Detection of False Data Injection Attacks in Smart Grid under Colored Gaussian Noise

Bo, Tang; Yan, Jun; Kay, Steven; He, Haibo

doi:10.48550/arxiv.1607.06015

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2016

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“…However, the assumption of Gaussian noise may be not always true for many practical problems of interest. The colored Gaussian noise may degrade the detection performance of the existing GLRT and Rao test detectors devised for Gaussian noise [6,7,8]. To address this issue, many colored Gaussian noise models have been studied.…”

Section: Introductionmentioning

confidence: 99%

Adaptive Signal Detection and Parameter Estimation in Unknown Colored Gaussian Noise

Tang¹,

He²,

Kay³

2016

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This paper considers the general signal detection and parameter estimation problem in the presence of colored Gaussian noise disturbance. By modeling the disturbance with an autoregressive process, we present three signal detectors with different unknown parameters under the general framework of binary hypothesis testing. The closed form of parameter estimates and the asymptotic distributions of these three tests are also given. Given two examples of frequency modulated signal detection problem and time series moving object detection problem, the simulation results demonstrate the effectiveness of three presented detectors.

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Section: Introductionmentioning

confidence: 99%