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Cognitive Fusion for Target Tracking [Kõva köide]

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Cognitive Fusion for Target TrackingSuurem pilt
Teised raamatud teemal:
Püsilink: https://www.kriso.ee/db/9781681736679.html
Märksõnad:

The adaptive configuration of nodes in a sensor network has the potential to improve sequential estimation performance by intelligently allocating limited sensor network resources.

In addition, the use of heterogeneous sensing nodes provides a diversity of information that also enhances estimation performance. This work reviews cognitive systems and presents a cognitive fusion framework for sequential state estimation using adaptive configuration of heterogeneous sensing nodes and heterogeneous data fusion. This work also provides an application of cognitive fusion to the sequential estimation problem of target tracking using foveal and radar sensors.

1 Introduction
1(8)
2 Cognitive Fusion
9(16)
2.1 State Space Formulation
9(6)
2.1.1 State Evolution Model
9(1)
2.1.2 Measurement Model
10(1)
2.1.3 Measurement Processing
11(4)
2.2 Cognitive Fusion Framework
15(10)
2.2.1 Prediction
15(3)
2.2.2 Node Configuration
18(1)
2.2.3 Measurement Update
18(7)
3 Cognitive Fusion for Target Tracking with Foveal and Radar Nodes
25(14)
3.1 State Space Formulation
25(6)
3.1.1 Target Motion Model
25(1)
3.1.2 Foveal Measurement Model
25(2)
3.1.3 Compressive Cognitive Radar Measurement Model
27(4)
3.2 Target Tracking Method
31(3)
3.2.1 Prediction
31(1)
3.2.2 Foveal Node Configuration
32(1)
3.2.3 Radar Node Configuration
33(1)
3.2.4 Measurement Update
33(1)
3.3 Simulation Scenario
34(5)
4 Conclusions
39(2)
A Sensing Node Configuration
41(2)
B Adaptive Compressive Sensing Matrix
43(4)
B.1 Sensing Matrix Construction
43(1)
B.2 Sensing Matrix Configurations
44(3)
B.2.1 Adaptive Sampling CSP (ASCSP)
44(1)
B.2.2 Non-Adaptive CSP (NACSP)
45(1)
B.2.3 Nyquist Sensing and Processing (NSP)
45(2)
Bibliography 47(10)
Author's Biography 57