Wireless data acquisition system with signal processing and control modules within Field Programmable Gate Array (FPGA)

A portable, low power, digital spectroscopy for CdZnTe (CZT) detector is designed and described in this paper. Its readout electronics is implemented with waveform sampling, Flash-based FPGA (Field Programmable Gate Array) and USB (universal serial bus) technique. The CZT detector, with an effective thickness of 3mm and a diameter of 5mm, is mounted on the same PCB board with high voltage supply module and low noise preamplifier. Current signal from CZT detector is integrated by a charge sensitive amplifier and then shaped by a CR-RC 3 shaper. The shaped signal is sampled by a 12-bit ADC and then processed by an IGLOO Flash-based low power FPGA in a digital module. A USB interface is adopted both for low voltage and high voltage power supply, and communicating with a host computer, which results in a portable solution with maximum power consumption of about 450mW. In the host computer, a graphic user interface (GUI) software is developed based on Labwindows/CVI, for real-timely displaying the energy spectrum or waveform of shaping signal. Test results showed that the dynamic range of the spectroscopy can reach 240fC (equivalent to about 7 MeV energy deposition in CZT detector) and the intrinsic noise (in RMS) for the electronics is less than 0.3fC (equivalent to about 8.7 keV).

The use of an automated Data Acquisition System (DAS) is very important in testing and measurement systems. The desire is extremely high in the DAS with high speed, multi-channel, and large capacity, so research in this area becomes very significant. The growing problem in DAS is to acquire the data with the required data rate and store data onto the on-chip memory. Microcontroller, microprocessor or Digital Signal Processors (DSP) devices can be programmed as a DAS, but these devices comprise problems, such as slower data acquisition rates, nonavailability of sufficient on-chip memory, etc. To overcome these above drawbacks, this paper provides an approach to design and develop DAS based on the Field Programmable Gate Array (FPGA). To acquire the data from Analog to Digital Converter (ADC) to FPGA, an Inter Integrated Circuit (I2C) serial communication protocol is used. I2C master communication protocol is designed and developed using VHDL with the Quartus II version 13.1, and the I2C master protocol is implemented in cyclone III FPGA. FPGA is acting as a master controller. DAS with the FPGA will provide the better acquisition results compared to the existing acquisition system.

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.

Nowadays the need for dealing with ultra-high speed Analog to Digital Converter (ADC) is becoming more and more common, from Telecommunications to Precise Instrumentation, every application is increasing the analog to digital interface data rate. The ultra-high sampling rate of the ADCs demands the use of advanced acquisition techniques as well as the latest technology available. The utilization of dedicated Application Specific Integrated Circuit (ASIC) is an expensive solution to deal with the very high throughput from the ADC and its lack of flexibility is a huge drawback. On the other hand, the technology, the architecture and the state-of-the art of the current Field Programmable Gate Arrays (FPGAs) make them especially suitable to act as interface between an ultra-high speed ADC and a data processing unit. Another extra advantage is the reconfigurability of the FPGAs, they can be quickly adapted to different ADCs or different data processing units. The purpose of this paper is to present a practical approach to interface an ultra-high speed 8-bit ADC, MAX104, from Maxim Integrated Circuit, which performs digitalization of the input signal with a sampling rate of 1Gsps and a commercial and popular FPGA, the Virtex2 Pro, from Xilinx Corporation. Once the ADC digital data have been acquired, then they can be processed by either the dedicated FPGA Digital Signal Processing (DSP) blocks, or the FPGA embedded processors or just send the data out to a PC for later processing. Hence, the proposed method of implementation can be used as front-end of a wide range of applications.

