Browsing by Author "Greenwald, R. A."

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    A comparison of SuperDARN ACF fitting methods
    Ribeiro, A. J.; Ruohoniemi, J. Michael; Ponomarenko, Pavlo V.; Clausen, Lasse B. N.; Baker, Joseph B. H.; Greenwald, R. A.; Oksavik, Kjellmar; de Larquier, S. (American Geophysical Union, 2013-05-01)
    The Super Dual Auroral Radar Network (SuperDARN) is a worldwide chain of HF radars which monitor plasma dynamics in the ionosphere. Autocorrelation functions are routinely calculated from the radar returns and applied to estimate Doppler velocity, spectral width, and backscatter power. This fitting has traditionally been performed by a routine called FITACF. This routine initiates a fitting by selecting a subset of valid phase measurements and then empirically adjusting for 2 phase ambiguities. The slope of the phase variation with lag time then provides Doppler velocity. Doppler spectral width is found by an independent fitting of the decay of power to an assumed exponential or Gaussian function. In this paper, we use simulated data to assess the performance of FITACF, as well as two other newer fitting techniques, named FITEX2 and LMFIT. The key new feature of FITEX2 is that phase models are compared in a least-squares fitting sense with the actual data phases to determine the best fit, eliminating some ambiguities which are present in FITACF. The key new feature of LMFIT is that the complex autocorrelation function (ACF) itself is fit, and Doppler velocity, spectral width, and backscatter power are solved simultaneously. We discuss some of the issues that negatively impact FITACF and find that of the algorithms tested, LMFIT provides the best overall performance in fitting the SuperDARN ACFs. The techniques and the data simulator are applicable to other radar systems that utilize multipulse sequences to make simultaneous range and velocity determinations under aliasing conditions.
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    A realistic radar data simulator for the Super Dual Auroral Radar Network
    Ribeiro, A. J.; Ponomarenko, Pavlo V.; Ruohoniemi, J. Michael; Baker, Joseph B. H.; Clausen, Lasse B. N.; Greenwald, R. A.; de Larquier, S. (American Geophysical Union, 2013-05-01)
    The Super Dual Auroral Radar Network (SuperDARN) is a chain of HF radars for monitoring plasma flows in the high and middle latitude E and F regions of the ionosphere. The targets of SuperDARN radars are plasma irregularities which can flow up to several kilometers per second and can be detected out to ranges of several thousand kilometers. We have developed a simulator which is able to model SuperDARN data realistically. The simulation system comprises four separate parts: model scatterers, model collective properties, a model radar, and post-processing. Importantly, the simulator is designed using the collective scatter approach which accurately captures the expected statistical fluctuations of the radar echoes. The output of the program can represent either receiver voltages or autocorrelation functions (ACFs) in standard SuperDARN file formats. The simulator is useful for testing and implementation of SuperDARN data processing software and for investigation of how radar data and performance change when the nature of the irregularities or radar operation varies. The companion paper demonstrates the application of simulated data to evaluate the performance of different ACF fitting algorithms. The data simulator is applicable to other ionospheric radar systems.