Automated Detection of Clouds in Satellite Imagery

The UART(Universal Asynchronous Receiver and transmitter) controller is the key component of the serial communications subsystem of a computer. The UART takes bytes of data and transmits the individual bits in a sequential fashion. SPI is a common technology used nowadays for communication with peripheral devices where we want to transfer data speedily and with in real time constraints. In the existing work data acquisition system for underground has been designed for counters triggered by surface detectors and they have used UART and SPI protocol for the communication with dedicated processor. In this paper we have used Xilinx 12.4i and SPARTAN 3E FPGA to implement the whole system. The hyper terminal is used to check the UART protocol and 12 bit DAC MCP4922 used for check SPI protocol. The proposed work can provides both protocol effectively for the wireless serial communication. These serial protocols mainly used in Zigbee wireless technology.

In this paper, a universal asynchronous receiver and transmitter (UART) are described, which is basically a serial data transmission protocol used in digital circuit applications. The architecture of the UART transmitter has a baud rate generator, parity generator, transmitter finite state machine (FSM) and parallel in serial out register (PISO). UART receiver has a baud rate generator, negative edge detector, parity checker, receiver finite state machine (FSM) and serial in parallel out (SIPO) register. The baud rate generator of both transmitter and receiver is the same, so the baud rate of transmitter/receiver is the same. Baud rate generator is the same as the frequency divider circuit. The data frame of the UART transmitter is 1 start bit, 8 transmits data bits, 1 parity bit and 1 stop bit. The baud rate of the transmitter and receiver is 4 Mbps using the system clock of 64 MHz’s. Implementation, simulation, and synthesis is done Xilinx Vivado 2016.2 version tool. The design is verified using simulated waveform and synthesized on the FPGA Zed board.

The communications link in a space program is a crucial point for upgrading its performance by handling data between spacecraft bus and payloads, because spacecraft`s missions are related to the data handling mechanism using communications ports such as a controlled area network bus (CAN Bus) and a universal asynchronous receiver and transmitter (UART). The NEXTSat-1 has a lot of communications ports for performing science and technology missions. However, the top level system requirements for the NEXTSat-1 are mass and volume limitations. Normally, the communications for units shall be conducted by using point to point link which require more mass and volume to interconnect. Thus, our approach for the novel communications link in the NEXTSat-1 program is to use CAN and serializer and deserializer low voltage differential signal (SerDesLVDS) to meet the system requirements of mass and volume. The CAN Bus and SerDesLVDS were confirmed by using already defined communications link for our missions in the NEXTSat-1 program and the analysis results were reported in this study in view of data flow and size analysis.

Many Internet of Things (IoT) applications are emerging and evolving rapidly thanks to widespread open-source hardware platforms. Most of the high-end open-source IoT platforms include built-in peripherals, such as the universal asynchronous receiver and transmitter (UART), pulse width modulation (PWM), general purpose input output (GPIO) ports and timers, and have enough computation power to run embedded operating systems such as Linux. However, each IoT platform has its own way of configuring peripherals, and it is difficult for programmers or users to configure the same peripheral on a different platform. Although diverse open-source IoT platforms are widespread, the difficulty in programming those platforms hinders the growth of IoT applications. Therefore, we propose an easy and convenient way to program and configure the operation of each peripheral using a user-friendly Web-based software framework. Through the implementation of the software framework and the real mobile robot application development along with it, we show the feasibility of the proposed software framework, named SoEasy.

Design of a micro-UART for SoC application

Multi-Party Computation (MPC) is a technique enabling data from several sources to be used in a secure computation revealing only the result while protecting the original data, facilitating shared utilization of data sets gathered by different entities. The presence of Field Programmable Gate Array (FPGA) hardware in datacenters can provide accelerated computing as well as low latency, high bandwidth communication that bolsters the performance of MPC and lowers the barrier to using MPC for many applications. In this work, we propose a Secret Sharing FPGA design based on the protocol described by Araki et al. We compare our hardware design to the original authors' software implementations of Secret Sharing and to work accelerating MPC protocols based on Garbled Circuits with FPGAs. Our conclusion is that Secret Sharing in the datacenter is competitive and when implemented on FPGA hardware was able to use at least 10× fewer computer resources than the original work using CPUs.

