高超声速滑翔目标自适应跟踪方法

针对机动模式复杂多变的高超声速滑翔目标跟踪问题，提出了一种机动频率自适应跟踪方法。采用介于常速度和常加速度模型之间的Singer模型来表征目标气动力加速度的变化，从而建立跟踪系统的状态方程。根据地基雷达量测量获得系统的量测方程，鉴于距离和角度信息的量级相差较大将其由球形量测量转换为位置量测量。为了适应高超声速滑翔目标灵活多样的机动模式，基于正交性原理和无迹卡尔曼滤波算法实现了Singer模型中机动频率参数的自适应。利用滤波信息计算得到能够反映状态模型误差大小的调整因子，用于放大Singer模型中的机动频率，进而调整状态方程的过程噪声以降低模型误差。通过对2种典型机动轨迹的跟踪仿真，并与交互式多模型等方法进行比较，结果表明所提方法的跟踪精度高、计算量小，能够较好地适应阶跃机动和连续幅值变化的机动。     

基于自适应反演滑模的末制导律设计

针对三维导弹-目标相对运动模型,结合反演控制、滑模控制和自适应技术,设计了一种新的自适应反演滑模末制导律。针对目标机动加速度上界难以获取的问题,将目标机动加速度视作模型的干扰,设计了一种自适应律对其进行在线估计,并将估计值补偿到制导律中。运用李亚普诺夫稳定性理论证明了系统的全局渐进稳定性和误差的收敛性。仿真结果证明了所设计的自适应反演滑模末制导律对机动目标的鲁棒性和有效性。     

一种基于径向加速度的Singer-EKF机动目标跟踪算法

针对雷达均不能提供目标加速度信息,在目标机动时会出现跟踪精度差甚至跟踪发散的问题,提出一种基于径向加速度的Singer-EKF算法。该算法在信号处理阶段利用Radon-Ambiguity变换（RAT）估计出目标的径向加速度,并通过坐标转换将其引入量测向量中,然后采用基于Singer模型的扩展卡尔曼滤波（EKF）算法实现机动目标的跟踪。仿真验证了该方法的有效性,并与传统的不带径向加速度的扩展卡尔曼滤波（EKF）方法进行了比较,结果表明该方法在径向距离、位置、加速度和速度估计精度方面都有所提高。     

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。     

一种IRST双机协同被动探测机动目标定位新方法

针对红外搜索跟踪系统（IRST）双机协同被动探测定位作战使用中，机动目标建模与实际运动失配造成定位误差偏大的问题，研究了一种基于曲线模型的自适应滤波新方法。该方法改进了传统方法根据方向角估计转弯率以及基于帧间插分线加速度估计切向加速度的思路，将转弯率及线加速度联合作为状态变量进行了状态扩维，并推导了扩维后的过程噪声协方差表达式，在缓解传统两层滤波结构带来的计算量大问题外，也提高了切向加速度的估计精度。另外基于反正切函数的值域，结合方向角在四象限间的转移关系，优化了方向角的设计。通过IRST双机协同仿真实例，验证了所提方法对机动目标的适应性更强、目标定位精度更高。     

精密转台系统非线性动态自适应控制器设计

提出了一种用于精密转台平滑鲁棒自适应控制器。通过基于σ改进方案的自适应律估计得到未知摩擦参数和非线性项的常值上界,并且利用一种平滑预测算法来改进用于估计不可测摩擦状态的双观测器。为了抑制不确定非线性项,加入了无抖振滑模控制项。通过Lyapunov方法证明了系统的位置跟踪误差是一致最终有界的。仿真研究表明了该控制方案的有效性。     

机动目标“当前”统计模型与自适应跟踪算法

本文提出机动目标“当前”统计模型的概念并建议用修正的瑞利-马尔科夫过程描述目标随机加速机动的统计特性。文中指出了在机动目标运动模型中状态（机动加速度）估值与状态噪声之间的内在联系。在此基础上提出了具有机动加速度均值及方差自适应的卡尔曼滤波算法。对一维和三维的情形进行了计算机模拟。计算结果表明,在仅对目标位置进行观测的情况下,这类自适应估值算法无论对高度机动或无机动的目标均可绘出较好的位置、速度及加速度估值。     

改进的MMPHD机动目标跟踪方法

基于序列蒙特卡罗方法的经典多模概率假设密度滤波方法及其各种衍生方法,在预测过程中依据多个并行的状态转移模型,通过将大量粒子散布到下一时刻目标所有可能出现的状态空间实现目标状态的捕获,造成计算量大、目标跟踪精度差。为此,提出一种改进的多模粒子概率假设密度机动目标跟踪方法。该方法利用最新量测信息估计目标运动模型概率及模型参数,并将估计得到的目标模型应用到粒子概率假设密度滤波方法的预测过程中生成预测粒子,从而将大部分粒子聚合在目标最可能出现的状态空间邻域中,实现粒子的有效利用。数值仿真表明,所提方法不仅显著地减少了目标丢失个数,而且提高了目标跟踪精度。     

常增益变采样率自适应滤波

作者曾给出一种跟踪飞机机动的自适应滤波,采用直角坐标系中的9维状态量,利用最优检测统计量探测目标机动,并用估计到的机动加速度修正目标的预报值。 本文将在文献[1]的基础上,提出两种简化自适应滤波。其一,采用两套直角坐标系中的9维卡尔曼滤波,其中的一套滤波用于取代最优检测统计量,完成对目标机动的探测和估计的功能;其二,采用三通道解偶的常增益变采样率自适应滤波。     