This study proposed a novel Field Programmable Gate Array (FPGA)-based 32-channel data acquisition system to acquire and process Electroencephalography (EEG) signal. The data acquisition system utilized PYNQ-Z1 board, which was equipped with a Xilinx ZYNQ XC7Z020-1CLG400C All Programmable System-on-Chip (APSoCs) that offered high performance embedded system because of the combination between the flexibility and versatility of the programmable logic (PL) and the high-speed embedded processor or programmable system (PS). As the core of the data acquisition system, the FPGA collected, processed, and stored the data based on Front-End Analog to Digital Converter (ADC) ADS1299EEG-FE. The communication protocol used in the data acquisition system was Serial Peripheral Interface (SPI) with daisy-chain configuration. For the signal processing part, a 5th-order Butterworth bandpass filter and Fast Fourier Transform (FFT) has been implemented directly on the PYNQ’s Overlay. The overlay was configurable FPGA design that extend the system from the PS of the ZYNQ to the PL, enabling us to control directly the hardware platform using Python running in the PS. The mean accuracy error obtained from validation result of the developed system was 1.34% and the Total Harmonic Distortion (THD) performance criterion resulting in 0.0091%, both of them validated with NETECH MiniSIM EEG Simulator 330. The comparison between the developed system and Neurostyle NS-EEG-D1 System acquiring the same EEG data shows correlation parameter gradient of 0.9818, y-intercept with -0.1803, and R squared of 0.9742 based on the least square analysis. The parameter above indicated that the developed system was adequate enough, if not on a par, with the commercialized, medical grade EEG data acquisition system Neurostyle NS-EEG-D1 as the system assured and maintained accuracy with higher sampling frequency.

In nuclear and high-energy physics experiments, data acquisition systems handle vast amounts of data from thousands of detectors and electronic channels, often reaching hundreds of terabits per second. While modern field programmable gate arrays (FPGAs) offer high-speed transceivers capable of processing such data, a mismatch can arise: individual analog-to-digital converters (ADCs) process lower data rates than FPGA transceivers can efficiently handle. This inefficiency leads to unnecessary usage of more powerful and expensive FPGAs, thus increasing system costs. This paper addresses this issue by proposing a link aggregator method for ADC readout. The solution integrates five universal link aggregator devices within an FPGA mezzanine card (FMC) board, enabling 1-to-1, 2-to-1, 3-to-1, or 4-to-1 multiplexing. The system optimizes FPGA resource utilization with support for up to 40 optical or copper inputs (2.5 Gbps per link) and a 10-line aggregated output (10 Gbps max) via a Vita57.1 FMC connector. A low-cost, low-power FPGA manages the mezzanine board as an intelligent standalone device. This approach significantly reduces hardware requirements and enhances cost-efficiency in high-performance data acquisition systems.

Compared with the four-phase optical structure, the grating encoder based on two-phase optical structure reduces the number of optical devices used in the system and makes the system more compact. Due to the high requirements for realtime and parallel processing of algorithm solution, the powerful parallel computing ability of Field Programmable Gate Array (FPGA) and customized hardware acceleration algorithm are needed to improve the real-time performance. In the previous research, the displacement signal generated by the grating encoder can be input into the FPGA through analog to digital converter (ADC) sampling, and then complete self-designed filter filtering, phase correction and displacement solution. In this paper, further, the ADC sampling rate adjustable interface is added to the FPGA, the global signal and the dc offset remove algorithm is added, and the displacement solution results in the form of fixed-point number are output to the host computer through the MicroBlaze (MB) soft core. MB core can realize process control and interface conversion on FPGA, and use a small amount of logic resources to replace the functions of MCU and DSP of traditional embedded measurement system, so as to further improve the integration of the instrument. A series of experiments are carried out on the two-phase FPGA platform. ADC sampling rate is 200ksps, 8-Channel synchronous parallel sampling, FPGA system clock frequency is 200MHz. The linear displacement table is set to drive the measurement grating at different displacement speeds, and the total stroke is set to 10mm. The FPGA real-time displacement solution platform is tested. The experimental results show that FPGA obtains accurate displacement solution results under different speed tests. In the test of 2 mm/s, the maximum cumulative displacement measurement error is 5um, which shows the real-time performance and accurate displacement solution performance of FPGA platform.

Present days witnessed extensive use of Analog to Digital Converters (ADC) in different fields of applications, as an interface between the analog world and the digital world. However, in most cases, external ADCs are employed to meet the purpose. This eventually makes the system bulky, power-consuming, complex, and costly. Implementation of reconfigurable ADC programmed inside Field-Programmable Gate Array (FPGA) could reduce the system cost and power consumption substantially. Furthermore, this will make the system simple as it does not require any external circuitry for the conversion of analog input data into digital form for processing. Thus, in this paper, a multichannel reconfigurable ADC is designed, with an additional feature of time multiplexing for efficient data acquisition. The design is being implemented using 100MHz FPGA clock frequency thus can achieve a sampling rate of 100 MS/s with a resolution of 10bit for 0-2.5V signal range. The FPGA resource utilization for the complete ADC model consists of 341 FFs and 265 LUTs, with total on-chip power consumption of 14.428 W. The proposed system can also be implemented for different analog signal from transducers, depending upon the demand and requirement of sensing parameters the data collection time can be varied for transducer to transducer.

