Digital Architectures for UWB Beamforming Using 2D IIR Spatio-Temporal Frequency-Planar Filters

A design method and an FPGA-based prototype implementation of massively parallel systolic-array VLSI architectures for 2nd-order and 3rd-order frequency-planar beam plane-wave filters are proposed. Frequency-planar beamforming enables highly-directional UWB RF beams at low computational complexity compared to digital phased-array feed techniques. The array factors of the proposed realizations are simulated and both high-directional selectivity and UWB performance are demonstrated. The proposed architectures operate using 2's complement finite precision digital arithmetic. The real-time throughput is maximized using look-ahead optimization applied locally to each processor in the proposed massively-parallel realization of the filter. From sensitivity theory, it is shown that 15 and 19-bit precision for filter coefficients results in better than 3% error for 2nd- and 3rd-order beam filters. Folding together with Ktimes multiplexing is applied to the proposed beam architectures such that throughput can be traded for K-fold lower complexity for realizing the 2-D fan filter banks. Prototype FPGA circuit implementations of these filters are proposed using a Virtex 6 xc6vsx475t-2ff1759 device. The FPGA-prototyped architectures are evaluated using area (A), critical path delay (T), and metrics AT and AT2. The L2 error energy is used as a metric for evaluating fixed-point noise levels and the accuracy of the finite precision digital arithmetic circuits

Digital and Mixed Domain Hardware Reduction Algorithms and Implementations for Massive MIMO

Emerging 5G and 6G based wireless communications systems largely rely on multiple-input-multiple-output (MIMO) systems to reduce inherently extensive path losses, facilitate high data rates, and high spatial diversity. Massive MIMO systems used in mmWave and sub-THz applications consists of hundreds perhaps thousands of antenna elements at base stations. Digital beamforming techniques provide the highest flexibility and better degrees of freedom for phased antenna arrays as compared to its analog and hybrid alternatives but has the highest hardware complexity. Conventional digital beamformers at the receiver require a dedicated analog to digital converter (ADC) for every antenna element, leading to ADCs for elements. The number of ADCs is the key deterministic factor for the power consumption of an antenna array system. The digital hardware consists of fast Fourier transform (FFT) cores with a multiplier complexity of (N log2N) for an element system to generate multiple beams. It is required to reduce the mixed and digital hardware complexities in MIMO systems to reduce the cost and the power consumption, while maintaining high performance. The well-known concept has been in use for ADCs to achieve reduced complexities. An extension of the architecture to multi-dimensional domain is explored in this dissertation to implement a single port ADC to replace ADCs in an element system, using the correlation of received signals in the spatial domain. This concept has applications in conventional uniform linear arrays (ULAs) as well as in focal plane array (FPA) receivers. Our analysis has shown that sparsity in the spatio-temporal frequency domain can be exploited to reduce the number of ADCs from N to where . By using the limited field of view of practical antennas, multiple sub-arrays are combined without interferences to achieve a factor of K increment in the information carrying capacity of the ADC systems. Applications of this concept include ULAs and rectangular array systems. Experimental verifications were done for a element, 1.8 - 2.1 GHz wideband array system to sample using ADCs. This dissertation proposes that frequency division multiplexing (FDM) receiver outputs at an intermediate frequency (IF) can pack multiple (M) narrowband channels with a guard band to avoid interferences. The combined output is then sampled using a single wideband ADC and baseband channels are retrieved in the digital domain. Measurement results were obtained by employing a element, 28 GHz antenna array system to combine channels together to achieve a 75% reduction of ADC requirement. Implementation of FFT cores in the digital domain is not always exact because of the finite precision. Therefore, this dissertation explores the possibility of approximating the discrete Fourier transform (DFT) matrix to achieve reduced hardware complexities at an allowable cost of accuracy. A point approximate DFT (ADFT) core was implemented on digital hardware using radix-32 to achieve savings in cost, size, weight and power (C-SWaP) and synthesized for ASIC at 45-nm technology

A New Wideband, Fully Steerable, Decametric Array at Clark Lake

A fully steerable, decametric array for radio astronomy is under construction at the Clark Lake Radio Observatory near Borrego Springs, California. This array will be a T of 720 conical spiral antennas (teepee-shaped antennas, hence the array is called the TPT), 3.0 km by 1.8 km capable of operating between 15 and 125 MHz. Both its operating frequency and beam position will be adjustable in less than one millisecond, and the TPT will provide a 49-element picture around the central beam position for extended source observations. Considerable experience was gained in the operation of completed portions of the array, and successful operation of the final array is assured. The results are described of the tests which were conducted with the conical spirals, and the planned electronics and data processing systems are described

Wavelet based similarity measurement algorithm for seafloor morphology

Thesis (S.M. in Naval Architecture and Marine Engineering and S.M. in Mechanical Engineering)--Massachusetts Institute of Technology, Dept. of Mechanical Engineering, 2006.Includes bibliographical references (leaves 71-73).The recent expansion of systematic seafloor exploration programs such as geophysical research, seafloor mapping, search and survey, resource assessment and other scientific, commercial and military applications has created a need for rapid and robust methods of processing seafloor imagery. Given the existence of a large library of seafloor images, a fast automated image classifier algorithm is needed to determine changes in seabed morphology over time. The focus of this work is the development of a robust Similarity Measurement (SM) algorithm to address the above problem. Our work uses a side-scan sonar image library for experimentation and testing. Variations of an underwater vehicle's height above the sea floor and of its pitch and roll angles cause distortion in the data obtained, such that transformations to align the data should include rotation, translation, anisotropic scaling and skew. In order to deal with these problems, we propose to use the Wavelet transform for similarity detection. Wavelets have been widely used during the last three decades in image processing. Since the Wavelet transform allows a multi-resolution decomposition, it is easier to identify the similarities between two images by examining the energy distribution at each decomposition level.(cont.) The energy distribution in the frequency domain at the output of the high pass and low pass filter banks identifies the texture discrimination. Our approach uses a statistical framework, involving fitting the Wavelet coefficients into a generalized Gaussian density distribution. The next step involves use of the Kullback-Leibner entropy metric to measure the distance between Wavelet coefficient distributions. To select the top N most likely matching images, the database images are ranked based on the minimum Kullback-Leibner distance. The statistical approach is effective in eliminating rotation, mis-registration and skew problems by working in the Wavelet domain. It's recommended that further work focuses on choosing the best Wavelet packet to increase the robustness of the algorithm developed in this thesis.by Ilkay Darilmaz.S.M.in Naval Architecture and Marine Engineering and S.M.in Mechanical Engineerin

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Digital Filters

The new technology advances provide that a great number of system signals can be easily measured with a low cost. The main problem is that usually only a fraction of the signal is useful for different purposes, for example maintenance, DVD-recorders, computers, electric/electronic circuits, econometric, optimization, etc. Digital filters are the most versatile, practical and effective methods for extracting the information necessary from the signal. They can be dynamic, so they can be automatically or manually adjusted to the external and internal conditions. Presented in this book are the most advanced digital filters including different case studies and the most relevant literature

Digital Filters and Signal Processing

Digital filters, together with signal processing, are being employed in the new technologies and information systems, and are implemented in different areas and applications. Digital filters and signal processing are used with no costs and they can be adapted to different cases with great flexibility and reliability. This book presents advanced developments in digital filters and signal process methods covering different cases studies. They present the main essence of the subject, with the principal approaches to the most recent mathematical models that are being employed worldwide