Adaptive detection for distributed targets in Gaussian noise with Rao and Wald tests

The problem of adaptively detecting a range distributed target or targets in Gaussian interference is considered in this paper.It is assumed that a set of secondary data is available.Firstly,we derive the adaptive Rao and Wald tests with one-step detection algorithm,and find that both of them are of...

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Bibliographic Details
Published in:Science China. Information sciences 2012-06, Vol.55 (6), p.1290-1300
Main Authors: Shuai, XiaoFei, Kong, LingJiang, Yang, JianYu
Format: Article
Language:English
Subjects:
Adaptive algorithms
Algorithms
Assessments
Asymptotic properties
Computer Science
Derivation
Equivalence
Gaussian
GLRT
Information Systems and Communication Service
Noise
Random noise
Research Paper
Strategy
Target detection
分布范围
噪声分布
干扰目标
测试
自适应检测
设计策略
高斯噪声
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Description
Summary:The problem of adaptively detecting a range distributed target or targets in Gaussian interference is considered in this paper.It is assumed that a set of secondary data is available.Firstly,we derive the adaptive Rao and Wald tests with one-step detection algorithm,and find that both of them are of the same asymptotic performance as the GLRT one.Secondly,the Rao and Wald tests are derived by resorting to the two-step design strategy.To our surprise,our derivations show that all the Rao,Wald and GLR tests in the two-step design strategy are equivalent.Thirdly,the property assessments are presented.It is shown that these new detectors guarantee CFAR property with respect to the Gaussian noise.Finally,simulation results show that these results are accurate.
ISSN:1674-733X
1869-1919
DOI:10.1007/s11432-011-4417-2