PULSE COMPRESSION IN SEARCH RADAR

Pulse compression is a vvidely used method to maintain the range resolution ot radar while increasing the average power per pulse that can be placed on a target. Using all these methods a wideband modulation is added to the transmitted pulse and a filter matched to this modulation is used in the receiver. There are several kinds of these additional modulations, and each has different properties, therefore simulation of these methods is essential during design of modulation. In this article an overview of pulse compression techniques is given, the benefits and disadvantages of these methods are discussed. Biphase coded systems are detailed, because they are easy to implement with digital hardware. At the end, our simulation hardware and software tools are described, giving some illustrations from the results

Comparison of file sanitization techniques in usb based on average file entropy valves

Nowadays, the technology has become so advanced that many electronic gadgets are in every household today. The fast growth of technology today gives the ability for digital devices like smartphones and laptops to have a huge size of storage which is letting people to keep many of their infonnation like contact lists, photos, videos and even personal infonnation. When these infonnation are not useful anymore, users will delete them. However, the growth of technology also letting people to recover back data that has been deleted. In this case, users do not realise that their deleted data can be recovered and then used by unauthorized user. The data deleted is invisible but not gone. This is where file sanitization plays it role. File sanitization is the process of deleting the memory of the content and over write it with a different characters. In this research, the methods chosen to sanitize file are Write Zero, Write Zero Randomly and Write Zero Alternately. All of the techniques will overwrite data with zero. The best technique is chosen based on the comparison of average entropy value of the files after they have been overwritten. Write Zero is the only technique that is provided by many software like WipeFile and BitKiller. There is no software that provide Write Zero Randomly technique except for sanitizing disk using dd. As for that, Write Zero Randomly and proposed technique, Write Zero Alternately are developed using C programming language in Dev-C++. In this research, sanitization with Write Zero has the lowest average entropy value for text document (TXT), Microsoft Word (DOCX) and image (JPG) with 100% of data in the files undergone this technique have been zero-filled compared to Write Zero Randomly and Write Zero Alternately. Next, Write Zero Alternately is more efficient in tenns of average entropy by 4.64 bpB to its closest competitor which is Write Zero Randomly with 5.02 bpB. This shows that Write Zero is the best sanitization method. These file sanitization techniques are important to keep the confidentiality against unauthorized user

Nonlinear Harmonic Distortion of Complementary Golay Codes

Recent advances in electronics miniaturization have led to the development of low-power, low-cost, point-of-care ultrasound scanners. Low-cost systems employing simple bi-level pulse generation devices need only utilize binary phase modulated coded excitations to significantly improve sensitivity; however the performance of complementary codes in the presence of nonlinear harmonic distortion has not been thoroughly investigated. Through simulation, it was found that nonlinear propagation media with little attenuative properties can significantly deteriorate the Peak Sidelobe Level (PSL) performance of complementary Golay coded pulse compression, resulting in PSL levels of -62 dB using nonlinear acoustics theory contrasted with -198 dB in the linear case. Simulations of 96 complementary pairs revealed that some pairs are more robust to sidelobe degradation from nonlinear harmonic distortion than others, up to a maximum PSL difference of 17 dB between the best and worst performing codes. It is recommended that users consider the effects of nonlinear harmonic distortion when implementing binary phase modulated complementary Golay coded excitations.</p

Sidelobe Suppression in Pulse Compresssed Radar Signal

Radio Detection And Ranging, RADAR, is a system that is used to detect and track a target at distant location with its other features (like velocity, direction etc.). The system uses various techniques to enhance its efficiency in terms of different physical parameters. Pulse compression technique provides the radar designers with an ability to combine the benefits of low power transmitters and the larger pulse wavelength to maintain the energy content of the pulse, in turn, the process elevates the range detection ability of high duration pulses and the resolution capacity of short pulses. To enhance the bandwidth of the high duration pulses so that better range resolution capability can be achieved, modulation in frequency and phase is done. Frequency or phase modulation is employed to a long duration pulse before it is transmitted and the received pulse is then passed through a filter to get its energy accumulated into a short pulse. Usually, matched filter is a common choice for pulse compression. Due to the high sidelobe peaks associated with the mainlobe in the matched filter output, which is simply an ACF of the input pulse, they have the possibility of masking the weaker targets near the stronger ones. So, the high sidelobes are needed to be suppressed to avoid such circumstances. Normally, the matched filter output has the sidelobe level of -13.5dB which can be improved by the use of the techniques like adaptive filtering, weighting through the use of windows etc. The windowing technique, besides suppressing the sidelobe also reduces the SNR which leads to reduction in rate of false alarm rate. A stepped frequency train of LFM pulses is an efficient method to enhance the overall bandwidth of the signal and maintaining the instantaneous bandwidth at the same time. But they are associated with the ambiguous peaks whose peak value is similar to the mainlobe peak and are also known as the grating lobes which have the potential of masking the smaller targets. So, it becomes necessary to suppress or nullify them by proper adjustment of the design parameters.

