Note: Front Cover -- Spatial Cognitive Engine Technology -- Spatial Cognitive Engine Technology -- Copyright -- Contents -- Preface -- 1 - Cognitive radio -- 1.1 Introduction -- 1.2 Concept of cognitive radio -- 1.3 Characteristics of cognitive radio technology -- References -- 2 - Cognitive engine technology -- 2.1 Conceptual connotation of the cognitive engine -- 2.2 Functions of cognitive engine -- 2.2.1 Cognitive cycle -- 2.2.1.1 Concept of cognitive cycle -- 2.2.1.2 Introduction to modules in cognitive cycle -- 2.2.1.3 Cognitive cycle and cognitive engine -- 2.2.1.4 Cognitive radio system level -- 2.2.2 Cognitive engine function model -- 2.3 Typical cognitive engine model -- 2.3.1 Cognitive engine of the Wireless Communication Center of Virginia Institute of Technology -- 2.3.2 Cognitive engine of US Department of Defense Communication Science Laboratory -- References -- 3 - Artificial intelligence technology -- 3.1 Artificial intelligence concept -- 3.1.1 Intelligence concept -- 3.1.2 Smart autonomy concept -- 3.2 Spacecraft intelligent autonomy level -- 3.3 Development and direction of artificial intelligence -- 3.3.1 Artificial intelligence development stage -- 3.3.2 Artificial intelligence development direction -- 3.3.3 Artificial intelligence development forecast -- References -- 4 - Requirements and challenges of space artificial intelligence -- 4.1 Space system demand for artificial intelligence technology applications -- 4.1.1 Space intelligent perception needs -- 4.1.2 Space intelligent decision-making and control requirements -- 4.1.3 Space cluster intelligence needs -- 4.1.4 Space intelligent interaction requirements -- 4.1.5 Space intelligent design requirements -- 4.2 Challenges to and solutions for application of artificial intelligence in aerospace -- 4.2.1 Hardware level -- 4.2.2 Software level -- 4.2.3 System level -- References. , 5 - Cognitive engine design based on artificial intelligence -- 5.1 Artificial intelligence technology at different cognitive stages -- 5.1.1 Environment perception and information storage stage -- 5.1.1.1 Knowledge representation -- 5.1.1.2 Expert system -- 5.1.2 Cognitive learning and reasoning stage -- 5.1.2.1 Genetic algorithm -- 5.1.2.2 Neural network -- 5.1.2.3 Fuzzy logic -- 5.1.3 Cognitive decision-making and adjustment stage -- 5.2 Cognitive engine architecture design based on artificial intelligence technology -- 5.2.1 System architecture -- 5.2.2 Information collection and rule derivation in inference and learning stages -- 5.3 Cognitive engine algorithm design based on artificial intelligence technology -- 5.3.1 Rule-based reasoning engine -- 5.3.2 Reconstruction decision-making algorithm combining inference and learning -- References -- 6 - Typical applications of cognitive engines -- 6.1 Multiobjective optimization and genetic algorithm -- 6.1.1 Mathematical model of multiobjective optimization problem -- 6.1.2 Pareto optimization -- 6.1.3 Basic genetic algorithm -- 6.1.4 Genetic algorithm based on target weight -- 6.1.5 Noninferior hierarchical genetic algorithm -- 6.2 Design of cognitive engine based on genetic algorithm -- 6.2.1 Cognitive engine optimization model -- 6.2.2 Choice of objective function -- 6.2.3 Relationship between optimization parameters and objective function -- 6.3 Case reasoning overview -- 6.3.1 Basic idea of case-based reasoning -- 6.3.2 Feasibility analysis of case-based reasoning in cognitive engine -- 6.4 Case reasoning design in cognitive engine -- 6.4.1 Case structure design -- 6.4.2 Case selection and retrieval -- 6.4.3 Case library maintenance -- 6.4.4 Genetic algorithm-case-based reasoning algorithm flow -- References -- 7 - Cognitive engine knowledge base design -- 7.1 Role of knowledge base. , 7.2 Data table structure design of knowledge base -- 7.2.1 Short-term knowledge base -- 7.2.1.1 Spectrum sensing energy value table -- 7.2.1.2 Spectrum sensing channel occupancy table -- 7.2.1.3 Short-term statistical information table -- 7.2.1.4 Short-term frequency point probability table -- 7.2.1.5 Short-term unavailable frequency band and noise frequency band table -- 7.2.1.6 Inference decision frequency hopping table -- 7.2.2 Long-term knowledge base -- 7.2.2.1 Case library table -- 7.2.2.2 Long-term unavailable frequency band and noise frequency band table -- 7.2.2.3 Long-term frequency point probability table -- References -- 8 - Hybrid inference integration mechanism based on data drive -- 8.1 Hybrid inference integration mechanism based on data drive -- 8.1.1 Dynamic and uncertain characteristics of intelligent decision-making -- 8.1.2 Mental patterns of human reasoning ability -- 8.1.3 Hybrid inference integration