空间态势评估初探

文章从空间态势评估的基本概念出发,指出了空间态势评估的主要任务和特点,对空间态势评估的过程进行了初步探讨,建立了空间态势评估的功能模型,简述了实现空间态势评估系统的关键技术,为进一步开发空间态势评估系统奠定了基础。     

态势估计技术及其算法研究

态势估计根据功能划分为态势觉察、态势理解、态势预测三级。由于态势元素的层次性 ,可以使用多级多层黑板模型构建态势估计系统。态势觉察为态势估计过程提炼态势元素 ,用到的技术有事件提取和分群技术。高层态势估计 (态势理解、态势预测 )需要详尽的态势知识库描述特定战场态势的时间、空间和因果关系 ,需选择适合应用领域的态势推理算法 ,基于模板匹配的方法简单可行 ;当前研究热点是规划识别系统和贝叶斯网络。     

态势评估领域知识的表示方法研究

从分析态势评估专家系统的结构出发,研究战场态势评估知识库的构建,进而对态势评估的领域知识进行归纳,并通过示例探讨对态势评估领域知识的表示方法,同时把可信度方法引入态势评估不确定性知识的表示,给出了复合条件可信度的计算方法。     

空间目标态势行为与事件本体设计与构建

针对空间目标态势威胁响应和预警研究不完善的问题，为实现空间目标行为和事件的智能推理、实时响应和主动预警，保障航天活动和空间利益，提出面向行为与事件的空间目标态势本体模型(BEO-SO2)。基于基本形式本体(BFO)，构建空间目标态势行为与事件本体模型。在统一时空框架下建立空间目标关系模型，实现空间目标行为执行和事件发生过程的动态推演。以空间目标碰撞威胁为背景，设计对象实体等级体系和碰撞威胁行为与事件要素，建立碰撞威胁推理规则，基于空间目标态势行为与事件本体进行实现、验证与展示。结果表明,空间目标态势行为与事件本体能够实现空间目标碰撞威胁的等级推理与预警，并指导进一步的空间活动，为航天任务与空间活动提供有效保障。     

天波干扰态势预测系统设计与实现

对短波干扰的电磁态势进行实时的预测,可以更好地配置干扰资源,掌控干扰效果.分析了天波干扰态势预测的现实需求,给出了天波态势预测方法步骤,并提出预测软件架构设计.     

基于态势感知一致性的UAV集群分布式协同性能分析

针对现有无人机集群分布式协同方法没有细致考虑态势感知过程，忽略了对抗环境下态势信息的不确定性对集群协同的影响，对协同性能缺乏量化分析等问题，提出基于态势感知一致性的无人机集群分布式协同方法，并分析协同性能。从集群协同作战角度分析协同方法的实质，考虑态势信息不确定性，给出集群态势感知一致性分析，建立态势觉察一致性、态势理解一致性等概念，并设计协同方法；建立协同时间、协同信息量等指标，分析指标特性，量化分析协同性能；在给定的仿真场景下，对比分析各协同方法性能。结果表明，所提方法协同性能较好，更切合对抗环境，对集群协同作战研究有一定的积极意义。     

多源信息融合在空间态势感知领域的应用与发展

在当前复杂多样的航天任务领域中,多源信息融合技术的重要性日益突出。文章以多源信息融合技术为核心,调研分析了其在空间态势感知领域的应用现状与发展前景;概述了多源信息融合的定义、模型和理论研究现状;归纳了空间态势感知的信息源种类和典型传感器;分析了基于多源信息融合的典型空间态势感知系统,包括美国空间监视网(SSN)、"轨道瞭望"(OrbitOutlook)计划、"印记"(Hallmark)计划和欧盟空间监视与跟踪系统(EUSST)等;最后对多源信息融合在空间态势感知领域的发展前景进行了展望。文章研究结果可为中国空间态势感知和多源信息融合技术发展提供参考。     

针对GEO目标的美国天基态势感知技术发展研究

为了掌握针对地球静止轨道(GEO)目标的天基态势感知技术动向,文章系统整理了美国相关卫星的公开数据和资料。根据卫星的功能和使命,GEO目标的天基态势感知技术试验卫星可分为3类:目标观测卫星、目标交会与抵近操作卫星以及目标编目卫星,并分别对3类技术试验卫星的有效载荷、平台和运行轨道等方面进行分析和比较,梳理了针对GEO目标的天基态势感知技术发展演进脉络,对后续态势感知技术的发展趋势进行了预测。文章的研究内容可为我国未来态势感知技术发展提供借鉴。     

美国空间监视系统最新发展及趋势分析

近几年,美军为增强空间态势感知能力,大力发展空间监视系统,发展重点包括两个方面：一是对原有空间监视网进行改进,二是研制和部署新的天基和地基空间监视系统。文章介绍了美国空间监视系统最新发展计划,总结了各计划的进展情况,研究了未来新系统的能力,并分析了美国空间监视系统总体发展趋势。     

基于集对理论的空间战场态势定量分析

以集对分析的同异反联系度为基础,结合武器与人员因素分析战场态势。从全局的角度,对空间战场整体态势进行研究,引入指标权重,构建空间战场态势分析模型,通过实例计算分析空间战场态势优劣。     

