基于能量管理的横向机动弹道优化设计

为实现小射程能量的有效利用,增强导弹的突防能力和禁飞区规避能力,提出了一种基于能量管理的横向机动弹道设计与优化方法.该方法通过初始离面角使弹道一级偏离传统射面,后面级再修正射面以命中目标.在建立能量管理方程、初始离面角及横向转弯角的解析计算模型的基础上,迭代解析计算机动角的初值;采用遗传算法对机动角及弹道程序进行优化,得到了最优解.仿真结果表明,该方法在满足导弹能量管理的条件下实现了导弹的横向机动,可有效提高弹道导弹的突防能力,优化算法简单可行,收敛效果好.     

浅析弹道导弹突防导弹防御系统

根据美国导弹防御系统（NMD）的防御特点，对弹道导弹突防的战略技术进行简要评估，分析了弹道导弹突防采用不同弹头、释放有源或无源干扰物、隐身和反探测、助推段机动及旋转导弹等技术。     

高突防能力导弹方案设计

随着导弹防御技术的快速发展,突防能力在现代导弹设计中显得越来越重要。为提高导弹对反导系统的突防能力,提出了一种利用速燃发动机和跨大气层跳跃式弹道实现突防的导弹设计方案,阐述了该方案提高突防能力的原理及其带来的技术挑战。采用该方案改进了某二级固体导弹,并在Matlab-Simulink中进行了弹道仿真,结果表明该方案是可行的。所提出的设计方案对导弹设计和改型有一定的参考价值。     

防空导弹防御系统中的TBM突防能力研究

建立了防空导弹弹道数学模型并应用排队论理论建立了TBM突防概率模型。通过仿真计算，深入定量地探讨了TBM的进入密度、防御武器数量和火力单元拦截概率等因素对TBM突防能力的影响，在此基础上，从导弹技术与战术运用方面，针对防空导弹的防御，进一步提高TBM突防能力的对策和途径。     

导弹靶弹弹道机动变轨通用控制指令设计

导弹进行一定强度的机动飞行,就能够提高突防能力,因而,在军事训练中需要具有末端机动变轨能力的靶弹.针对靶弹机动变轨弹道的设计问题,提出变轨通用控制指令设计形式,利用此设计可使靶弹位移与过载指令控制信号协调配合,控制靶弹实现跃升机动、蛇行机动、摆式机动和螺旋机动等变轨形式.通过仿真证明,此设计的变轨弹道通用控制指令,可以满足靶弹跃升机动、蛇行机动、摆式机动和螺旋机动等各种变轨形式的弹道设计要求.     

基于蒙特卡洛法的反舰导弹末端机动突防效果研究

为了比较反舰导弹在不同的末端机动方式下,当有舰空导弹拦截时哪种突防效果更好,从工程应用的角度出发,考虑反舰导弹受多种因素(包括干扰、建模误差、海情、不确定性等)的影响,并同时考虑舰空导弹的前置角约束和死区约束,建立了反舰导弹与舰空导弹的对抗模型。其中,反舰导弹采用的是基于过载控制方法设计的全弹道仿真模型,舰空导弹则采用三阶简化模型。根据舰空导弹初始拦截位置的不同,设定不同的初始仿真条件,在计算机上进行多次打靶,应用蒙特卡洛法分别计算反舰导弹在不同机动方式下的突防概率。仿真结果表明,在有舰空导弹拦截的情况下,反舰导弹进行螺旋机动时,其突防效果最好,摆式机动次之,然后是纵向蛇行机动,最后是航向蛇行机动,而突防效果最差的则是反舰导弹不进行末端机动。     

基于反预警的反拦截中段规避突防策略

为了充分挖掘多脉冲机动突防的潜力,提高弹道导弹中段机动突防能力,提出一种基于反预警的反拦截中段规避突防策略。首先,分别以脉冲点火点及点火间隔为搜索节点与步长,视敌方拦截系统为威胁源并转化为航迹规划中的约束条件,将多脉冲弹道的设计问题转化成无人机避障航迹的规划问题。然后,在综合考虑敌方探测系统延迟和拦截系统部署及性能的基础上,选取最优的脉冲点火参数。最后,研究了脉冲增量和探测系统延迟对多脉冲规划的影响。仿真结果表明:所提出的突防策略通过多脉冲机动增加敌方预测误差,使其不能收敛与准确预警,当敌方的预测误差收敛且准确预警时,导弹却处于其拦截范围之外,无法进行拦截;能根据获取的最新战场信息,在线下60s内设计出一条多脉冲突防弹道。此外,还能根据任务的需求,提高(降低)导弹的飞行高度、平均飞行速度,缩短(增加)20%~35%的飞行时间。     

