Mathematical Techniques in Multisensor Data Fusion

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Artech House, 2004 - Computers - 449 pages
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Since the publication of the first edition of this book, advances in algorithms, logic and software tools have transformed the field of data fusion. The latest edition covers these areas as well as smart agents, human computer interaction, cognitive aides to analysis and data system fusion control. data fusion system, this book guides you through the process of determining the trade-offs among competing data fusion algorithms, selecting commercial off-the-shelf (COTS) tools, and understanding when data fusion improves systems processing. Completely new chapters in this second edition explain data fusion system control, DARPA's recently developed TRIP model, and the latest applications of data fusion in data warehousing and medical equipment, as well as defence systems.
 

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Contents

Introduction to Multisensor Data Fusion
1
12 FUSION APPLICATIONS
3
13 SENSORS AND SENSOR DATA
8
OUTPUT DATA
16
15 A DATA FUSION MODEL
18
16 BENEFITS OF DATA FUSION
22
17 ARCHITECTURAL CONCEPTS AND ISSUES
27
18 LIMITATIONS OF DATA FUSION
32
KnowledgeBased Approaches
239
72 OVERVIEW OF EXPERT SYSTEMS
245
73 IMPLEMENTATION OF EXPERT SYSTEMS
266
74 LOGICAL TEMPLATING TECHNIQUES
278
75 BAYES BELIEF SYSTEMS
283
76 INTELLIGENT AGENT SYSTEMS
285
Level 4 Processing Process Monitoring and Optimization
291
82 EXTENDING THE CONCEPT OF LEVEL 4 PROCESSING
297

Introduction to the Joint Directors of Laboratories JDL Data Fusion Process Model and Taxonomy of Algorithms
37
22 LEVEL 1 FUSION ALGORITHMS
42
24 LEVEL 3 FUSION ALGORITHMS
57
25 LEVEL 4 FUSION ALGORITHMS
59
26 LEVEL 5 FUSION TECHNIQUES
62
27 ANCILLARY SUPPORT FUNCTIONS
65
28 ALTERNATIVE DATA FUSION PROCESS MODELS
66
Level 1 Processing Data Association and Correlation
73
32 PROCESS MODEL FOR CORRELATION
78
33 HYPOTHESIS GENERATION
80
34 HYPOTHESIS EVALUATION
99
35 HYPOTHESIS SELECTION TECHNIQUES
109
Level 1 Fusion Kinematic and Attribute Estimation
129
42 OVERVIEW OF ESTIMATION TECHNIQUES
132
43 BATCH ESTIMATION
144
44 SEQUENTIAL ESTIMATION
153
45 COVARIANCE ERROR ESTIMATION
163
46 RECENT DEVELOPMENTS IN ESTIMATION
166
Identity Declaration
171
52 FEATURE EXTRACTION
178
53 PARAMETRIC TEMPLATES
185
54 CLUSTER ANALYSIS TECHNIQUES
187
55 ADAPTIVE NEURAL NETWORKS
193
56 PHYSICAL MODELS
196
57 KNOWLEDGEBASED METHODS
198
DecisionLevel Identity Fusion
205
62 CLASSICAL INFERENCE
209
63 BAYESIAN INFERENCE
214
64 DEMPSTERSHAFERS METHOD
220
65 GENERALIZED EVIDENCE PROCESSING GEP THEORY
229
66 HEURISTIC METHODS FOR IDENTITY FUSION
231
67 IMPLEMENTATION AND TRADEOFFS
234
83 TECHNIQUES FOR LEVEL 4 PROCESSING
300
84 AUCTIONBASED METHODS
308
85 RESEARCH ISSUES IN LEVEL 4 PROCESSING
311
Level 5 Cognitive Refinement and HumanComputer Interaction
315
92 COGNITIVE ASPECTS OF SITUATION ASSESSMENT
317
93 INDIVIDUAL DIFFERENCES IN INFORMATION PROCESSING
320
95 COMPUTERAIDED SITUATION ASSESSMENT
330
96 AN SBIR MULTIMODE EXPERIMENT IN COMPUTERBASED TRAINING
336
Implementing Data Fusion Systems
345
102 REQUIREMENTS ANALYSIS AND DEFINITION
349
103 SENSOR SELECTION AND EVALUATION
351
104 FUNCTIONAL ALLOCATION AND DECOMPOSITION
356
105 ARCHITECTURE TRADEOFFS
358
106 ALGORITHM SELECTION
364
107 DATABASE DEFINITION
369
108 HCI DESIGN
373
109 SOFTWARE IMPLEMENTATION
377
1010 TEST AND EVALUATION
379
Emerging Applications of Multisensor Data Fusion
385
112 SURVEY OF MILITARY APPLICATIONS
386
113 EMERGING NONMILITARY APPLICATIONS
392
114 COMMERCIAL OFF THE SHELF COTS TOOLS
399
115 PERSPECTIVES AND COMMENTS
408
Automated Information Management
415
AUTOMATED TARGETING DATA FUSION
419
STRUCTURE AND FLOW
424
AUTOMATED IMAGERY CORROBORATION
433
UBIQUITOUS UTILITY
441
About the Authors
445
Index
447
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About the author (2004)

David L. Hall is the associate dean for research and graduate programs at The Pennsylvania State University, School of Information Sciences and Technology.

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