相控阵雷达资源优化管理的理论与方法
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摘要
相控阵雷达是一种多功能、高性能的新型雷达系统,其依靠灵活的波束扫描方式、丰富的工作波形、可变的参数控制、可选的多种工作模式、高效的资源配置以及强大的数据处理能力,已成为雷达技术的重要发展方向。相控阵雷达系统优势的发挥需要依靠高效的资源管理技术作为支撑,相控阵雷达资源管理是雷达技术、计算机技术和控制技术相结合的产物,旨在通过对相控阵雷达系统中任务的有效调度、资源的合理分配以及工作参数的优化控制,以提高雷达系统的实际工作效能。因此,能否发挥相控阵雷达系统的优势,资源管理是其中的核心和关键环节。
本文以相控阵雷达系统资源优化管理为研究内容,建立了相控阵雷达搜索管理、多目标跟踪管理、雷达任务调度、观测任务规划、实时负载分配等问题的优化模型,提出了相应的解决方法,并将研究成果应用于空间探测相控阵雷达系统的任务计划设计中,取得了较好的实际效果。
在相控阵雷达搜索方式的参数优化及搜索策略设计方面,针对单次驻留时间内的目标检测,分析了搜索时间、脉冲积累数与最终检测性能的关系,推导给出了理论上最佳的搜索参数;针对目标的多帧积累检测问题,分析了搜索资源对搜索性能的影响,给出了资源受限下搜索参数的优化模型,提出了一种最优的搜索参数调整策略;研究了指示信息引导下的目标搜索问题,给出了搜索区域确定、区域内波位编排以及先验概率计算的方法,并提出了一种基于最大信息增益准则的最优搜索算法。
基于协方差控制的思想,建立了相控阵雷达多目标跟踪资源管理的理论框架,提出了资源管理的一般最优化模型,并以此给出了一种多目标跟踪资源管理算法;进一步将其推广到稳态跟踪和机动目标跟踪的情况下,分别提出了基于Riccati方程和IMM滤波器的资源管理方法;针对相控阵雷达时间一能量资源管理问题,提出了一种波束波形联合自适应调度算法。
依据相控阵雷达任务的多个属性参数分析了实时任务综合优先级的生成方法,构建了实时任务的修正EDF调度模型;建立了合理的相控阵雷达实时任务模型,并以此提出了一种相控阵雷达实时任务的自适应调度算法,分析了算法的可调度条件,给出了系统负载过载条件下任务参数的调整策略;针对空间探测相控阵雷达系统,基于修正EDF调度模型提出了一种相控阵雷达观测任务规划算法;进一步,根据可变观测时长任务模型,提出一种自适应任务规划算法,该算法通过引入任务的可选部分,有效地提升系统任务规划的成功率以及资源利用率。
将可分性负载理论推广到实时任务处理中,提出了相控阵雷达实时可分性负载分配的最优化模型;以雷达系统中的异构总线网络为分析对象,研究了最优的实时可分性负载分配方法,给出了负载分配的最优次序以及参与处理的最优节点数目;进一步给出了网络参数的估计方法。
最后,针对实际的空间探测相控阵雷达系统,研究了系统中任务计划处理的设计与实现问题;提出了任务计划设计的基本原则和功能需求,进一步给出了系统设计的处理流程和模块结构;最后实现了一个完整的任务计划软件系统。
As a multi-function and high-performance radar system, phased array radar has the advantages of flexible beam pointing direction, versatile waveforms, controllable system parameters, as well as the effective resource allocation strategy and powerful data processing capacity. It is playing an important role in the future advanced radar systems. All the aforementioned predominance depends on the effective resource management. Resource management technique for phased array radar aims at improving the radar system performance by effectively task scheduling, resource allocation and parameter control. It is a combination of radar technique, computer technique and control technique. Thereby resource management technique has been a key factor in modern phased array radar system.
This dissertation studied some general theory and technique in phased array radar resource management, including search resource management, multi-target tracking management, radar task scheduling, observation mission planning, real-time load allocation and task planning system design for space surveillance phased array radar.
Parameter optimization and search strategy design for phased array radar search mode was firstly studied in the dissertation. Based on the analysis of search time, pulse integration number and detection performance, the optimum search parameter was obtained for the detection of single dwell time. While for the multi-frame integration cases, the impact of search resource on the radar system detection performance was discussed and the optimum search model with limited search resources was derived. Furthermore an optimum strategy of parameter adjustment was proposed. Based on the principle of the maximal information gain, a cued search method of phased array radar was presented, along with the discussion on the calculation of cued search region, beam position arrangement and the estimation of priori probability distribution.
According to the concept of covariance control, the theoretic architecture of multi-target tracking resource management for phased array radar was presented. And an optimum resource management model was built, together with a multi-target tacking resource management algorithm. Extending to the steady state tracking and maneuvering target tracking, two resource management algorithms were proposed based on the Riccati equation and IMM(Interacting Multiple Model) filter respectively. Furthermore a joint adaptive scheduling algorithm of beam and waveform was presented for time-energy resource management in phased array radar system.
With the analysis of the real-time task integrated priority by multi-attribute parameters, a real-time task modified EDF(Earliest Deadline First) scheduling model for phased array radar was built. The real-time task model and an adaptive real-time task scheduling algorithm for phased array radar were proposed. The schedulability condition was analyzed, followed by an effective task adjustment method under the condition of system overload. For the space surveillance phased array radar system, an observation mission planning algorithm was proposed. Furthermore, based on the task model of changeable observation span, an adaptive mission planning algorithm was presented which can evidently improve system performance.
Subsequently, by introducing divisible load theory to real-time task processing, an optimum real-time divisible load allocation model was established for phased array radar. Aiming at the heterogeneous bus network of radar system, the real-time divisible load allocation method was studied, and the optimum load distribution sequence as well as the processor number was given. Then the parameter estimation for the bus network was discussed.