Usage of digital receivers in today's radar and electronic warfare applications is becoming more common. Analog to digital converters (ADC) used in digital receivers play a significant role in the performance of these receivers. Therefore, it is very important to obtain performance analysis of possible ADC's under different conditions such as different temperature etc. before making final decision of the ADC to be used in the digital receiver. It is obvious that it would be very helpful to get results of integration of different ADC's with the existing system and to test ADC's under different conditions that may not exist on data sheets. For this reason, a Field Programmable Gate Array (FPGA) based board is designed in order to gather digital output of ADC being evaluated and a graphical analysis software responsible for analyzing gathered digital output is developed. Developed infrastructure enables us to compare performances of different ADC's in the same system and in same conditions by replacing only the ADC to be analyzed.

In the context of implementing more control and data processing capabilities in new electronic cards at the European Organization for Nuclear Research (CERN), the Smartfusion2 Flash-based Reprogrammable Field Programmable Gate Array (FPGA) has been tested in the CHARM radiation facility at CERN. The CHARM facility was configured to offer a representative radiation environment of the CERN's Large Hardon Collider (LHC) accelerator. The FPGAs were tested during three irradiation campaigns. The observed radiation effects include Single Event Upsets (SEU), Single Event Transients (SET), Single Event Latch-ups (SEL), Single Event Functional Interrupts (SEFI) and failures due to Total Ionizing Radiation (TID). The use of this FPGA is linked to the implementation of appropriate Finite State Machine (FSM) encoding, Printed Circuit Board (PCB) design, and automated power cycling that are here discussed. The suitability of the FPGA in harsh environments and critical applications such as the cryogenics electronics infrastructure in the LHC tunnel is also discussed.

Software defined radio (SDR) is a vast and emerging field that requires the design of various technologies such as antenna, RF, IF, and digital baseband subsystems. Among all these technologies, data converters that convert signals between analog and digital domains are highly crucial. On the other hand field programmable gate arrays (FPGAs) based platforms are being preferred for evaluating and implementing the digital communication concepts due to their programmability and reconfigurability. As a result they are well suited for the design of SDR technology. In this research work, we develop a platform where high-speed data converters are interfaced with high performance FPGAs. Interfaces are designed for analog-to-digital convertors (ADC) and digital-to-analog convertors (DAC) to communicate with FPGAs. For the interface design between ADC and FPGA, a double data rate and a low voltage differential signalling based serial output is adopted. And, for the interface design between DAC and other FPGA, parallel complementary metal oxide semiconductor outputs are used. To reconfigure the modes and parameters of the data convertors, serial peripheral interface data controllers have been designed. We have through simulations evaluated the performance of our designed interfaces between data convertors and FPGAs.

With the rapid development of electronic science and technology, the signal frequency that engineers need to measure becomes higher and higher. Limited by the analog-to-digital converter (ADC) sampling rate and Nyquist sampling theorem, the digital oscilloscope can only measure waveform in a very limited range of frequency in real-time sampling mode. Therefore, it is necessary to introduce an equivalent sampling technique to increase the ability of the oscilloscope to measure higher frequency signals. In this paper, a random equivalent sampling reconstruction method based on field programmable gate array (FPGA) is proposed. In the random equivalent sampling mode, multiple sets of samples collected by the ADC are buffered in the FPGA, and the stretched circuit measures the time interval $\Delta$t between each set of trigger signals and the rising edge of the first sampling clock. Through these samples as well as the $\Delta$t in each group, the waveform can be reconstructed in FPGA, and then this reconstructed waveform can be read and displayed by the upper computer. The waveform refreshing rate of the random equivalent sampling can be greatly improved by this kind of reconstruction inside a FPGA.