Wireless sensor network (WSN) is a group of interconnected sensor nodes that work wirelessly to capture the information of surroundings. The routing of the network is a challenging task. The routing of WSN is classified as proactive, reactive, and hybrid. Adhoc on-demand distance vector (AODV) routing is an example of reactive routing based on the demand route formations among different nodes in the network. The research article emphasizes the design and simulation of the AODV routing hardware chip using very-high-speed integrated circuit hardware description language (VHDL) programming in Xilinx integrated synthesis environment (ISE) 14.7 software. The performance of the chip is studied based on the field-programmable gate array (FPGA) hardware parameters such as slices, lookup table (LUTs), input/output block (IOB), flip-flops, and memory for the different configurations of the network (N = 10, 20 ….100). The delay and frequency are also estimated on the Virtex-5 FPGA. The performance of the WSN with AODV routing is also analyzed based on the packet delivery ratio, throughput, delay, and control overhead. The simulation test cases verified the 8-bit, 64-bit, and 128-bit data communication within the nodes.

Hardware-in-the-Loop (HWIL) simulation is becoming increasingly important for cost-effective testing of imaging infrared systems. DSTO is developing real-time scene generation and image processing capabilities within its HWIL simulation programs, based on the application of COTS desktop PCs equipped with Graphics Processing Unit (GPU) cards, and including limited use of Field Programmable Gate Arrays (FPGAs). GPUs and FPGAs are high-performance parallel computing machines but are fundamentally different types of hardware. To determine which hardware type should be used to implement a real-time solution of a given application, a methodology is required to expose the concurrency within the problem and to structure the problem in a way that can be mapped to the hardware types. In this paper we use parallel programming patterns to compare the architectures of recent generation GPUs and FPGAs. We demonstrate the decomposition of a parallel application and its implementation on GPU and FPGA hardware and present preliminary results.

Because of the recent slowdown in silicon technology and increasing power consumption of hardware, several dedicated architectures have been proposed in High Performance Computing (HPC) to exploit the limited number of transistors in a chip with low power consumption. Although Field-Programmable Gate Array (FPGA) is considered as one of the promising technologies to realize dedicated hardware, it is difficult for non-domain experts to program FPGAs due to the gap between thier applications and hardware-level programming models for FPGAs. In this paper, we propose a C/C++ based programming framework, C2SPD, to describe stream processing on FPGA. It uses SPGen, a dataflow High Level Synthesis (HSL) tool, as the FPGA backend. C2SPD can program FPGAs by adding directives to serial code, and the compiler translates it into optimized SPGen code. The range of application is limited in C2SPD due to its domain-specific approach. However it can generate efficient hardware on FPGAs when the programming model matches the target application. 2D-stencil computation is written in C2SPD to evaluate the performance of our C2SPD compiler implementation. 2 lines of the C2SPD directives are added into the serial C code to generate FPGA hardware. The Optimized FPGA hardware achieves 175.41 GFLOPS by using 256 stream cores, which is 220 times faster than a single stream core.

The demand for low-power devices has significantly increased across various applications, highlighting the crucial role of VLSI technology due to its unique capabilities. Traditional data acquisition systems often utilize embedded and ASIC devices, but these devices typically fail to meet the low-power requirements of modern applications. As an alternative, Field Programmable Gate Array (FPGA)-based solutions have emerged as effective candidates for data acquisition systems. This paper presents the implementation of a data acquisition system (DAQ) on a Basys 3 FPGA board utilizing both MicroBlaze and Zynq processors. Temperature sensors, ultrasonic sensors, and OLED peripherals are interfaced and executed on FPGA hardware. The Xilinx Vivado software serves as the design tool to integrate hardware components and processors, employing Verilog as the hardware description language. Performance evaluation confirms that FPGA devices effectively handle DAQ applications at a clock frequency of <tex xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">$\mathbf{1 0 0 ~ M H z}$</tex>.

Median filtering is an important approach in digital image processing for noise elimination. An improved median filtering algorithm (IMFA) is proposed which can be implemented with only 17 comparisons and 6 clocks delay for 3×3 median filtering mathematical model based on field programmable gate array (FPGA). The algorithm benefits from the parallel processing and pipelining structure of FPGA hardware. At first, the characteristics, basic operational principle and computing process of the IMFA are presented. And then the algorithm using modular technique and top-down design flow methodology with Verilog HDL are programed. At last, some simulation verifications for the algorithm by ModelSim and experimental verification on FPGA hardware platform are carried out. The IMFA can get a large number of data throughput and more quickly processing speed and less hardware resources than similar filtering algorithms.