Finally, for the space surveillance phased array radar system, the design and realization of task planning subsystem was studied. The basic principle and function requirement for designing the task planning subsystem were given. Then processing flow and module structure were presented. Based on the above work, a general task planning software was achieved.
本文以相控阵雷达系统资源优化管理为研究内容,建立了相控阵雷达搜索管理、多目标跟踪管理、雷达任务调度、观测任务规划、实时负载分配等问题的优化模型,提出了相应的解决方法,并将研究成果应用于空间探测相控阵雷达系统的任务计划设计中,取得了较好的实际效果。
在相控阵雷达搜索方式的参数优化及搜索策略设计方面,针对单次驻留时间内的目标检测,分析了搜索时间、脉冲积累数与最终检测性能的关系,推导给出了理论上最佳的搜索参数;针对目标的多帧积累检测问题,分析了搜索资源对搜索性能的影响,给出了资源受限下搜索参数的优化模型,提出了一种最优的搜索参数调整策略;研究了指示信息引导下的目标搜索问题,给出了搜索区域确定、区域内波位编排以及先验概率计算的方法,并提出了一种基于最大信息增益准则的最优搜索算法。
基于协方差控制的思想,建立了相控阵雷达多目标跟踪资源管理的理论框架,提出了资源管理的一般最优化模型,并以此给出了一种多目标跟踪资源管理算法;进一步将其推广到稳态跟踪和机动目标跟踪的情况下,分别提出了基于Riccati方程和IMM滤波器的资源管理方法;针对相控阵雷达时间一能量资源管理问题,提出了一种波束波形联合自适应调度算法。
依据相控阵雷达任务的多个属性参数分析了实时任务综合优先级的生成方法,构建了实时任务的修正EDF调度模型;建立了合理的相控阵雷达实时任务模型,并以此提出了一种相控阵雷达实时任务的自适应调度算法,分析了算法的可调度条件,给出了系统负载过载条件下任务参数的调整策略;针对空间探测相控阵雷达系统,基于修正EDF调度模型提出了一种相控阵雷达观测任务规划算法;进一步,根据可变观测时长任务模型,提出一种自适应任务规划算法,该算法通过引入任务的可选部分,有效地提升系统任务规划的成功率以及资源利用率。
将可分性负载理论推广到实时任务处理中,提出了相控阵雷达实时可分性负载分配的最优化模型;以雷达系统中的异构总线网络为分析对象,研究了最优的实时可分性负载分配方法,给出了负载分配的最优次序以及参与处理的最优节点数目;进一步给出了网络参数的估计方法。
最后,针对实际的空间探测相控阵雷达系统,研究了系统中任务计划处理的设计与实现问题;提出了任务计划设计的基本原则和功能需求,进一步给出了系统设计的处理流程和模块结构;最后实现了一个完整的任务计划软件系统。
As a multi-function and high-performance radar system, phased array radar has the advantages of flexible beam pointing direction, versatile waveforms, controllable system parameters, as well as the effective resource allocation strategy and powerful data processing capacity. It is playing an important role in the future advanced radar systems. All the aforementioned predominance depends on the effective resource management. Resource management technique for phased array radar aims at improving the radar system performance by effectively task scheduling, resource allocation and parameter control. It is a combination of radar technique, computer technique and control technique. Thereby resource management technique has been a key factor in modern phased array radar system.
This dissertation studied some general theory and technique in phased array radar resource management, including search resource management, multi-target tracking management, radar task scheduling, observation mission planning, real-time load allocation and task planning system design for space surveillance phased array radar.
Parameter optimization and search strategy design for phased array radar search mode was firstly studied in the dissertation. Based on the analysis of search time, pulse integration number and detection performance, the optimum search parameter was obtained for the detection of single dwell time. While for the multi-frame integration cases, the impact of search resource on the radar system detection performance was discussed and the optimum search model with limited search resources was derived. Furthermore an optimum strategy of parameter adjustment was proposed. Based on the principle of the maximal information gain, a cued search method of phased array radar was presented, along with the discussion on the calculation of cued search region, beam position arrangement and the estimation of priori probability distribution.
According to the concept of covariance control, the theoretic architecture of multi-target tracking resource management for phased array radar was presented. And an optimum resource management model was built, together with a multi-target tacking resource management algorithm. Extending to the steady state tracking and maneuvering target tracking, two resource management algorithms were proposed based on the Riccati equation and IMM(Interacting Multiple Model) filter respectively. Furthermore a joint adaptive scheduling algorithm of beam and waveform was presented for time-energy resource management in phased array radar system.
With the analysis of the real-time task integrated priority by multi-attribute parameters, a real-time task modified EDF(Earliest Deadline First) scheduling model for phased array radar was built. The real-time task model and an adaptive real-time task scheduling algorithm for phased array radar were proposed. The schedulability condition was analyzed, followed by an effective task adjustment method under the condition of system overload. For the space surveillance phased array radar system, an observation mission planning algorithm was proposed. Furthermore, based on the task model of changeable observation span, an adaptive mission planning algorithm was presented which can evidently improve system performance.
Subsequently, by introducing divisible load theory to real-time task processing, an optimum real-time divisible load allocation model was established for phased array radar. Aiming at the heterogeneous bus network of radar system, the real-time divisible load allocation method was studied, and the optimum load distribution sequence as well as the processor number was given. Then the parameter estimation for the bus network was discussed.
Finally, for the space surveillance phased array radar system, the design and realization of task planning subsystem was studied. The basic principle and function requirement for designing the task planning subsystem were given. Then processing flow and module structure were presented. Based on the above work, a general task planning software was achieved.
引文
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