• Journal of Advanced Navigation Technology
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• v.26 no.4
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• pp.211-218
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• 2022

Continuous wave (CW) radar has the advantage of reliability and accuracy compared to other sensors such as camera and lidar. In addition, binarized neural network (BNN) has a characteristic that dramatically reduces memory usage and complexity compared to other deep learning networks. Therefore, this paper proposes binarized neural network based human identification and motion classification system using CW radar. After receiving a signal from CW radar, a spectrogram is generated through a short-time Fourier transform (STFT). Based on this spectrogram, we propose an algorithm that detects whether a person approaches a radar. Also, we designed an optimized BNN model that can support the accuracy of 90.0% for human identification and 98.3% for motion classification. In order to accelerate BNN operation, we designed BNN hardware accelerator on field programmable gate array (FPGA). The accelerator was implemented with 1,030 logics, 836 registers, and 334.904 Kbit block memory, and it was confirmed that the real-time operation was possible with a total calculation time of 6 ms from inference to transferring result.

• JSTS:Journal of Semiconductor Technology and Science
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• v.17 no.1
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• pp.110-119
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• 2017

This paper describes a CMOS image sensor (CIS) with dual correlated double sampling (CDS) and column-parallel analog-to-digital converter (ADC) and its measurement method using a field-programmable gate array (FPGA) integrated module. The CIS is composed of a $320{\times}240$ pixel array with $3.2{\mu}m{\times}3.2{\mu}m$ pixels and column-parallel 10-bit single-slope ADCs. It is fabricated in a $0.11-{\mu}m$ CIS process, and consumes 49.2 mW from 1.5 V and 3.3 V power supplies while operating at 6.25 MHz. The measured dynamic range is 53.72 dB, and the total and column fixed pattern noise in a dark condition are 0.10% and 0.029%. The maximum integral nonlinearity and the differential nonlinearity of the ADC are +1.15 / -1.74 LSB and +0.63 / -0.56 LSB, respectively.

• Journal of the Korean Institute of Telematics and Electronics D
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• v.36D no.5
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• pp.36-43
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• 1999

A new design of a Direct Digital Frequency Synthesizer(DDFS) is presented, where a pipelined Coordinate Rotate Digital Computer(CORDIC) circuit is employed to calculate amplitude values of all the phase angles of sinusoidal waveforms produced. a near-optimal number of pipeline stages is determined based on an error analysis of calculated amplitude values in terms of the number of bits. The DDFS was implemented using a field programmable gate array, yielding a stable operating frequency of 11.75MHz. The measurement results show higher resolution, faster operating speed and simpler fabrication process, compared to ROM-based counterparts. The CORDIC-based DDFS yields 5 times higher resolution than conventional ROM-based versions.

• Journal of the Korea Institute of Information Security & Cryptology
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• v.28 no.5
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• pp.1225-1231
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• 2018

FPGA-based system development is being developed as a form of outsourcing that shortens the development time and reduces the cost. Through the process, the risk of letting the hardware Trojan, which causes malfunctions, seep into the system also increases. Various detection methods are proposed for the issue; however, such type of hardware Trojans is inserted by modifying a bitstream directly and therefore, it is hard to detect with the suggested methods. To detect the type of hardware Trojans, it is essential to reverse-engineer the electric circuit implemented by bitstream to a distinguishable level. Specifically, it is important to reverse-engineer the routing information of the circuit that can identify the input-output flow of the signal. In this paper, we analyze the BIL bitstream reverse-engineering tool-chain that uses the algorithm, which retrieves the routing information from FPGA bitstream, and suggest the method to improve the tool-chain.

• Journal of the Institute of Electronics Engineers of Korea SD
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• v.46 no.2
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• pp.24-30
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• 2009

In this paper, the FPGA modem platform complying with 3GPP Release 7 eHSPA specifications and its regularized verification flow are proposed. The FFGA platform consists of modem board supporting physical layer requirements, MCU and DSP core embedded control board to drive the modem board, and peripheral boards for RF interfacing and various equipment interfaces. On the other hand, the proposed verification flow has been regularized into three categories according to the correlation degrees of hardware-software inter-operation, such as simple function test, scenario test call processing and system-level performance test. When it comes to real implementations, the emulation verification strategy for low power mobile SoC is also introduced.

• Nuclear Engineering and Technology
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• v.54 no.7
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• pp.2444-2452
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• 2022

The field-programmable gate array (FPGA) is gaining popularity in industrial automation such as nuclear power plant instrumentation and control (I&C) systems due to the benefits of having non-existence of operating system, minimum software errors, and minimum common reason failures. Separate functions can be processed individually and in parallel on the same integrated circuit using FPGAs in comparison to the conventional microprocessor-based systems used in any plant operations. The use of FPGAs offers the potential to minimize complexity and the accompanying difficulty of securing regulatory approval, as well as provide superior protection against obsolescence. Wireless sensor networks (WSNs) are a new technology for acquiring and processing plant data wirelessly in which sensor nodes are configured for real-time signal processing, data acquisition, and monitoring. ZigBee (IEEE 802.15.4) is an open worldwide standard for minimum power, low-cost machine-to-machine (M2M), and internet of things (IoT) enabled wireless network communication. It is always a challenge to follow the specific topology when different Zigbee nodes are placed in a large network such as a plant. The research article focuses on the hardware chip design of different topological structures supported by ZigBee that can be used for monitoring and controlling the different operations of the plant and evaluates the performance in Vitex-5 FPGA hardware. The research work presents a strategy for configuring FPGA with ZigBee sensor nodes when communicating in a large area such as an industrial plant for real-time monitoring.

