The latitude of filament bands at the sunspot minimum and the activity level in the two following 11-year solar cycles

The zonal structure of the distribution of filaments is considered. The mean latitudes of two filament bands are calculated in each solar hemisphere at the minima of the sunspot cycle in the period 1924–1986: middle latitude _{2, m} and low latitude _{1, m} . It is shown that the mean latitude of the filament band _{2, m} at the minimum -m of the cycle correlates, with = 0.94, with the maximum - M sunspot area S(M) and maximum Wolf number W(M) in the succeeding solar cycle M. It is shown that the mean latitude of the low-latitude filament band _{1, m} is linearly dependent on the mean latitude filament band _{2, m + 1} at the succeeding minimum. We found a correlation of the latitude of the low-latitude filament band _{1, m} with the maximum sunspot area in the M + 1 cycle. This enables us to predict the power of two succeeding 11-year solar cycles on the basis of the latitude of filament bands at the minimum of activity, 1985–1986: W(22) - 205 ± 10, W(23) - 210 ± 10. The importance of the relationships found for theory and applied aspects is emphasized. An attempt is made to interpret the relationships physically.     

3D Reconstrution with Rational Function Model

Rational Function Model (RFM) is the alternate sensor Model to the rigorous sensor model that allows end user to perform sensor-independent photogrammetric processing. Nowadays, commercial off-the-shelf (COTS) digital photogrammetric work stations have incorporated RFM as a method for image restitution. It is technically applicable to all types of airborne and space borne sensors. In this paper, we describe the derivations of the algorithmic procedure for third order inverse and forward RFM method for 3-D reconstruction. Model accuracy is evaluated for aerial image, TK-350 Russian image and IRS-1C PAN image. The results ensure that properly constructed RFM are accurate enough to be used in place of the original rigorous models. The test results are reported and summarised.     

Mapping of suspended sediments using site specific seasonal algorithms

This article reports a preliminary work in which two site specific seasonal algorithms have been proposed for estimating the suspended sediments concentration (SSC) from the digital numbers recorded on Indian Remote sensing Satellite, IRS-P4 Ocean Colour Monitor (OCM) sensor. For estimation of SSC, the proposed algorithms utilize dark pixel deduction atmospheric correction technique. The computations are performed with respect to north east monsoon phase situations of Palk Strait coastal stretch. The algorithms performance was satisfactory during the north east monsoon period. Although the results obtained cannot be generalized, we suggest that the authority of proposed algorithms can be extended to other seasons with the addition of more temporal experimental validation data sets and with numeric constants adjusted to present existing conditions. (As this area was severely affected by Tsunami, it may have dissimilar conditions at present).     

A study on the polarimetric properties of various features using SIR-C data

Spaceborne Imaging Radar (SIR-C) data acquired over Gujarat, India in 1994 were processed and analysed using differnet techniques applicable to polarimetric SAR data such as polarization signatures, polarization index, decomposition of the signal and polarization phase difference and limited groundtruth data. It has been observed that multi-frequency polarimetric data enhances the potential of retrieving geo-physical parameters. The polarization signatures are found to vary with the nature of the target. Target decomposition of the returned signal will be useful for the classification of various features. Polarization Phase Difference (PPD) gives good information about the vegetation parameters.     

GPS signal acquisition using the repeatability of successive code phase measurements

This paper introduces a new method for GPS signal acquisition, which is based on the repeatability of successive code phase measurements and the M-of-N search algorithm. The performance of the proposed method in terms of probability of signal detection is similar to that of traditional methods, except that the calculation of the probability of detection does not rely on the noise distribution or the Carrier-to-Noise ratio (C/N₀). The code phase repeatability-based method is presented along with equations for probability of detection and probability of false detection. If the distribution of the noise is known, it also provides an estimate of the C/N₀. The proposed method is illustrated for coherent and non-coherent acquisition and C/N₀ estimation.     

Automated Target Detection and Discrimination Using Constrained Kurtosis Maximization

Exploiting hyperspectral imagery without prior information is a challenge. Under this circumstance, unsupervised target detection becomes an anomaly detection problem. We propose an effective algorithm for target detection and discrimination based on the normalized fourth central moment named kurtosis, which can measure the flatness of a distribution. Small targets in hyperspectral imagery contribute to the tail of a distribution, thus making it heavier. The Gaussian distribution is completely determined by the first two order statistics and has zero kurtosis. Consequently, kurtosis measures the deviation of a distribution from the background and is suitable for anomaly/target detection. When imposing appropriate inequality constraints on the kurtosis to be maximized, the resulting constrained kurtosis maximization (CKM) algorithm will be able to quickly detect small targets with several projections. Compared to the widely used unconstrained kurtosis maximization algorithm, i.e., fast independent component analysis, the CKM algorithm may detect small targets with fewer projections and yield a slightly higher detection rate.     

A Microwave Tomographic Approach for Nondestructive Testing of Dielectric Coated Metallic Surfaces

A microwave imaging method for nondestructive testing of perfectly conducting surfaces beyond a layered media is presented. The method is an adaptation of the surface reconstruction approach by Yapar et al. to the present problem. It is based on the analytical continuation of the measured data to the surface under test through a special representation of the scattered field in terms of Fourier transform and Taylor expansion. Then the problem is reduced to the solution of a nonlinear equation which is solved iteratively via the Newton method and regularization in the least squares sense. Numerical simulations show that defects as small as lambda/500 can be recovered through the presented algorithm.