamic model is encoded into the state space and then coupled with the structural dynamic equations, resulting in a ROM of the cascade aeroelasticity. The cascade flutter can be determined by solving the e...     

二阶系统输出响应及输入信号恢复的仿真

介绍用数学方法推导出二阶系统信号恢复的计算方法,并用算法语言在计算机上模拟出当其输入信号为标准半正弦波进的输出信号,以及当输出信号为计算出的信号时模拟恢复出原输入信号,并讨论了在该算法的数学推导及模拟实验的基础上恢复动态信号的可能性。     

l1-based calibration of POD-Galerkin models of two-dimensional unsteady flows

This paper discusses a physics-informed methodology aimed at reconstructing efficiently the fluid state of a system. Herein, the generation of an accurate reduced order model of two-dimensional unsteady flows from data leverages on sparsity-promoting statistical learning techniques. The cornerstone of the approach is l₁ regularised regression, resulting in sparsely-connected models where only the important quadratic interactions between modes are retained. The original dynamical behaviour is reproduced at low computational costs, as few quadratic interactions need to be evaluated. The approach has two key features. First, interactions are selected systematically as a solution of a convex optimisation problem and no a priori assumptions on the physics of the flow are required. Second, the presence of a regularisation term improves the predictive performance of the original model, generally affected by noise and poor data quality. Test cases are for two-dimensional lid-driven cavity flows, at three values of the Reynolds number for which the motion is chaotic and energy interactions are scattered across the spectrum. It is found that: (A) the sparsification generates models maintaining the original accuracy level but with a lower number of active coefficients; this becomes more pronounced for increasing Reynolds numbers suggesting that extension of these techniques to real-life flow configurations is possible; (B) sparse models maintain a good temporal stability for predictions. The methodology is ready for more complex applications without modifications of the underlying theory, and the integration into a cyber-physical model is feasible.     

跟瞄激光雷达扫描图像的实时滤波算法

为实现跟瞄激光雷达的高精度实时跟瞄,对雷达三维信息实时滤波算法进行了研究。对方位信息,用卡尔曼滤波算法滤波,在保证实时性的同时获得了较好的滤波效果;对距离信息,用去边缘点3×3小窗口中值滤波算法,实现了对距离信息的准实时性滤波。研究表明:该信息处理滤波算法既有优良的滤波性能,又能保证实时性,可提高测角和测距精度,改善整机的实时跟踪性能。     

基于JPDA-MPC的单站纯方位多目标跟踪

静止单站对多目标进行纯方位跟踪时,若在直角坐标系下建立跟踪模型并使用最近邻标准滤波器(NNSF)进行关联和滤波,结果通常不稳定且容易发散。针对此问题,提出将修正的极坐标系(MPC)下的扩展Kalman滤波算法及联合概率数据互联关联(JPDA)算法相结合。与NNSF-MPC算法的仿真对比试验表明,JPDA-MPC算法可以提高跟踪过程的稳定性,且具有更小的跟踪误差。