Application of Soft Computing Techniques to RADAR Pulse Compression

Soft Computing is a term associated with fields characterized by the use of inexact solutions to computationally-hard tasks for which an exact solution cannot be derived in polynomial time. Almost contrary to conventional (Hard) computing, it is tolerant of imprecision, uncertainty, partial truth, and approximation to achieve tractability, robustness and low solution cost. Effectively, it resembles the Human Mind. The Soft Computing Techniques used in this project work are Adaptive Filter Algorithms and Artificial Neural Networks. An adaptive filter is a filter that self-adjusts its transfer function according to an optimizing algorithm. The adaptive filter algorithms used in this project work are the LMS algorithm, the RLS algorithm, and a slight variation of RLS, the Modified RLS algorithm. An Artificial Neural Network (ANN) is a mathematical model or computational model that tries to simulate the structure and/or functional aspects of biological neural networks. It consists of an interconnected group of artificial neurons and processes information using a connectionist approach to computation. Several models have been designed to realize an ANN. In this project, Multi-Layer Perceptron (MLP) Network is used. The algorithm used for modeling such a network is Back-Propagation Algorithm (BPA). Through this project, there has been analyzed a possibility for using the Adaptive Filter Algorithms to determine optimum Matched Filter Coefficients and effectively designing Multi-Layer Perceptron Networks with adequate weight and bias parameters for RADAR Pulse Compression. Barker Codes are taken as system inputs for Radar Pulse Compression. In case of Adaptive Filters, a convergence rate analysis has also been performed for System Identification and in case of ANN, Function Approximation using a 1-2-1 neural network has also been dealt with. A comparison of the adaptive filter algorithms has been performed on the basis of Peak Sidelobe Ratio (PSR). Finally, SSRs are obtained using MLPs of varying neurons and hidden layers and are then compared under several criteria like Noise Performance and Doppler Tolerance

Coded Signals for High Frequency Ultrasound Imaging

Degeneration of articular cartilage is known as a serious and painful knee disease seriously affecting people in all ages. The disease also marks the presence of osteoarthritis which is a complex musculoskeletal disorder. A successful assessment of the degeneration status is of great importance for estimating osteoarthritis progression, and thereby beneficial for implementing clinical treatments. Ultrasound has played a vital role in imaging the articular cartilage since it is capable of providing distinct information of important cartilage structures. However, various types of noise in ultrasound signals (e.g. clutter noise) are known to limit the quality of ultrasound images, especially at high frequencies where wave attenuation becomes severe. The possibility for improving the signal to noise ratio (SNR) by using coded signals is therefore the motivation behind this thesis, with the main objective is to investigate suitable codes and compression methods for cartilage imaging. The main focus of this thesis has been put on coded ultrasound signals and related signal processing methods. Transducers made from two different piezoelectric materials (PZT and PVDF) are used to image a thick cartilage sample. For each transducer, three different waveforms (Ricker wavelet, Gaussian chirped, and a 13-bit Barker) are used to excite the ultrasonic transducers. Two different wave compression methods (Matched filtering and Wiener filtering) are also explored to decode the signals received by transducers. Ahead of processing the received signals, a time calibration was used to compensate for sample tilting, yielding an improved precision in the phase/time delay. A maximum method and a center of mass method were used for calibration. The results from the experimental work show that both Chirp coded signals and Barker coded signals work well in improving the SNR, and that both transducers are able to produce high quality images of the cartilage sample. For the situations using coded excitation signals, however, the PZT transducer has high requirement for excitation repetition frequency because of its built-in delay line. Different time calibration methods have their own applicable conditions. Matched filter and Wiener filter both perform well for decoding, but the “noise” parameter in the Wiener filter has to be adjusted carefully to produce reasonable results