The soft computing algorithms are being nowadays used for various multi input multi output complicated non linear control applications. This paper presented the development and implementation of back propagation of multilayer perceptron architecture developed in FPGA using VHDL. The usage of the FPGA (Field Programmable Gate Array) for neural network implementation provides flexibility in programmable systems. For the neural network based instrument prototype in real time application. The conventional specific VLSI neural chip design suffers the limitation in time and cost. With low precision artificial neural network design, FPGA have higher speed and smaller size for real time application than the VLSI design. The challenges are finding an architecture that minimizes the hardware cost, maximizing the performance, accuracy. The goal of this work is to realize the hardware implementation of neural network using FPGA. Digital system architecture is presented using Very High Speed Integrated Circuits Hardware Description Language (VHDL)and is implemented in FPGA chip. MATLAB ANN programming and tools are used for training the ANN. The trained weights are stored in different RAM, and is implemented in FPGA. The design was tested on a FPGA demo board. Keywords- Backpropagation, field programmable gate array (FPGA) hardware implementation, multilayer perceptron, pressure sensor, Xilinx FPGA.

Building the machines that advance scientific knowledge is one of the most significant challenges of our time. So-called Big Science instruments are unique; the expertise required to build them is multidisciplinary, and few countries can build and maintain them. Since resources and budgets are not unlimited, these require efficient solutions. Big Science machines take a decade to plan, a decade to build, and at least a decade to operate. One such machine is the largest fusion reactor project, ITER, which promises to be the next step in fusion research and has a big challenge in system integration. To mitigate the integration effort, ITER has invested in standardization, both in software and hardware, introducing standard instrumentation software named Nominal Device Support (NDSv3); Micro Telecommunication Computing Architecture (MTCA) as the long-term hardware standard choice, and EPICS as a general-purpose distributed control system. These control systems are essential in the management of the facility. They provide functions such as communication protocols, process management, monitoring, alarms, and human-machine interfaces. But also, more advanced access to databases or data acquisition systems. The latter is typically managed by a Field Programmable Gate Array (FPGA), of which facilities can easily have thousands of these FPGAs managing millions of signals within the control system environment. Nevertheless, these FPGA data acquisition (DAQ) systems continue to be labor-intensive. Standardized, modular, and open-source frameworks have been proposed to solve this problem, however, the FPGA programming expertise requirement remained. This thesis proposes a complete technology stack that considers these DAQ systems from the control system to the hardware. It provides a methodology using the Open Computing Language (OpenCL) to reduce the FPGA programming effort. The FPGA devices are programmed using C/C++-like environments, which are much simpler than traditional Hardware Description Languages (HDLs). The software, named IRIO-OpenCL, is written in C++ following ITER's NDSv3 model, which abstracts and generalizes the development of software device drivers and simplifies the interface to EPICS. IRIO-OpenCL is specifically designed to simplify the integration of intelligent instrumentation systems, allowing the integration of algorithms into the FPGA without modifying large parts of the supporting library. The MTCA standard was chosen to maintain modularity. The chassis backplane connects to the devices via Ethernet and PCIe, enabling standard communications. The Advanced Mezzanine Card is the typical MTCA FPGA-based DAQ carrier board. It connects the FPGA to the chassis backplane and typically provides FPGA Mezzanine Connectors (FMCs) for plugging in analog-to-digital (ADC) carrier boards. An ADC connected via the FMC interface samples the analog signals passed to the OpenCL processing kernels. Using OpenCL, the FPGA kernels communicate with the host machine in a standardized way. To demonstrate the applicability of this methodology, reference problems were selected from the literature and implemented, both with traditional and deep learning (DL) solutions. The methodology elaborates on connecting the OpenCL kernels for any use case, and the results show examples of kernel sets. The neutron flux measurement problem is solved at 1GS/s in real time using pulse counting and Campbell techniques, using 40% of the target Arria10 FPGA. The DL application example is based on a neutron/gamma discrimination neural network (NN) that achieves a classification rate of up to 1.3 MEvents/s using less than 25% of the target resource. RESUMEN Construir máquinas que avancen el conocimiento científico es uno de los desafíos más significativos de nuestro tiempo. Los instrumentos de la llamada Big Science son únicos; las competencias requeridas para su construcción son multidisciplinares, y pocos países pueden construirlos y mantenerlos. Dado que los recursos y presupuestos no son ilimitados, estos requieren soluciones eficientes. Las máquinas de Gran Ciencia tardan una década en planificarse, una década en construirse y al menos una década en operarse. Una de estas máquinas es el proyecto del reactor de fusión más grande, ITER, que promete ser el siguiente paso en la investigación de fusión y presenta un gran desafío en la integración de sistemas. Para mitigar el esfuerzo de integración, ITER ha invertido en estandarización, tanto en software como en hardware, introduciendo un software de instrumentación estándar llamado Nominal Device Support v3 (NDSv3); Micro Telecommunication Computing Architecture (MTCA) como la elección estándar de hardware a largo plazo, y EPICS como un sistema de control distribuido de propósito general. Estos sistemas de control son esenciales en la gestión de la