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Tables of Contents for Mathematical Techniques in Multisensor Data Fusion
Chapter/Section Title
Page #
Page Count
Preface
xiii
Introduction to Multisensor Data Fusion
1
36
Introduction
1
2
Fusion Applications
3
5
Sensors and Sensor Data
8
8
The Inference Hierarchy: Output Data
16
2
A Data Fusion Model
18
4
Benefits of Data Fusion
22
5
Architectural Concepts and Issues
27
5
Limitations of Data Fusion
32
5
Introduction to the Joint Directors of Laboratories (JDL) Data Fusion Process Model and Taxonomy of Algorithms
37
36
Introduction to the JDL Data Fusion Processing Model
37
5
Level 1 Fusion Algorithms
42
12
Data Alignment
44
1
Data/Object Correlation
44
1
Object Position, Kinematic, and Attribute Estimation
45
2
Object Identity Estimation
47
7
Level 2 Fusion Algorithms
54
3
Level 3 Fusion Algorithms
57
2
Level 4 Fusion Algorithms
59
3
Level 5 Fusion Techniques
62
3
Ancillary Support Functions
65
1
Alternative Data Fusion Process Models
66
7
Dasarathy's Functional Model
66
1
Boyd's Decision Loop
67
1
Bedworth and O'Brien's Omnibus Process Model
68
1
TRIP Model
69
4
Level 1 Processing: Data Association and Correlation
73
56
Introduction
73
5
Process Model for Correlation
78
2
Hypothesis Generation
80
19
Characterizing the Hypothesis Generation Problem
85
7
Overview of Hypothesis Generation Techniques
92
7
Hypothesis Evaluation
99
10
Characterizing the Hypothesis Evaluation Problem
101
4
Overview of Hypothesis Evaluation Techniques
105
4
Hypothesis Selection Techniques
109
20
Defining the Hypothesis Selection Space
112
4
Overview of Hypothesis Selection Techniques
116
13
Level 1 Fusion: Kinematic and Attribute Estimation
129
42
Introduction
129
3
Overview of Estimation Techniques
132
12
System Models
133
3
Optimization Criteria
136
4
Optimization Approach
140
3
Processing Approach
143
1
Batch Estimation
144
9
Derivation of Weighted Least Squares Solution
144
5
Processing Flow
149
3
Batch Processing Implementation Issues
152
1
Sequential Estimation
153
10
Derivation of Sequential Weighted Least Squares Solution
154
2
Sequential Estimation Processing Flow
156
3
Sequential Processing Implementation Issues
159
1
The Alpha-Beta Filter
160
3
Covariance Error Estimation
163
3
Recent Developments in Estimation
166
5
Identity Declaration
171
34
Identity Declaration and Pattern Recognition
171
7
Feature Extraction
178
7
Parametric Templates
185
2
Cluster Analysis Techniques
187
6
Adaptive Neural Networks
193
3
Physical Models
196
2
Knowledge-Based Methods
198
2
Hybrid Techniques
200
5
Decision-Level Identity Fusion
205
34
Introduction
205
4
Classical Inference
209
5
Bayesian Inference
214
6
Dempster-Shafer's Method
220
9
Generalized Evidence Processing (GEP) Theory
229
2
Heuristic Methods for Identity Fusion
231
3
Implementation and Trade-Offs
234
5
Inference Accuracy and Performance
235
1
Computer Resource Requirements
236
1
A Priori Data Requirements
236
3
Knowledge-Based Approaches
239
52
Brief Introduction to Artificial Intelligence
239
6
Overview of Expert Systems
245
21
Expert System Concept
245
2
The Inference Process
247
2
Forward and Backward Chaining
249
1
Knowledge Representation
250
3
Representing Uncertainty
253
7
Search Techniques
260
3
Architectures for Knowledge-Based Systems
263
3
Implementation of Expert Systems
266
12
Life-Cycle Development Model for Expert Systems
266
3
Knowledge Engineering
269
3
Test and Evaluation
272
3
Expert System Development Tools
275
3
Logical Templating Techniques
278
5
Bayes Belief Systems
283
2
Intelligent Agent Systems
285
6
Level 4 Processing: Process Monitoring and Optimization
291
24
Introduction
291
6
Extending the Concept of Level 4 Processing
297
3
Techniques for Level 4 Processing
300
8
Sensor Management Functions
300
2
General Sensor Controls
302
3
Optimization of System Resources
305
1
Measures of Effectiveness and Performance
306
2
Auction-Based Methods
308
3
Market Components
309
1
Multiattribute Auctions
310
1
Multiattribute Auction Algorithms
311
1
Research Issues in Level 4 Processing
311
4
Level 5: Cognitive Refinement and Human-Computer Interaction
315
30
Introduction
315
2
Cognitive Aspects of Situation Assessment
317
3
Individual Differences in Information Processing
320
1
Enabling HCI Technologies
320
10
Visual and Graphical Interfaces
321
4
Aural Interfaces and Natural Language Processing (NLP)
325
2
Haptic Interfaces
327
1
Gesture Recognition
328
1
Wearable Computers
329
1
Computer-Aided Situation Assessment
330
6
Computer-Aided Cognition
330
1
Utilization of Language Constructs
331
3
Areas for Research
334
2
An SBIR Multimode Experiment in Computer-Based Training
336
9
SBIR Objective
336
1
Experimental Design and Test Approach
337
1
CBT Implementation
338
2
Summary of Results
340
1
Implications for Data Fusion Systems
341
4
Implementing Data Fusion Systems
345
40
Introduction
345
4
Requirements Analysis and Definition
349
2
Sensor Selection and Evaluation
351
5
Functional Allocation and Decomposition
356
2
Architecture Trade-Offs
358
6
Algorithm Selection
364
5
Database Definition
369
4
HCI Design
373
4
Software Implementation
377
2
Test and Evaluation
379
6
Emerging Applications of Multisensor Data Fusion
385
30
Introduction
385
1
Survey of Military Applications
386
6
Emerging Nonmilitary Applications
392
7
Intelligent Monitoring of Complex Systems
393
3
Medical Applications
396
1
Law Enforcement
397
1
Nondestructive Testing (NDT)
398
1
Robotics
398
1
Commercial Off The Shelf (COTS) Tools
399
9
Survey of COTS Software
399
1
Special Purpose COTS Software
399
3
General Purpose Data Fusion Software
402
4
A Survey of Surveys
406
2
Perspectives and Comments
408
7
Automated Information Management
415
30
Introduction
415
4
Initial Automated Information Manager: Automated Targeting Data Fusion
419
5
Automated Targeting Data Fusion: Structure and Flow
424
9
Automatic Information Needs Resolution Example: Automated Imagery Corroboration
433
8
Automated Image Corroboration Example
436
5
Automated Information Manager: Ubiquitious Utility
441
4
About The Authors
445
2
Index
447