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- ItemAll-sky interferometric meteor radar meteoroid speed estimation using the Fresnel transform(München : European Geopyhsical Union, 2007) Holdsworth, D.A.; Elford, W.G.; Vincent, R.A.; Reid, I.M.; Murphy, D.J.; Singer, W.Fresnel transform meteor speed estimation is investigated. A spectral based technique is developed allowing the transform to be applied at low temporal sampling rates. Simulations are used to compare meteoroid speeds determined using the Fresnel transform and alternative techniques, confirming that the Fresnel transform produces the most accurate meteoroid speed estimates for high effective pulse repetition frequencies (PRFs). The Fresnel transform is applied to high effective PRF data collected during Leonid meteor showers, producing speed estimates in good agreement with the theoretical pre-atmospheric speed of the 71 kms−1. Further simulations for the standard low effective PRF sampling parameters used for Buckland Park meteor radar (BPMR) observations suggests that the Fresnel transform can successfully estimate meteor speeds up to 80 kms−1. Fresnel transform speed estimation is applied using the BPMR, producing speed distributions similar to those obtained in previous studies. The technique is also applied to data collected using the BPMR sampling parameters during Southern delta-Aquarid and Geminid meteor showers, producing speeds in very good agreement with the theoretical pre-atmospheric speeds of these showers (41 kms−1 and 35 kms−1, respectively). However, application of the Fresnel transform to high speed showers suggests that the practical upper limit for accurate speed estimation using the BPMR sampling parameters is around 50 kms−1. This limit allows speed accurate estimates to be made for about 70% of known meteor showers, and around 70% of sporadic echoes.
- ItemEstimation of sedimentary proxy records together with associated uncertainty(Göttingen : Copernicus GmbH, 2015) Goswami, B.; Heitzig, J.; Rehfeld, K.; Marwan, N.; Anoop, A.; Prasad, S.; Kurths, J.
- ItemA propagation-separation approach to estimate the autocorrelation in a time-series(Göttingen : Copernicus, 2008) Divine, D.V.; Polzehl, J.; Godtliebsen, F.The paper presents an approach to estimate parameters of a local stationary AR(1) time series model by maximization of a local likelihood function. The method is based on a propagation-separation procedure that leads to data dependent weights defining the local model. Using free propagation of weights under homogeneity, the method is capable of separating the time series into intervals of approximate local stationarity. Parameters in different regions will be significantly different. Therefore the method also serves as a test for a stationary AR(1) model. The performance of the method is illustrated by applications to both synthetic data and real time-series of reconstructed NAO and ENSO indices and GRIP stable isotopes.