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Global Descriptors of Convolution Neural Networks for Remote Scene Images Classification Read chapter Read first chapter

2020 | OriginalPaper | Chapter

3D Statistical Resolution Limit of Two Close Spaced Targets for Active Array in the GLRT Context

Authors : Pei Peng, Yunlei Zhang, Jianbin Lu

Published in: Artificial Intelligence in China

Publisher: Springer Singapore

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Abstract

The current research of the statistical resolution limit (SRL), which is based on the hypothesis test, usually takes Taylor expansion and approximation to get a linear model of general likelihood rate test (GLRT) and achieves an analytical expression of the SRL. In the way, one dimension (range, angle) and two dimensions (range-Doppler, angle-Doppler) SRLs have been explored. In this paper we dwell on the three-dimension (3D) SRL in range-angle-Doppler domain and discuss the factors which make effects on 3D SRL. Our theoretical and simulation results both demonstrate that the 3D SRL is the weighting square sum of three respective SRLs, which will throw some insights into the systemic design to improve the resolution ability.

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previous chapter A Transmission Method for Intra-flight Ad Hoc Networks Based on Business Classification
next chapter A Scene Semantic Recognition Method of Remote Sensing Images Based on CSIFT and PLSA
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Metadata
Title
3D Statistical Resolution Limit of Two Close Spaced Targets for Active Array in the GLRT Context
Authors
Pei Peng
Yunlei Zhang
Jianbin Lu
Copyright Year
2020
Publisher
Springer Singapore
Book
Artificial Intelligence in China

Print ISBN: 978-981-15-0186-9

Electronic ISBN: 978-981-15-0187-6

Copyright Year: 2020

DOI
https://doi.org/10.1007/978-981-15-0187-6_43