Proceedings with Extended Abstracts (single PDF file) - Radio ...

MULTITAPER SPECTRAL ANALYSIS OF ATMOSPHERIC RADARSIGNALSV.K.Anandan (1)* , T. Rajalakshmi (2) , G. Ramachandra Reddy (2) , C.J.Pan (1)(1) Institute of Space Science, National Central University, Chung-Li, 32054, TaiwanEmail: anandanvk@hotmail.com*On leave from National MST Radar Facility, Gadanki, India(2) Department of EEE, SV University, Tirupati, AP, India, 517 502AbstractMultitaper spectral analysis using sinusoidal tapers has been carried out on backscatteredsignals received from the troposphere and lower stratosphere by the Gadankimesosphere-stratosphere-troposphere (MST) radar under various conditions. The sine tapershave much narrower main lobe and much higher side lobes. Thus they achieve a smaller biasdue to smoothing by the main lobe, but at the expense of side lobe suppression. The analysisis carried out on different data sets. Comparison of study is made with single taper tounderstand the relative merits of the processing under the scheme. The result shows thatmultitaper analysis gives better signal to noise ratio or higher detectability. The signals arebetter identified in the multitaper analysis in both sets of data. The spectral analysis throughmultitaper and single-taper is subjected to study of consistency in measurements. Resultshows that multitaper is having very low variance compared to single taper estimators.IntroductionTapering is another name for the data windowing operation in the time domain. Singletaper smoothed spectrum estimates are plagued by a trade-off between the variance of theestimate and the bias caused by spectral leakage [Park et al., 1987]. Applying a taper toreduce bias, discards data, increasing the variance of the estimate. Using a taper alsounevenly samples the record. Single-taper estimators, which are less affected by leakage, notonly have increased variance but also can misrepresent the spectra of non-stationary data. Soas long as only a single data taper is used, there will be a trade-off between the resistance tospectral leakage and the variance of a spectral estimate.Thomson [1982] introduced the multitaper spectral analysis technique and applicationfound in various scientific fields[Park et al., 1987]. First, the data are multiplied by not one,but several leakage-resistant tapers. This yields several tapered time series from one record.Taking the DFTs of each of these time series, several “eigen spectra” are produced whichare averaged to form a single spectral estimate. The central premise of this multitaperapproach is that if the data tapers are properly designed orthogonal functions, then, undermild conditions, the spectral estimates would be independent of each other at everyfrequency. Averaging would reduce the variance while proper design of full - length windowswould reduce bias and loss of resolution.Reidel and Siderenko [1995] proposed a set of orthonormal taper, which containharmonically related sinusoidal tapers. These tapers are called sinusoidal tapers or minimumbias tapers. The discrete analogs of the continuous time minimum bias tapers are calledsinusoidal tapers. The n th sinusoidal taper is given by2 ⎛ πkn⎞v k( n)= sin⎜⎟ ; n = 1,2,…,N ; k=1,2,…,K (1)N + 1 ⎝ N + 1⎠Identifying the signal and computing the three low order spectral moments is centralto the problem of extracting information from the Doppler spectrum of the Mesosphere-Stratosphere-Troposphere (MST) radar signal. The straightforward method of analyzing theMST radar spectral data is based on identifying the most prominent peak of the Dopplerspectrum for each range gate and computing the three low order spectral moments using theexpressions given by Woodman [1985]. Since MST radar signals are characterized by rapidlyfalling signal-to-noise ratio (SNR), the identification of atmospheric signals and in a weak130