Three-dimensional cooperative guidance strategy and guidance law for intercepting highly maneuvering target

Cooperative interception of the target with strong maneuverability by multiple missiles with weak maneuverability in the three-dimensional nonlinear model is studied. Firstly, the three-dimensional nonlinear model of cooperative guidance is established. The three-dimensional reachable region is represented composed of lateral acceleration and longitudinal acceleration in the two-dimensional coordinate system. Secondly, the problem of the multiple missile's reachable coverage area is transformed into the problem of cooperative coverage. A cooperative coverage strategy is proposed and an algorithm for quickly calculating the number of required missiles is designed. Then, the guidance law based on the cooperative coverage strategy is proposed, and it is proved that cooperative interception of the target can be achieved under the acceleration limit. Moreover, the relations among the number of missiles, the initial array position of terminal guidance and the coverage area of the target’s large maneuver are analyzed. The dynamic adjustment strategy of guidance parameters is proposed to reduce the guidance error. Finally, simulation results show that multiple missiles with low maneuverability can achieve effective interception of target with strong maneuverability through the proposed cooperative strategy and cooperative guidance method.     

用差分法处理相关性测量数据方法探讨

当测量参数（或称测量元素）具有强相关性时,运用测量求差法解算测量结果,能消除相关性误差因素的影响,获得高精度测量结果,如电影望远镜同帧画幅测量脱靶量.基于此,运用测量方法和数学手段构建一个虚拟的元素相关测量系统,以消除相关性误差因素的影响,同样能获得理想结果.用多台测速雷达组成的系统,可使火炮弹丸空间坐标的测量精度达到毫米量级,从而满足多种火炮立靶密集度的测量精度要求.     

基于PCA-MPSO-ELM的空战目标威胁评估

目标威胁评估是空战对抗过程中的关键环节。由于影响空战目标威胁评估的因素复杂多样，且指标之间存在相关性，导致传统的评估算法无法得到准确客观的评估结果。由此，提出了一种基于主成分分析法和改进粒子群算法优化的极限学习机（PCA-MPSO-ELM）的目标威胁评估算法。首先，综合分析了影响目标威胁程度的指标，利用主成分分析法对原始评估指标进行线性变化处理得到综合变量，消除了评估指标之间的相关性，实现了对评估数据的降维；在此基础上，构建ELM神经网络并利用改进的粒子群算法优化极限学习机的输入权值和阈值，提高了目标威胁评估模型的精度。最后，在空战训练测量仪中选取空战对抗数据，利用威胁指数法构造了目标威胁评估样本数据，通过仿真实验分析了PCA-MPSO-ELM算法的精度和实时性，结果表明所提算法可以快速准确地进行空战目标威胁评估。     

高速平台下动目标高分辨成像方法研究

高速平台对地面强散射移动目标或者海面舰船目标进行合成孔径雷达成像（SAR）时，存在两方面问题：一是传统SAR匀速直线模型已不适应高速平台自身高动态运动特征；二是目标的非合作运动一方面会引起图像散焦，另一方面动目标在地距图中的位置会产生较大偏移。针对这两个问题，首先在匀加速度模型频域相位滤波算法下，推导出了精确的斜地投影关系以及近似的反投影关系，同时给出了基于惯性组合导航（INS）的平台运动补偿方法，最后结合自聚焦技术，完成对舰船目标的聚焦并得到以目标为图像中心的地距图。     

An optimal one-way cooperative strategy for two defenders against an attacking missile

This paper investigates a cooperative strategy for protecting an aerial target.The problem is solved as a game among four players(a target,two defenders,and a missile).In this scenario,the target launches two defenders(defender-1 and defender-2)simultaneously,to establish a oneway cooperation system(OCS)against an attacking missile.A new optimal evasion strategy for the target is also derived.During the engagement,the target takes into account the reaction of the attacking missile,and guides defender-1 to the interception point by receiving information from defender-1.Depending on the control effort of the target,defender-2 can choose appropriate launch conditions and use very limited maneuvering capability to intercept the missile.For adversaries with first-order dynamics,simulation results show that the OCS allows two defenders to intercept the missile.During the engagement,even if one defender or communication channel is broken,the OCS still allows an interception to be made,thus increasing the target’s survivability.     

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。     

Motion prediction of an uncontrolled space target

Capturing an uncontrolled space target is a tremendously challenging research topic. Target capture by a space robot can be well planned according to predicted motion of the target. In this paper, motion prediction of an uncontrolled space target is studied and a motion prediction algorithm is proposed. In the proposed algorithm, firstly a method for identifying the parameters of motion state and inertial property of the target is established; and then through substituting the identified parameters into the dynamic equations of the target, the motion of the target can be predicted as the solution of the equations. In the identification of the parameters, the unscented Kalman filter (UKF) is applied. In order to support the UKF, a method for estimating noise level of the observation data is developed, so our motion prediction algorithm is noise adaptive. A practical convergent criterion is also designed to determine the time when the estimated result of the UKF is accurate enough, such that the predicted motion is credible enough. After that, the accuracy of the prediction is further improved by an optimization method. In the end of this paper, numerical simulations are done to verify the validity of the proposed motion prediction algorithm. Simulation results indicate that the proposed algorithm is able to predict the motion of the target precisely.     

某异形卷弧翼弹的蒙特卡罗计算机模拟打靶

卷弧翼弹在实际的训练或作战过程中,由于系统干扰或误差的影响,会存在弹道偏差。蒙特卡罗方法(MCM)利用计算机产生的随机数模拟实际系统中的随机变量,通过随机变量参与的系统的大量仿真,可以得到系统的数学期望意义下的解。通过蒙特卡罗计算机模拟打靶,得到了卷弧翼弹的弹着点散布及命中概率,从结果看,弹着点符合正态分布,其命中概率基本满足实际要求。蒙特卡罗计算机模拟打靶方法对于指导训练或作战有一定的指导意义。     

分布式MIMO雷达欺骗干扰抑制算法研究

从信号级协同对抗欺骗干扰出发,直接利用各节点雷达回波信号的复包络信息,建立相关检测融合算法实现协同抗干扰。首先展开对分布式MIMO雷达信号相参性的研究,并给出了回波信号间的独立性条件。依据目标空间散射特性的差异,提出了一种信号级协同对抗欺骗式假目标的算法。该算法根据真假目标回波相关性的差异,利用多脉冲回波数据得到相关系数估计值并进行相关性检验,实现对目标的有效鉴别。通过仿真验证了算法的有效性,并对算法性能进行仿真分析。     

基于速率先验信息的固定单站仅测角目标运动分析

针对固定单站无源定位中仅利用角度对匀速运动目标定位跟踪问题,将速率信息视为先验约束,研究并提出基于伪线性估计和加权伪线性估计的目标运动分析算法.仿真实验表明,固定单站无源定位系统在速率先验信息条件下可以通过仅测角实现对匀速运动目标的定位跟踪.