• Journal of IKEEE
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• v.27 no.4
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• pp.624-629
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• 2023

Estimation of signal parameters via rotational invariance techniques (ESPRIT) is an algorithm that estimates the angle of a signal arriving at an array antenna using the shift invariance property of an array antenna. ESPRIT offers the good trade-off between performance and complexity. However, the ESPRIT algorithm still requires high-complexity operations such as covariance matrix and eigenvalue decomposition, so implementation with a hardware processor is essential to estimate the angle of arrival in real time. In addition, ESPRIT processors should have high performance. The performance is related to the number of antennas, and the number of antennas required for each application are different. Therefore, we proposed an ESPRIT processor that provides 2 to 8 variable antenna configurations to meet the performance and complexity requirements according to the applied field. The proposed ESPRIT processor was designed using the Verilog-HDL and implemented on a field programmable gate array (FPGA).

• Journal of Power Electronics
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• v.17 no.1
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• pp.56-66
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• 2017

Fast and accurate fault detection is the primary step and one of the most important tasks in fault tolerant converters. In this paper, a fast and simple method is proposed to detect and diagnosis the faulty cell in a cascaded H-bridge multilevel inverter under a short circuit fault. In this method, the reference voltage is calculated using switching control pulses and DC-Link voltages. The comparison result of the output voltage and the reference voltage is used in conjunction with active cell pulses to detect the faulty cell. To achieve this goal, the cell which is active when the Fault signal turns to "0" is detected as the faulty cell. Furthermore, consideration of generating the active cell pulses is completely described. Since the main advantage of this method is its simplicity, it can be easily implemented in a programmable digital device. Experimental results obtained with an 11-level inverter prototype confirm the effectiveness of the proposed fault detection technique. In addition, they show that the diagnosis method is unaffected by variations of the modulation index.

• Transactions of the Society of Information Storage Systems
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• v.1 no.2
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• pp.155-160
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• 2005

In this paper, the channel decoder promising reliable data retrieving in noisy holographic channel has been developed for holographic WORM(write once read many) system. It covers various DSP(digital signal processing) blocks, such as align mark detector, adaptive channel equalizer, modulation decoder and ECC(error correction code) decoder. The specific schemes of DSP are designed to reduce the effect of noises in holographic WORM(H-WORM) system, particularly in prototype of DAEWOO electronics(DEPROTO). For real time data retrieving, the channel decoder is redesigned for FPGA(field programmable gate array) based hardware, where DSP blocks calculate in parallel sense with memory buffers between blocks and controllers for driving peripherals of FPGA. As an input source of the experiments, MPEG2 TS(transport stream) data was used and recorded to DEPROTO system. During retrieving, the CCD(charge coupled device), capturing device of DEPROTO, detects retrieved images and transmits signals of them to the FPGA of hardware channel decoder. Finally, the output data stream of the channel decoder was transferred to the MPEG decoding board for monitoring video signals. The experimental results showed the error corrected BER(bit error rate) of less than $10^{-9}$, from the raw BER of DEPROTO, about $10^{-3}$. With the developed hardware channel decoder, the real-time video demonstration was possible during the experiments. The operating clock of the FPGA was 60 MHz, of which speed was capable of decoding up to 120 mega channel bits per sec.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.13 no.10
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• pp.4865-4885
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• 2019

We propose a FPGA based design that performs real-time power-efficient analysis of heterogeneous sensor data using adaptive ANN on edge gateway of smart military wearables. In this work, four independent ANN classifiers are developed with optimum topologies. Out of which human activity, BP and toxic gas classifier are multiclass and ECG classifier is binary. These classifiers are later integrated into a single adaptive ANN hardware with a select line(s) that switches the hardware architecture as per the sensor type. Five versions of adaptive ANN with different precisions have been synthesized into IP cores. These IP cores are implemented and tested on Xilinx Artix-7 FPGA using Microblaze test system and LabVIEW based sensor simulators. The hardware analysis shows that the adaptive ANN even with 8-bit precision is the most efficient IP core in terms of hardware resource utilization and power consumption without compromising much on classification accuracy. This IP core requires only 31 microseconds for classification by consuming only 12 milliwatts of power. The proposed adaptive ANN design saves 61% to 97% of different FPGA resources and 44% of power as compared with the independent implementations. In addition, 96.87% to 98.75% of data throughput reduction is achieved by this edge gateway.