mechanism based on data drive -- 8.2 Service-oriented architecture-based inference engine framework design -- 8.2.1 Flexible design thinking -- 8.2.2 Overall design of system framework -- 8.2.3 Hierarchical design of system framework -- 8.2.4 System topology -- References -- 9 - Object-oriented knowledge representation -- 9.1 The data, information, knowledge, wisdom hierarchical model of knowledge -- 9.2 Concept of knowledge representation -- 9.3 Object-oriented knowledge representation -- 9.3.1 Object-oriented concept -- 9.3.2 Analysis of new object-oriented knowledge representation methods -- 9.3.3 The basic idea of object-oriented knowledge base construction -- References -- 10 - Basic theory and technology of reasoning engine -- 10.1 Rule-based reasoning -- 10.1.1 Basic process -- 10.1.2 Knowledge representation -- 10.1.3 Reasoning engine -- 10.1.4 Analysis of advantages and disadvantages -- 10.2 Case reasoning. , 10.2.1 Basic process -- 10.2.2 Knowledge representation -- 10.2.3 Reasoning engine -- 10.2.3.1 Nearest-neighbor approach -- 10.2.3.2 Inductive approach -- 10.2.3.3 Knowledge-based indexing approach -- 10.2.4 Analysis of advantages and disadvantages -- 10.2.4.1 Easy access to knowledge -- 10.2.4.2 High solution ability -- 10.2.4.3 Results are easy to interpret -- 10.2.4.4 Wide range of applications -- 10.2.4.5 Easy case maintenance -- 10.2.4.6 Incremental self-learning -- 10.2.4.7 Fast running speed -- 10.3 Comparison between rule-based reasoning and case-based reasoning -- 10.4 Distributed technology -- 10.4.1 MapReduce parallel programming model -- 10.4.2 Hadoop platform implementation -- References -- 11 - Spacecraft -- 11.1 Overview -- 11.2 Satellite remote sensing -- 11.2.1 Characteristics of satellite remote sensing -- 11.2.1.1 Unrestricted by national borders, the observation range is large -- 11.2.1.2 It is convenient for dynamic observation, and the cycle can be designed -- 11.2.1.3 The wide range of applications saves people and property -- 11.2.2 Basic theory of electromagnetic radiation -- 11.2.2.1 Solar radiation -- 11.2.2.2 Blackbody radiation -- 11.2.2.2.1 Stefan-Boltzmann law -- 11.2.2.2.2 Wien's displacement law -- 11.2.2.2.3 Planck's radiation law -- 11.2.2.2.4 Kirchhoff's law -- 11.2.3 Satellite remote sensing classification -- 11.2.3.1 Division from perspective of electromagnetic spectrum -- 11.2.3.2 From the perspective of technical means -- 11.2.3.3 Divide from the perspective of application objects -- 11.2.4 Typical parameters of satellite remote sensing -- 11.2.4.1 Spatial resolution -- 11.2.4.2 Spectral resolution -- 11.2.4.3 Time resolution -- 11.3 Satellite communications -- 11.3.1 Characteristics of satellite communication -- 11.3.1.1 Wide coverage area and large communication capacity. , 11.3.1.2 The communication distance is long and there is a transmission delay -- 11.3.2 Orbital location and frequency resources -- 11.3.3 Basic principle of satellite communications -- 11.3.4 Classification of satellite communications systems -- 11.3.5 Basic parameters of satellite communications -- 11.3.5.1 Equivalent isotropic radiated power -- 11.3.5.2 Noise figure and equivalent noise temperature -- 11.3.5.3 Carrier-to-noise ratio -- 11.3.5.4 Saturation flux density of satellite transponder -- 11.3.5.5 System bit error ratio -- 11.4 Satellite navigation -- 11.4.1 Features of satellite navigation -- 11.4.1.1 24-7 service -- 11.4.1.2 Simple applications and wide influence -- 11.4.1.3 Time-space benchmark military-civilian integration -- 11.4.2 Principle of satellite navigation -- 11.4.3 Classification of satellite navigation systems -- 11.4.3.1 Doppler frequency shift measurement system -- 11.4.3.2 Active pseudodistance measurement system -- 11.4.3.3 Passive pseudodistance measurement system -- 11.4.4 Basic parameters of satellite navigation -- References -- 12 - Compound knowledge mining -- 12.1 Data mining -- 12.1.1 Concept of data mining -- 12.1.2 Steps of data mining -- 12.1.3 Data mining methods -- 12.1.3.1 Correlation analysis -- 12.1.3.2 Granger causality test -- 12.1.3.3 Forecast analysis -- 12.2 Text mining -- 12.2.1 Concept of text mining -- 12.2.2 Steps of text mining -- 12.2.3 Text mining technology -- 12.2.3.1 Text correlation analysis -- 12.2.3.2 Reduced error pruning tree decision tree -- 12.3 Summary of chapter -- References -- 13 - Machine learning algorithm for cognitive engine -- 13.1 Artificial intelligence: endowing human intelligence to machines -- 13.2 Machine learning: a method to realize artificial intelligence -- 13.3 Deep learning: a technology to realize machine learning. , 13.4 Reinforcement learning: self-evolution mechanism of learning feedback.