打击复杂地形目标的导弹再入机动弹道设计

建立了再入机动弹道数学模型，给出了气动力系数为速度、迎角、高度的函数拟合式，进行了最佳再入机动弹道设计和仿真计算。结果表明，数学模型正确，计算方法可行，利用再入机动弹道技术可有效地打击复杂地形目标、提高导弹的作战效能和突防能力。     

面-面火箭弹增程与突防研究

阐述了面-火箭弹增程及突防设计原理,建立了导弹弹道仿真模型.通过飞行数值仿真比较了常规火箭弹和滑翔增程导弹的弹道特性,验证了面一面火箭弹通过滑翔增程的可行性.重点研究了滑翔增程弹分导式多弹头突防的可行性及分弹头弹道特性,并分析了该突防方案的突防概率,对今后面-面战术导弹研究有着重要的意义.     

反舰导弹对舰空导弹的机动突防模型研究

结合现代化海战中反舰导弹与舰空导弹的对抗过程,以反舰导弹蛇行机动为例,分析了反舰导弹对舰空导弹的突防规避策略,建立反舰导弹"蛇行机动"的突防模型。通过仿真计算,对比分析了反舰导弹"蛇行机动"和传统导弹攻击的优劣,指出了"蛇行机动"对于提高反舰导弹突防概率的必要性。     

基于自适应IMM的高超声速飞行器轨迹预测

为了给基于预测命中点法的高超声速飞行器中制导拦截提供先验知识,提出高超声速飞行器的轨迹预测方法。首先,给出高超声速环境下与目标姿态近似线性的气动参数;其次,针对气动参数作控制量的运动模型,设计自适应交互多模型（IMM）跟踪算法,并进行性能有效性验证;然后,根据气动参数特性和目标假设机动方式,设计基于最小二乘拟合的轨迹预测方法。通过对目标轨迹进行跟踪和预测仿真,预测100 s的位置误差均小于5 km,速度误差均小于100 m/s,结果表明基于自适应IMM的轨迹预测方法对有规律机动的目标进行轨迹预测,效果良好。     

Trajectory prediction in pipeline form for intercepting hypersonic gliding vehicles based on LSTM

The interception problem of Hypersonic Gliding Vehicles (HGVs) has been an important aspect of missile defense systems. In order to provide interceptors with accurate information of target trajectory, a model based on an improved Long Short-Time Memory (LSTM) network for trajectory prediction pipeline is proposed for the interception of a skip gliding hypersonic target. Firstly, for trajectory prediction required by intercepting guidance laws, the altitude, velocity and velocity direction of the target are formulated in the form of analytic functions, consisting of linear decay terms and amplitude decay sinusoidal terms. Then, the dynamic characteristics of the model parameters are analyzed, and the target trajectory prediction pipeline is proposed with the prediction error considered. Finally, an improved LSTM network is designed to estimate parameters in a dynamically-updated manner, and estimation results are used for the calculation of the final trajectory prediction pipeline. The proposed prediction algorithm provides information on the velocity vector for midcourse guidance with the effect of prediction errors on interception taken into account. Simulation is conducted and the results show the high accuracy of the algorithm in HGVs’ trajectory prediction which is conducive to increasing the interception success rate.     

In-Flight Alignment and Calibration of Inertial Measurement Units?Part II: Experimental Results

This is the second part of a two-part paper which summarizes work pursued by the author in 1967 [2]. The paper describes the application of minimum-variance estimation techniques for in-flight alignment and calibration of an inertial measurement unit (IMU) relative to another IMU and/or some other reference. The first paper [1] formulates the problem, and this paper reports numerical results and analyses. The approach taken is to cast the problem into the framework of Kalman-Bucy estimation theory, where velocity and position differences between the two IMU's are used as observations and the IMU parameters of interest become part of the state vector. Instrument quantization and computer roundoff errors are considered as measurement noise, and environmental induced random accelerations are considered as state noise. In this paper, numerical results for three important IMU error parameter configurations are presented and discussed. The main results of the paper determine the effects of state and observation noise levels and the nominal trajectory on the identifications of the errors for these configurations. A discussion of the minimum number of trajectory maneuvers and of the optimal trajectory maneuvering is given.     

