Detection and tracking for radar simulation using MATLAB

The objective of the project is to simulate the real time Radar detection and tracking operations using MATLAB software. Radar system use modulated waveforms and directive antennas to transmit electromagnetic energy into a specific volume in space to search for targets. Objects (targets) within a search volume will reflect portions of this energy (radar returns or echoes) back to the radar. These echoes are then processed by radar receiver to extract target information such as range. Velocity, angular position, and other target identifying characteristics. The project mainly concentrates on the radar displays and different radar types to collect the information of the flying objects, such as the range, speed, distance, angles. The display types are A-scope, B-scope, C-scope, PPI, and RHI, which are used in modern radars. While others are either obsolete or are found only in very specialized applications. Signals displayed on these scopes can be raw video, synthetic video (detected video) or computer-generated symbols. The radar types consider in the project are CWT (Continuous Wave Transmission), Pulse, Doppler, and MTI (Moving Target Indicator). For each display, all the values related to the object are calculated in different patterns and graphs for the corresponding formulated values and angles

Design and Simulation of Wave Shaping Schemes for a Virtual Data Communication and Impaired Link Environment System for Advanced ICT Education

Design and Simulation of Waves Shaping Schemes for a Virtual Data Communication and Impaired Link Environment System for Advanced ICT Education is aimed at providing a simulator for the performance of digital filtering of signals for data communication experiments with the aid of MATLAB. A fundamental aspect of signal processing is filtering. Filtering involves the manipulation of the spectrum of a signal by passing or blocking certain portions of the spectrum, depending on the frequency of those portions. This work is designed to provide a flexible platform for teaching the operations of waves shaping schemes (lowpass, bandpass and highpass) modelled over an additive white Gaussian noise (AWGN) channel. Keywords – Lowpass, Bandpass, Highpass, MATLAB

Josephson effect in mesoscopic graphene strips with finite width

We study Josephson effect in a ballistic graphene strip of length $L$ smaller than the superconducting coherence length and arbitrary width $W$. We find that the dependence of the critical supercurrent $I_{c}$ on $W$ is drastically different for different types of the edges. For \textit{smooth} and \textit{armchair} edges at low concentration of the carriers $I_{c}$ decreases monotonically with decreasing $W/L$ and tends to a constant minimum for a narrow strip $W/L\lesssim1$. The minimum supercurrent is zero for smooth edges but has a finite value $e\Delta_{0}/\hbar$ for the armchair edges. At higher concentration of the carriers, in addition to this overall monotonic variation, the critical current undergoes a series of peaks with varying $W$. On the other hand in a strip with \textit{zigzag} edges the supercurrent is half-integer quantized to $(n+1/2)4e\Delta_{0}/\hbar$, showing a step-wise variation with $W$.Comment: 4 pages, 3 figure

Inversion of seismic reflection data from the Gialo Field, Sirte Basin

This project is concerned with the development of software to invert seismic reflection data for acoustic impedance, with application to the YY-reservoir area in Gialo Field, Sirte Basin. The problem was that of inverting post-stack seismic reflection data from two seismic lines into impedance profiles. The main input to the inversion process is an initial guess, or initial earth model, of the impedance profile defined in terms of parameters. These parameters describe the impedance and the geometry of the number of layers that constitute the earth model. Additionally, an initial guess is needed for the seismic wavelet, defined in the frequency domain using nine parameters. The inversion is an optimisation problem subject to constraints. The optimisation problem is that of minimising the error energy function defined by the sum of squares of the residuals between the observed seismic trace and its prediction by the forward model for the given earth model parameters. To determine the solution we use the method of generalised linear inverses. The generalised inverse is possible only when the Hessian matrix, which describe the curvature of error energy surface, is positive definite. When the Hessian is not definite, it is necessary to modify it to obtain the nearest positive definite matrix. To modify the Hessian we used a method based on the Cholesky factorisation. Because the modified Hessian is positive definite, we need to find the generalised inverse only once. But we may need to restrict the step-length to obtain the minimum. Such a method is a step-length based method. A step-length based method was implemented using linear equality and inequality constraints into a computer program to invert the observed seismic data for impedance. The linear equality and inequality constraints were used so that solutions that are geologically feasible and numerically stable are obtained. The strategy for the real data inversion was to first estimate the seismic wavelet at the well, then optimise the wavelet parameters. Then use the optimum wavelet to invert for impedance and layer boundaries in the seismic traces. In the three real data examples studied, this inversion scheme proved that the delineation of the Chadra sands in Gialo Field is possible. Better results could be obtained by using initial earth models that properly parameterise the subsurface, and linear constraints that are based on well data. Defining the wavelet parameters in the time domain may prove to be more stable and could lead to better inversion results