Modelling Dynamic Spatial Systems in the Situation Calculus

Abstract

We propose and systematically formalise a dynamical spatial systems approach for the modelling of changing spatial environments. The formalisation adheres to the semantics of the situation calculus and includes a systematic account of key aspects that are necessary to realize a domain-independent qualitative spatial theory that may be utilised across diverse application domains. The spatial theory is primarily derivable from the all-pervasive generic notion of “qualitative spatial calculi” that are representative of differing aspects of space. In addition, the theory also includes aspects, both ontological and phenomenal in nature, that are considered inherent in dynamic spatial systems. Foundational to the formalisation is a causal theory that adheres to the representational and computational semantics of the situation calculus. This foundational theory provides the necessary (general) mechanism required to represent and reason about changing spatial environments and also includes an account of the key fundamental epistemological issues concerning the frame and the ramification problems that arise whilst modelling change within such domains. The main advantage of the proposed approach is that based on the structure and semantics of the proposed framework, fundamental reasoning tasks such as projection and explanation directly follow. Within the specialised spatial reasoning domain, these translate to spatial planning/re-configuration, causal explanation and spatial simulation. Our approach is based on the hypothesis that alternate formalisations of existing qualitative spatial calculi using high-level tools such as the situation calculus are essential for their utilisation in diverse application domains such as intelligent systems, cognitive robotics and event-based GIS.     

Implicit spatial reference systems using proximity and aligment knowledge

In this paper, we explore the situation where no cardinal directions or globally available orientations are available and no metric estimates are given. This corresponds to the way many people perceive their environment and carry out spatial reasoning tasks. We consider three kinds of locally available information – proximity (nearest neighbor), relevance (different sets of neighbors) and distribution (alignments) – and we limit our interest to a universe of point objects. We show how the theory of manifolds and sheaves can be applied to the problem of combining locally available information of a qualitative nature into a global model of an environmental space. We then explore the limitations of the resulting global model if information capture is incomplete or uncertain. Finally, we note that some indeterminacy in the global model does not entail difficulties for a user, provided the reasoning task is appropriately constrained or appropriate additional information is used, such as an external reference.     

美国空间态势感知系统发展现状及趋势分析

空间态势感知(SSA)是航天电子对抗的重点内容之一,SSA项目的研发已引起极大的关注.简要介绍了美国<2020年空军条令>中有关SSA的规划,重点讨论美国在研的几种SSA系统现状,明确了其未来的SSA是响应型.最后,分析了未来的响应型SSA.     

基于PRA的交会对接任务可靠性评估

为有效评估交会对接任务过程的可靠性指标,提出了基于概率风险评价（PRA）的交会对接任务可靠性评估方法,该方法是通过事件树描述各事件或功能的可靠性与任务可靠性之间的关系,同时通过概率风险模型描述事件或功能的可靠性与设备可靠性之间的关系。根据我国航天领域可靠性工作现状,提出了交会对接过程可靠性评估的工程流程。     

A Neuro-Cognitive Theory of Deductive Relational Reasoning with Mental Models and Visual Images

Abstract

Many neuro-imaging studies have provided evidence that the parietal cortex plays a key role in reasoning based on mental models, which are supposed to be of abstract spatial nature. However, these studies have also shown concurrent activation in vision-related cortical areas which have often been interpreted as evidence for the role of visual mental imagery in reasoning. The aim of the paper is to resolve the inconsistencies in the previous literature on reasoning and imagery and to develop a neurally and cognitively plausible theory of human relational reasoning. The main assumption is that visual brain areas are only involved if the problem information is easy to visualize and when this information must be processed and maintained in visual working memory. A regular reasoning process, however, does not involve visual images but more abstract spatial representations—spatial mental models—held in parietal cortices. Only these spatial representations are crucial for the genuine reasoning processes.     

TDD: A Comprehensive Model for Qualitative Spatial Similarity Assessment

Similarity plays a fundamental role in the human cognition process. It serves as a principle of categorization, inductive reasoning, and analogical inference. Spatial similarity assessment plays the same role in the retrieval, integration, and data mining of spatial information. In this paper, we introduce the basic components of a similarity assessment model. The model makes a contribution in the following aspects. First, it applies the order of priority topology --> direction --> distance into spatial similarity assessment. Second, instead of measuring the distance between stimuli, which neglects the effect of common features, we adopt Tversky's feature contrast model, which considers both commonality and difference in similarity assessment. Third, our model applies spatial alignment, which was considered as an assumption in previous research. Fourth, it relaxes the rule used in previous research, which considered identical the transformation costs of each edge belonging to a conceptual neighborhood network. In order to address this fourth point, we group the topological relationships and introduce the concepts of inter- and intra-group transformation costs. The inter-group transformation cost has a higher value than the intra-group transformation cost. We call the model TDD for Topology-Direction-Distance.     

一个基于多重推理的遥感图片解译专家系统

本文研究了在图象模式识别过程中引入人工智能的知识学习、知识表达和知识推理的理论和技术,设计并实现了一个应用于遥感图片解译的计算机视觉专家系统。 为使系统具有较高的智能化程度,本文提出了一种新的推理方法——多重推理法,它具有处理某些不完全知识和错误知识的能力,并且推理过程所运用的部分知识(规则)是从已知样本中自动归纳学习生成的。