On approximating the distribution of quadratic forms in uniform and beta order statistics

Provost, Serge B.; Mohsenipour, A. Akbar

doi:10.1007/s40300-013-0014-z

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B the Rsf Configuration1

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2015

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“…The determination of E[g(X)] involves the joint distribution function of the quadratic form K T WK, which is highly complex for the uniform distributed variables k i [16]. We resort to approximations here.…”

Section: B the Rsf Configurationmentioning

confidence: 99%

Performance of ML Range Estimator in Radio Interferometric Positioning Systems

Zhang

et al. 2015

IEEE Signal Process. Lett.

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The radio interferometric positioning system (RIPS) is a novel positioning solution used in wireless sensor networks. This letter explores the ranging accuracy of RIPS in two configurations. In the linear step-frequency (LSF) configuration, we derive the mean square error (MSE) of the maximum likelihood (ML) estimator. In the random step-frequency (RSF) configuration, we introduce average MSE to characterize the performance of the ML estimator. The simulation results fit well with theoretical analysis.It is revealed that RSF is superior to LSF in that the former is more robust in a jamming environment with similar ranging accuracy. Index TermsRadio interferometric positioning system, maximum likelihood estimator, method of interval error, outlier probability, average MSE, average ambiguity function.

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Section: B the Rsf Configurationmentioning

confidence: 99%

Performance of ML Range Estimator in Radio Interferometric Positioning Systems

Zhang

et al. 2015

IEEE Signal Process. Lett.

View full text Add to dashboard Cite

show abstract

On approximating the distribution of quadratic forms in uniform and beta order statistics

Cited by 1 publication

References 8 publications

Performance of ML Range Estimator in Radio Interferometric Positioning Systems

Performance of ML Range Estimator in Radio Interferometric Positioning Systems

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