EOVSA Implementation of a Spectral Kurtosis Correlator for Transient Detection and Classification

We describe in general terms the practical use in astronomy of a higher-order statistical quantity called spectral kurtosis (SK), and describe the first implementation of SK-enabled firmware in the Fourier transform-engine (F-engine) of a digital FX correlator for the Expanded Owens Valley Solar Array (EOVSA). The development of the theory for SK is summarized, leading to an expression for generalized SK that is applicable to both SK spectrometers and those not specifically designed for SK. We also give the means for computing both the SK estimator and thresholds for its application as a discriminator of RFI contamination. Tests of the performance of EOVSA as an SK spectrometer are shown to agree precisely with theoretical expectations, and the methods for configuring the correlator for correct SK operation are described.

[1]  F. Kitaura,et al.  Bayesian power-spectrum inference for large-scale structure data , 2009, 0911.2493.

[2]  Gordon J. Hurford,et al.  Radio Frequency Interference Excision Using Spectral‐Domain Statistics , 2007 .

[3]  Dale E. Gary,et al.  A Wideband Spectrometer with RFI Detection , 2010 .

[4]  Dale E. Gary,et al.  The Korean Solar Radio Burst Locator (KSRBL) , 2009 .

[5]  Gelu M. Nita,et al.  Spectral Kurtosis Statistics of Transient Signals , 2016, 1603.01158.

[6]  P. A. Fridman RFI excision using a higher order statistics analysis of the power spectrum , 2001 .

[7]  Dale E. Gary,et al.  Measurement of duration and signal‐to‐noise ratio of astronomical transients using a Spectral Kurtosis spectrometer , 2016 .

[8]  Gaël Chevallier,et al.  Harmonic component detection: Optimized Spectral Kurtosis for operational modal analysis , 2012 .

[9]  J. Antoni Fast computation of the kurtogram for the detection of transient faults , 2007 .

[10]  W. Baan,et al.  RFI mitigation methods in radio astronomy , 2001 .

[11]  J. Antoni The spectral kurtosis: a useful tool for characterising non-stationary signals , 2006 .

[12]  Gordon J. Hurford,et al.  A Subsystem Test Bed for the Frequency‐Agile Solar Radiotelescope , 2007 .

[13]  S. Pagnan,et al.  Modified frequency domain kurtosis for signal processing , 1994 .

[14]  Roger F. Dwyer,et al.  Detection of non-Gaussian signals by frequency domain Kurtosis estimation , 1983, ICASSP.

[15]  P. Ho Geoscience And Remote Sensing , 2014 .

[16]  Robert B. Randall,et al.  The spectral kurtosis: application to the vibratory surveillance and diagnostics of rotating machines , 2006 .

[17]  W. Alef,et al.  DiFX-2: A More Flexible, Efficient, Robust, and Powerful Software Correlator , 2011, 1101.0885.

[18]  Kaushal D. Buch,et al.  RFI mitigation techniques in radio astronomy , 2014, 2014 IEEE Geoscience and Remote Sensing Symposium.

[19]  Peter Fridman,et al.  Radio frequency interference mitigation with real-time FPGA digital signal processing , 2004, 2004 12th European Signal Processing Conference.

[20]  Valeriu Vrabie,et al.  Spectral kurtosis: from definition to application , 2003 .

[21]  K. Pearson Contributions to the Mathematical Theory of Evolution. II. Skew Variation in Homogeneous Material , 1895 .

[22]  Grant Hampson,et al.  Active adaptive antennas for radio astronomy: results from the R&D program on the Square Kilometer Array , 2000, Astronomical Telescopes and Instrumentation.

[23]  Sidharth Misra,et al.  RFI detection and mitigation for microwave radiometry with an agile digital detector , 2006, IEEE Transactions on Geoscience and Remote Sensing.

[24]  R. Karuppusamy,et al.  LEAP: the large European array for pulsars , 2015, 1511.06597.

[25]  Dan Werthimer,et al.  THE ALLEN TELESCOPE ARRAY SEARCH FOR ELECTROSTATIC DISCHARGES ON MARS , 2011, 1111.0685.

[26]  Dale E. Gary,et al.  Statistics of the Spectral Kurtosis Estimator , 2010 .