instalación ya que proporcionan funciones como protocolos de comunicación, gestión de procesos, monitorización, alarmas e interfaces de usuario, además de acceso avanzado a bases de datos o sistemas de adquisición de datos. Este último es típicamente gestionado por un Field Programmable Gate Array (FPGA), de los cuales las instalaciones pueden tener fácilmente miles de unidades gestionando millones de señales dentro del entorno del sistema de control. Estos sistemas de adquisición de datos (DAQ) con FPGA siguen requiriendo programación experta y laboriosa. Se han propuesto marcos estandarizados, modulares y de código abierto para resolver este problema, sin embargo, la necesidad de experiencia en programación FPGA no se ha podido eludir. Esta tesis propone una pila de tecnologías que considera estos sistemas DAQ desde el sistema de control hasta el hardware. Proporciona una metodología utilizando el Open Computing Language (OpenCL) para reducir el esfuerzo de programación FPGA. Los dispositivos FPGA se programan utilizando entornos similares a C/C++, que son mucho más simples que los Lenguajes de Descripción de Hardware (HDL) tradicionales. El software, llamado IRIO-OpenCL, está escrito en C++ siguiendo el modelo de NDSv3 de ITER, que abstrae y generaliza el desarrollo de controladores de dispositivos de software y simplifica la interfaz con EPICS. IRIO-OpenCL está específicamente diseñado para simplificar la integración de sistemas de instrumentación inteligentes, permitiendo la integración de algoritmos en el FPGA sin modificar grandes partes de la biblioteca de soporte. El estándar MTCA fue elegido para mantener la modularidad. El backplane del chasis se conecta a los dispositivos a través de Ethernet y PCIe, habilitando comunicaciones estándar. La Advanced Mezzanine Card es la placa portadora DAQ FPGA típica de MTCA, que conecta el FPGA al backplane del chasis y típicamente proporciona FPGA Mezzanine Connectors (FMC) para conectar placas con conversores analógico-digitales (ADC). Un ADC conectado a través de la interfaz FMC muestrea las señales analógicas pasadas a los núcleos de procesamiento OpenCL. Utilizando OpenCL, los núcleos FPGA se comunican con la máquina anfitriona de una manera estandarizada. Para demostrar la aplicabilidad de esta metodología, se seleccionaron e implementaron problemas de referencia de la literatura, tanto con soluciones tradicionales como de Deep Learning (DL). La metodología elabora ejemplos de conexión de núcleos OpenCL para cualquier caso de uso, y los resultados muestran ejemplos de conjuntos de núcleos. El problema de medición del flujo de neutrones se resuelve a 1GS/s en tiempo real utilizando técnicas de conteo de pulsos y Campbell, utilizando el 40% del objetivo FPGA Arria10. El ejemplo de aplicación DL se basa en una red neuronal para la discriminación neutrones/gammas que logra una tasa de clasificación de hasta 1.3 MEventos/s utilizando menos del 25% de la FPGA objetivo. LABURPENA Ezagutza zientifikoa aurreratzen duten makinak eraikitzea gure garaiko erronka garrantzitsuenetako bat da. Big Science deritzonaren makinak bakarrak dira; beharrezko esperientzia diziplina anitzekoa da, eta herrialde gutxik eraiki eta mantendu ditzakete. Baliabideak eta aurrekontuak mugagabeak ez direnez, konponbide eraginkorrak behar dira. Zientzia Handi makinak hamarkada bat behar dute diseinatuak izateko, hamarkada bat eraikitzeko eta gutxienez hamarkada bat jarduteko. Makina horietako bat fusio-erreaktore handienaren proiektua da, ITER, fusio-ikerketan hurrengo urratsa izango dena eta sistemak integratzeko erronka handia aurkezten duena. Integrazio-ahalegina arintzeko, ITERek estandarizazioan inbertitu du, bai softwarean bai - eta EPICS helburu orokorreko kontrol-sistema banatua. Kontrol-sistema horiek funtsezkoak dira instalazioa kudeatzeko. Komunikazio-protokoloak, prozesuen kudeaketa, monitorizazioa, alarmak eta pertsona-makina interfazeak bezalako funtzioak ematen dituzte, datubaseetarako edo datuak eskuratzeko sistemetarako sarbide aurreratua izateaz gain. Azken hori "Field Programmable Gate Array" (FPGA) batek kudeatzen du, milaka FPGA konektatuz makina bakoitzean eta kontrol-sistemaz milioika seinale kudeatuz. FPGA duten datuak eskuratzeko sistemek (DAQ) programazio aditua eta neketsua eskatzen jarraitzen dute. Problema hori ebazteko marko estandarizatuak, modularrak eta kode irekikoak proposatu dira, hala ere, FPGA hardware programazio espezializatuaren beharra ezin izan da ukatu. Tesi honek DAQ sistema hauek kontrol sistematik hardwareraino kontsideratuz teknologia bilduma bat programazio-ahalegina murrizten du. FPGA gailuak C/C++ antzeko inguruneak erabiliz programatzen dira, - OpenCL izenekoa, C++n idatzita dago, ITERren "Nominal Device Support v3" (NDSv3) eredua jarraituz. Honek software-gailuen garapena diseinu abstraktu eta orokorrez EPICSekiko interfazea sinplifikatzen du. IRIOOpenCL berariaz diseinatuta dago instrumentazio-sistema adimendunen integrazioa sinplifikatzeko, eta algoritmoak FPGAn integratzea ahalbidetzen du, software zati handiak aldatu gabe. Modularitateari eusteko, MTCA estandarra aukeratu da. Txasisaren backplanea Ethernet eta PCIe bidez konektatzen da gailuetara, komunikazio estandarrak gaituz. "Advanced Mezzanine Card" MTCAren ohiko DAQ FPGA plaka eramailea da. FPGA txasisaren backplanera konektatzen du eta, normalean, "FPGA Mezzanine Connectors"ak (FMC) ditu plaka bihurgailu analogiko-digitalak (ADC) konektatzeko. ADCak, FMC interfazearen bidez konektatuta, OpenCL prozesatze-nukleoetara igarotako seinale analogikoak bihurtzen ditu. OpenCL erabiliz, FPGA nukleoak ordenagailuarekin modu estandarizatuan komunikatzen dira. Metodologia horren aplikagarritasuna egiaztatzeko, erreferentziazko adibideak literaturatik hautatu eta nukleoen konexio-adibideak egiten ditu, edozein kasutan erabiltzeko, eta emaitzek nukleo multzoen adibideak erakusten dituzte. Neutroi-fluxuaren neurketak 1GS/s-ko ebazten dira real time errendimenduaz, pultsuak eta Campbell zenbatzeko teknikak erabiliz, Arria10 FPGAren % 40 erabiliz. Azkenik, DL aplikazioaren adibidea, neutroi/gamma sailkapena, sare neuronal batean oinarritzen da, eta FPGAren baliabideen % 25 baino gutxiago erabiliz 1.3 MSailkapen/s sailkapen-tasa lortzen du.