Recently, digital Intermediate Frequency (IF) waveform generators and receivers are introduced in modern radar systems to reduce the cost, size, and achieve better performance. Moreover, digital IF waveform generators achieve the requirements of high resolution and complex modulation schemes. Digital receivers have better sensitivity, wider dynamic range and lower noise Figure than analog receivers. Digital IF waveform generators and receivers work well in conjunction with a high-speed Analog to Digital Converters (ADC) and Digital to Analog Converters (DAC). In this paper, the design and implementation of high-speed data acquisition circuits (ADC and DAC) to generate and acquire IF waveforms are presented. Different modulated waveforms are generated digitally using Field Programmable Gate Array (FPGA). The corresponding digital receiver, including digital phase detection and matched filtering, is designed and implemented on the same FPGA chip. Design and implementation of a Printed Circuit Board (PCB) including FPGA chip and its required circuitry are introduced. The proposed design is simulated using Computer-Aided Design (CAD) tools and verified experimentally through laboratory testing.

A new highly integrated data acquisition (DAQ) system for a combined, APD-based, dual-modality PET/CT scanner, implementing both analog and digital electronics on the same board, has been fabricated and tested. The DAQ system was designed to achieve high-precision (<1 ns) coincidence detection in PET and high-rate event counting in CT imaging using the same detectors and electronics. One DAQ board holds 64 parallel detector channels that can be sampled directly at the output of the charge-sensitive preamplifiers (CSP) at a rate of 100 MHz with free-running analog-to-digital converters (ADC) from Maxim. Digital signal processing is performed in field programmable gate arrays (FPGAs) from Xilinx. Independent 500 V voltage regulators are mounted on board for optimum biasing of individual APDs coupled to phoswich detectors. The DAQ board has been fabricated on a 12 copper layers printed circuit board (PCB). The low-noise analog front-end is directly interfaced on board through differential CSP outputs to the high-speed digital circuits for optimum coupling and noise immunity. The board shows excellent electrical characteristics with all circuitry powered up, featuring a mean signal to noise and distortion ratio (SINAD) of 47.7 dB over all 64 channels when supplied with a 10 MHz sine waveform at its input. Initial performance characteristics with BGO/LSO phoswich detectors are reported.

Abstract. Easy-to-use data acquisition methods are required for variable-rate irrigation (VRI) decision support systems. Plant canopy temperature is related to plant water stress. Plant height is useful as an indicator of plant health conditions and can be used to estimate yield potential. Therefore, measurements of plant canopy temperature and plant height coupled with spatial information in the field can be used for determining VRI water application depths. A center-pivot-mounted wireless data acquisition (WDAQ) system was developed to collect plant canopy temperature and plant height data in the field. Each WDAQ unit consisted of a GPS receiver, programmable data logger, infrared temperature sensor, ultrasonic distance sensor, solar power supply, and wireless data transmitter/receiver. The system included two WDAQ units installed on a four-span center-pivot VRI system. One unit was mounted at the middle of the third span, and the other was mounted at the middle of the fourth span from the pivot. The infrared temperature sensors were used to detect the canopy temperature, while the ultrasonic distance sensors were used to measure plant height. The WDAQ system was designed to continuously and simultaneously measure plant canopy temperature and plant height and record the spatial coordinates at each measurement location as the center pivot moved around the field. Data collected were wirelessly transferred to a receiver for data processing. This WDAQ system has been tested and evaluated in the field for two years. Test results indicated that the WDAQ system was able to record approximately 3,200 measurements from each sensor in one pivot circle (360°). The measurement error of the ultrasonic distance sensor was 0.2 to 3 cm in a measurement range of 14 to 209 cm, and the sensor-measured plant heights were strongly correlated with manually tape-measured plant heights in soybean and cotton crops (r2 = 0.97). Combined with the spatial information, measurements of plant height and crop canopy temperature were used to generate plant height and crop canopy temperature maps. Spatial variabilities of plant height and canopy temperature across the field could be identified from the maps and used in irrigation research. The WDAQ system has great potential for automatic creation of VRI prescription maps and plant-based irrigation scheduling. Keywords: Canopy temperature, Irrigation scheduling, Plant height, Sensors, Variable-rate irrigation.