Temporal and spatial evolution of C2 in laser induced plasma from graphite target

Laser ablation of graphite has been carried out using 1.06mm radiation from a Q-switched Nd:YAG laser and the time of flight distribution of molecular C2 present in the resultant plasma is investigated in terms of distance from the target as well as laser fluences employing time resolved spectroscopic technique. At low laser fluences the intensities of the emission lines from C2 exhibit only single peak structure while beyond a threshold laser fluence, emission from C2 shows a twin peak distribution in time. The occurrence of the faster velocity component at higher laser fluences is explained as due to species generated from recombination processes while the delayed peak is attributed to dissociation of higher carbon clusters resulting in the generation of C2 molecule. Analysis of measured data provides a fairly complete picture of the evolution and dynamics of C2 species in the laser induced plasma from graphite.

Development of Time - Frequency Techniques for Sonar Applications

Sonar signal processing comprises of a large number of signal processing algorithms for implementing functions such as Target Detection, Localisation, Classification, Tracking and Parameter estimation. Current implementations of these functions rely on conventional techniques largely based on Fourier Techniques, primarily meant for stationary signals. Interestingly enough, the signals received by the sonar sensors are often non-stationary and hence processing methods capable of handling the non-stationarity will definitely fare better than Fourier transform based methods.Time-frequency methods(TFMs) are known as one of the best DSP tools for nonstationary signal processing, with which one can analyze signals in time and frequency domains simultaneously. But, other than STFT, TFMs have been largely limited to academic research because of the complexity of the algorithms and the limitations of computing power. With the availability of fast processors, many applications of TFMs have been reported in the fields of speech and image processing and biomedical applications, but not many in sonar processing. A structured effort, to fill these lacunae by exploring the potential of TFMs in sonar applications, is the net outcome of this thesis. To this end, four TFMs have been explored in detail viz. Wavelet Transform, Fractional Fourier Transfonn, Wigner Ville Distribution and Ambiguity Function and their potential in implementing five major sonar functions has been demonstrated with very promising results. What has been conclusively brought out in this thesis, is that there is no "one best TFM" for all applications, but there is "one best TFM" for each application. Accordingly, the TFM has to be adapted and tailored in many ways in order to develop specific algorithms for each of the applications.