海上机动目标的天基观测体系的观测预判算法

Observation-Prejudged Algorithm of Space-Based Observation Systems-of-Systems for Moving Marine Objects

为了适应海上机动目标的天基观测所具有的时间敏感性、不完全信息和复杂环境等三大特征,并克服这些特征给观测造成的困难,提出了一种天基观测体系来观测海上机动目标.在天基观测体系中,先由观测范围大的电子侦察卫星确认目标是否存在,再由观测精度高的光学成像卫星对目标查证识别,从而完成观测任务.设计了一种光学成像卫星观测可行性预判算法,天基观测体系可以根据此算法提前判断光学成像卫星能否直接观测目标或者能否通过侧摆来扩大观测范围进而观测到目标,并预估目标被光学成像卫星观测的具体时刻.若确定光学成像卫星侧摆后能够观测到目标则令其侧摆,既能增加体系完成观测任务的机会,又能避免频繁侧摆对卫星造成不利影响.天基观测体系的预判依赖于一种针对海上机动目标的位置预测算法,该算法采用最小二乘法对电子侦察卫星采集到的目标时空轨迹数据进行空间直线拟合,以拟合直线作为目标的预测航迹,结合目标的预测速度推理目标在未来时刻的位置坐标.采用基于Agent的建模与仿真方法在体系效能分析仿真平台上对天基观测体系进行了建模仿真,考察了体系和相关算法应对沿不同航迹行动的目标效果.仿真结果显示,观测预判算法能够使天基观测体系完成观测任务的次数至少增加200%,且算法准确率、精度和召回率都在95%以上.

Space-based observation of a moving marine object(MMO)has three characteristics,namely,time sensitivity,incomplete information,and complex experiment.To overcome the difficulties caused by these characteristics,the space-based observation systems-of-systems(SBOSoS)was developed to observe the MMO.For the SBOSoS to fulfill the observation task,first the electronic reconnaissance satellite detects the MMO using its vast-range observation device and thereafter,the optical imaging satellite(OIS)identifies or classifies the MMO using its high-precision imaging device.A prejudged algorithm for observation feasibility of optical imaging satellite(PAOFO)was designed to help the SBOSoS prejudge whether the OIS can observe the MMO directly or after the OIS has enlarged its observation range by swinging.The PAOFO could also forecast the time that the MMO was observed by the OIS.If the OIS was confirmed to observe the MMO with swing,then it was assumed to swing.With the help of the PAOFO,the SBOSoS should have more opportunities to fulfill the observation task and the OIS should be able to prevent damage caused by frequent swings.The prejudgment by the SBOSoS needs to rely on the location prediction algorithm of moving marine objects(PPAM).The PPAM uses the least squares method to fit a linear equation to the trajectory data of the MMO,which will serve as the predicted course of the MMO.Hence,the location of the MMO at a certain time in the future may be computed according to its predicted course and speed.A system-of-systems effectiveness analysis simulation software was applied to model and simulate the SBOSoS with agent-based modeling and simulation method.Thus,how the SBOSoS and accompanying algorithms handle the MMO with three different courses was investigated through several simulations.The results of the simulations indicated that the PAOFO enables the SBOSoS to increase the success frequency of its observation tasks by at least 200%.Moreover,the accuracy,precision,and recall of the PAOFO exceeded 95%.