This paper presents an approach of model-based design for implementing a digital communication system on a field programmable gate array (FPGA) for a software defined radio (SDR). SDR is a popular prototyping platform for wireless communication systems due to its flexibility and utility. A traditional SDR system performs nearly all computations and signal processing tasks on the host computer, and then sends the waveform to the RF front end. For complex algorithms or high data rate, the host computer becomes the processing bottleneck and FPGA is often employed as a hardware accelerator. This paper demonstrates the procedure of using model-based design for SDR targeted on FPGA hardware. A complete digital communication system, including a transmitter with convolutional encoder and a receiver with Viterbi decoder, is implemented on an FPGA-based SDR platform and validated by over-the-air demonstration. Synchronization algorithms, such as carrier frequency offset, phase offset, and time recovery, are also optimized for hardware efficiency.

The concept of Software Defined Radio (SDR) has become very popular in molding of the Digital Communication System due to its flexibility and advantages. It is form of a radio where the conventional hardware components such as the modulators, mixers, filters etc is replaced by software implementation on personal computers. For complicated algorithms, the Field Programmable Gate Array (FPGA) is often utilized as a hardware accelerator while the host computer becomes the processing tailback. My work exhibits the operation of SDR targeted on FPGA hardware (Avnet's ZedBoard Zynq-7000 and Analog Device AD9361). This is achieved by using Xilinx's System Generator programming and Matlab environment.We have illustrated our work by realizing ADS-B Aircraft Tracking System, by which it can detect the pre captured as well as live aircrafts.