基于软件在环(SIL)的导弹末制导评价

E. H. Kapeel, M. Abozied, A. Kamel, H. Hendy
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引用次数: 2

摘要

导弹的拦截能力特别依赖于导弹制导处理器中实现的制导律。比例导航自20世纪首次使用以来,大多数导弹都采用比例导航作为主制导律。PN倾向于通过调整导弹的转向速率与视距速率成比例来抵消视距(LOS)角速率。随着航空工业的巨大进步,PN已不足以满足高机动目标。基于数学的先进制导律的发展一直是该领域研究人员关注的问题,从那时起,许多先进制导律被提出并进行了测试。增广PN (Augmented PN, APN)是一种能够与高机动目标相互作用的先进制导律,它通过在线估计目标加速度项来增大原PN。在本研究中,利用Matlab®Simulink™对APN仿真和二维导弹-目标拦截几何图形进行建模。对现代制导律在不同情况下的仿真结果进行了评价,并对PN等经典制导律进行了比较。在Xilinx FPGA处理器上使用系统生成器(Xilinx工具箱)实现了调谐后的APN律,该系统生成器作为处理器在环路(SIL)仿真方案中进行仿真模型。仿真结果表明了APN相对于其他经典制导律的优越性,并对该FPGA处理器的性能进行了评估和讨论。
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Evaluation of Missile Terminal Guidance Using Software in Loop (SIL)
Missile interception capability particularly depends on the guidance law implemented in the guidance processor of the missile. The majority of missiles employ proportional navigation (PN) as the primary guidance law since its first usage in the 20th century. PN tends to nullify the line-of-sight (LOS) angular rate by adjusting the missile turning rate proportionally to the LOS rate. With the great improvements in the aeronautic industry, PN is no more sufficient for highly maneuvering targets. Developing mathematical based advanced guidance laws has concerned a lot of researchers in that field and since then a lot of advanced guidance laws have been proposed and tested. Augmented PN (APN) is one of the proposed advanced guidance laws that can interact with highly maneuvering targets by augmenting the original PN with a target acceleration term which is estimated online. In this research, APN simulation and two-dimensioned missile-target intercept geometry are modeled using Matlab® Simulink™. Simulation results through different scenarios for modern guidance laws are evaluated and compared with other classical ones such as PN. The tuned APN law is implemented on a Xilinx FPGA processor using a system generator (Xilinx toolbox) which is conducted to the simulation model as a processor in the loop (SIL) simulation scheme. Simulation results show the superiority of APN against other classical guidance laws and the capability of the Xilinx FPGA processor is assessed and discussed.
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