基于全驱系统方法的制导控制一体化设计

针对滑行转弯导弹拦截高机动目标的制导控制系统设计问题,提出了一种基于全驱系统和反步法相结合的制导控制一体化设计方案。首先,考虑目标的机动特性,建立了二阶严格反馈的制导控制一体化非线性模型,消除了中间过程量,简化了建模和计算过程。其次,设计降阶状态观测器,对包含目标未知机动、系统未建模部分、气动参数等扰动进行估计,并在控制器中进行前馈补偿。随后,基于高阶全驱系统方法,结合反步控制方法,设计具有拦截角度约束的制导控制一体化方案,使用极点配置方法,得到闭环系统控制系数矩阵,满足期望的系统性能。引入Lyapunov函数,证明闭环系统稳定性。最后,通过不同场景和对比仿真试验,证明了所设计的制导控制一体化方案的有效性、优越性和鲁棒性。     

Modified input estimation technique using pseudoresiduals

An adaptive tracking filter for maneuvering targets is proposed using modified input estimation technique. Pseudoresiduals are defined using measurements and the velocity estimate at the hypothesized maneuver onset time. With the pseudoresiduals and a new target model representing transitions of nominal accelerations, a new input estimation method for tracking a maneuvering target is derived. Since the proposed detection technique is more sensitive to maneuvers than previous work, the shorter window length can be employed to detect and compensate target maneuvers. Also shown is that the tracking performance of the proposed filter is similar to that of interacting multiple model method (IMM) with 3 models, while computational loads of our method are drastically reduced     

Interacting acceleration compensation algorithm for trackingmaneuvering targets

The two-stage Kalman estimator has been studied for state estimation in the presence of random bias and applied to the tracking of maneuvering targets by treating the target acceleration as a bias vector. Since the target acceleration is considered a bias, the first stage contains a constant velocity motion model and estimates the target position and velocity, while the second stage estimates the target acceleration when a maneuver is detected, the acceleration estimate is used to correct the estimates of the first stage. The interacting acceleration compensation (IAC) algorithm is proposed to overcome the requirement of explicit maneuver detection of the two-stage estimator. The IAC algorithm is viewed as a two-stage estimator having two acceleration models: the zero acceleration of the constant velocity model and a constant acceleration model. The interacting multiple model (IMM) algorithm is used to compute the acceleration estimates that compensate the estimate of the constant velocity filter. Simulation results indicate the tracking performance of the IAC algorithm approaches that of a comparative IMM algorithm while requiring approximately 50% of the computations     

考虑驾驶仪动态性能的指令滤波反演制导律

针对攻击机动目标的制导问题,设计了一种考虑自动驾驶仪性能、输入项约束的指令滤波反演制导律。首先,基于三维空间内弹目相对运动模型,采用反演递推方式设计制导律。针对传统反演控制存在的"微分膨胀"问题,引入指令滤波器对虚拟量进行过滤计算。考虑硬件计算能力的约束,引入自动驾驶仪二阶动力学模型减少控制过程延迟,并利用饱和函数和低通滤波器对输入项进行约束。此外,针对机动目标设计了一种扩张状态观测器来获取其加速度。通过Lyapunov理论证明了所设计闭环制导系统的稳定性。通过仿真实验验证了该制导律相有效性及优越性。     

Saturated super-twisting sliding mode missile guidance

This paper concentrates on developing a missile terminal guidance law against a highly maneuvering target whose maneuvering acceleration is very close to that of the missile or even exceeds the missile normal acceleration in a finite period of time. A new saturated super-twisting algorithm is proposed and applied to the design of missile guidance law. The proposed algorithm has the advantages of simple structure, easy parameter tuning rules and a full utilization of the limit control input. The designed saturated super-twisting sliding mode guidance law is then employed in a missile guidance system. Simulation and its superior performance against strong maneuvering targets is demonstrated.     

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.     

自寻的导弹攻击机动目标的最优制导规律的研究及实现

提出一种适用于红外和雷达自寻的制导导弹的适应性强、制导精度高、易实现的最优制导规律。为解决工程实现的关键问题,提出了目标机动加速度模型。根据该模型并利用导弹导引头的AGC信号或雷达测距信号,给出了目标机动加速度、导弹与目标相对距离和距离变化率的估计算法。     

Suboptimal filter design with pseudomeasurements for targettracking

A suboptimal Kalman filter design method is presented for the problem of tracking a maneuvering target. The design method is essentially based on linear target dynamics and linear-like structured measurements called pseudomeasurements. The pseudomeasurements are obtained by manipulating the original nonlinear measurements algebraically. The resulting filter has computational advantages over other filters with similar performance. Also, a variant of the Berg model is proposed as a target acceleration model under the assumption of a coordinated turn maneuver. The proposed model is consistent with the underlying assumption. Monte Carlo computer simulation results are included to demonstrate the effectiveness of the proposed suboptimal filter associated with the target acceleration model     

三维空间中目标机动加速度的估值问题

建立了描述目标在三维空间中进行切向与法向机动的非线性状态模型。目标切向与法向机动加速度的幅值表示为修正的瑞利-马尔可夫随机过程;法向加速度的方向角则假定在2π区间内具有均匀的概率密度。在仅有含噪声位置观察数据的情况下,发展了一种推广的卡尔曼滤波和自适应算法,并由此获得一种机动目标切向与法向加速度估值的直接方法。提供了某些计算结果以证实方法的有效性。