NDLI: Optimal invariant detection of a monochromatic plane wave with unknown amplitude, frequency, phase, direction of arrival and noise variance

Content Provider	IET Digital Library
Author	Yu, Zi bin Cheng, Lei Zhao, Hang fang Gong, Xian yi
Abstract	This study deals with the problem of detecting a monochromatic plane wave with unknown amplitude, phase, temporal frequency and direction of arrival in complex white Gaussian noise with unknown variance. Depending on the natural invariance in scale, temporal modulation and spatial modulation of the problem, the uniformly most powerful invariant (UMPI) test is derived by using the statistical invariance principles. However, the UMPI test does not apply unless the signal-to-noise ratio (SNR) is known. However, it provides us with performance bound to evaluate any invariant test's performance when the SNR is unknown. Typically, the generalised likelihood ratio test (GLRT) and locally most powerful invariant (LMPI) test are derived as realisable suboptimal invariant tests with their performance comparison in different SNR through theoretical analysis. Computer simulation examples corroborate the authors analysis and indicate that the GLRT is close to the UMPI bound especially in the low probability-of-false-alarm (P FA) region of the receiver operating characteristic curve while the performance of the LMPI test is close to that of the UMPI test in the low SNR region.
Starting Page	465
Ending Page	478
Page Count	14
ISSN	17518784
Volume Number	8
e-ISSN	17518792
Issue Number	Issue 5, Jun (2014)
Alternate Webpage(s)	https://digital-library.theiet.org/content/journals/iet-rsn/8/5
Alternate Webpage(s)	https://digital-library.theiet.org/content/journals/10.1049/iet-rsn.2013.0109
Journal	IET Radar, Sonar & Navigation
Publisher Date	2013-12-19
Access Restriction	Open
Rights Holder	© The Institution of Engineering and Technology
Subject Keyword	Complex White Gaussian Noise Direction of Arrival Direction of Arrival Estimation Gaussian Noise Generalised Likelihood Ratio Test GLRT Locally Most Powerful Invariant Test Maximum Likelihood Estimation Monochromatic Plane Wave Detection Noise Variance Optimal Invariant Detection Receiver Operating Characteristic Curve Signal Detection Signal Processing Theory Spatial Modulation Statistical Invariance Principle Statistics Suboptimal Invariant Tests Temporal Frequency Temporal Modulation UMPI Uniformly Most Powerful Invariant Test Unknown Variance Wave Amplitude Wave Phase White Noise
Content Type	Text
Resource Type	Article
Subject	Electrical and Electronic Engineering

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