Trajectory Estimation with Multi-range-rate System Based on Sparse Representation and Spline Model Optimization

The classic state methods for trajectory estimation in boost phase with multi-range-rate system include method of point-by-point manner and that of spline-model-based manner. Both are deficient in terms of model-approximation accuracy and systematic error determination thus resulting in the estimation errors well beyond the requirements, especially, concerning the maneuvering trajectory. This article proposes a new high-precision estimation approach based on the residual error analysis. The residual error comprises three components, i. e. systematic error, model truncation error and random error. The approach realizes self-adaptive estimation of systematic errors in measurements following the theory of sparse representation of signals to minimize the low-frequency components of residual errors. By taking median- and high-frequency components as indexes, the spline model-approximation is improved by optimizing node sequence of the spline function and the weight selection for data fusion through iteration. Simulation has validated the performances of the proposed method.     

基于改进粒子群算法辨识Volterra级数的目标机动轨迹预测

目标机动轨迹预测是空战态势感知和目标威胁评估的重要前提。针对传统目标机动轨迹预测模型复杂度大、预测精度低等问题，结合目标机动轨迹时间序列的混沌特性，提出一种基于相空间重构理论和Volterra泛函级数的目标机动轨迹预测模型。该模型首先采用0-1检测法验证了目标机动轨迹时间序列具有混沌特性；其次，利用C-C法确定嵌入维数和时间延迟，对目标机动轨迹时间序列进行了相空间重构；然后，引入Volterra泛函级数预测模型，为了克服高阶Volterra核函数求解复杂的难题，提出一种混沌变异自适应粒子群算法，构建一种基于改进粒子群算法辨识的Volterra级数预测模型，并将其应用于目标机动轨迹预测；最后，将所提算法与卡尔曼滤波算法以及机器学习算法进行单步和多步预测对比，同时将改进粒子群算法与其他智能算法进行性能比较。仿真结果表明：所提预测模型具有良好的单步和多步预测性能，改进的粒子群算法具有参数辨识精度高、收敛速度快的优点。     

民用航空器四维航迹预测技术综述

民用航空器四维航迹预测是保障飞行安全、提升运行效率、缓解航班延误、倡导绿色飞行的有效支撑和重要保证.四维航迹预测的研究集中于如下领域:预测结构与流程、预测模型与方法、误差分析与精度提升,其中航迹预测模型与方法是核心,主要包括混合估计模型、质点运动模型与机器学习方法.最后,总结与提炼开展民用航空器四维航迹预测研究的思路和热点,并相应指出了未来的研究方向.     

A Nonlinear Tracker Using Attitude Measurements

The subject of this paper involves tracking the present position of a maneuvering aircraft as well as predicting its future position. A tracking filter is developed that uses aircraft attitude angles (yaw, pitch, roll) in addition to the usual radar measurements. Computer simulation of tracker performance when tracking violently maneuvering aircraft indicates that a dramatic improvement is obtained by using attitude information. The approach taken is to develop a 12-or 15-state extended Kalman filter that models both translational and rotational degrees of freedom. By measuring and estimating attitude it is possible to approximately determine the magnitude and direction of the force system acting on the vehicle and therefore determine vehicle linear acceleration. Knowledge of acceleration is then used to improve the estimate of present and future position of the vehicle being tracked. Simulation of a T-38 aircraft performing a 5 g turn indicates that the new tracker produces maximum trajectory prediction errors that are 36 percent of the errors experienced by more conventional trackers.     

自主机动条件下的实时定轨方法

中继卫星在跟踪自主机动用户目标时,由于机动轨道未知,需要利用中继卫星下传的星载GNSS(Global Navigations Satellite System,全球导航卫星系统)数据进行实时轨道确定与预报,为中继卫星跟踪提供实时的引导信息,以方便中继卫星快速捕获目标和连续稳定跟踪。针对该类用户目标的任务需求,讨论了基于星载GNSS数据自主机动条件下的实时定轨方法,建立了连续推力机动力学模型。以某一型号卫星的实测数据进行分析验证,并对轨道机动进行辨识,计算的机动加速度和机动时间与试验单位提供的结果一致。针对卫星不同机动情况,5min的观测数据定轨预报10min的弧段,最大位置误差小于8km,可以为中继卫星快速捕获提供高精度的引导信息。     

基于样条拟合和双向滤波的助推段弹道估计

三次B样条拟合在助推段弹道估计中应用广泛,但存在弹道两端点邻域估计误差过大的问题.通过对B样条基函数矩阵的特性进行分析,发现其原因为端点邻域估计时能利用的有效观测数据最少.因此,提出一种基于样条拟合和双向滤波相结合的弹道估计策略：首先将双星观测数据利用无迹变换转换为等效位置观测;然后利用三次B样条拟合弹道;最后基于一种自适应卡尔曼滤波器,采用双向滤波策略改善样条拟合的端点估计精度.仿真结果表明：组合方法使样条拟合的端点估计误差减少40％,同时使估计弹道更平滑.此结果满足实时性要求.