Semiparametric Algorithm for Processing MST Radar Data

Eappen, Neetha I.; Reddy, T. Sreenivasulu; Reddy, G. Ramachandra

doi:10.1109/tgrs.2015.2504949

Cited by 7 publications

(2 citation statements)

References 10 publications

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“…where R −1∕2 N represents the Hermitian square root of R −1 N , ‖⋅‖ denotes the Frobenius norm. SPICE estimate [7,8] of the m r 's is an iterative process of the form:…”

Section: Review Of Spice Algorithmmentioning

confidence: 99%

Fast implementation of sparse iterative covariance-based estimation for processing MST radar data

Raju

Reddy

2019

SN Appl. Sci.

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Doppler estimation is an essential problem for the mesosphere-stratosphere-troposphere (MST) radar data for estimation of atmospheric parameters. The Doppler is estimated by computing the power spectral density using either parametric or non-parametric method. A recent class of spectral estimation technique referred as Sparse Iterative Covariance Based Estimation (SPICE) is introduced in literature. SPICE is a sound, user-parameter free, good resolution, iterative and globally convergent method which exhibits the enhanced results than the current spectral estimation methods, at the high computational cost. This letter presents the fast implementation of the SPICE algorithm for the MST radar data and the estimation of various wind parameters at a lesser computational time and is validated with the radiosonde data.

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“…where R −1∕2 N represents the Hermitian square root of R −1 N , ‖⋅‖ denotes the Frobenius norm. SPICE estimate [7,8] of the m r 's is an iterative process of the form:…”

Section: Review Of Spice Algorithmmentioning

confidence: 99%

Fast implementation of sparse iterative covariance-based estimation for processing MST radar data

Raju

Reddy

2019

SN Appl. Sci.

View full text Add to dashboard Cite

show abstract

“…Several data processing techniques earlier implemented on MST radar dataset for signal enhancement by noise suppression include the Bi-spectral process (Rao et al, 2008) [ 6 ], Principal component analysis (Rao et al, 2014) [ 7 ], Semi Parametric sparse Iterative Covariance-based Estimation (SPICE) technique (Eappen et al, 2015) [ 8 ], non-parametric and semi-parametric spectral techniques (Raju et al, 2019) [ 9 ]. These techniques could deliver a maximum altitude coverage of 20–21 km using the old MST dataset, which was discontinuous across incoherent integrations.…”

Section: Introductionmentioning

confidence: 99%