• The Journal of Korean Institute of Electromagnetic Engineering and Science
• /
• v.21 no.3
• /
• pp.321-330
• /
• 2010

In this paper, the theoretical background and the specific implementation method of a compressive receiver for RFID signal detection as well as the design method of DDL(Dispersive Delay Line) and chirp LO are described. DDL, which is one of the main components of the compressive receiver, is designed to have $13{\mu}s$ dispersive delay time and 6 MHz bandwidth using the SAW technique based on $LiNbO_3$ material. The chirp LO is designed using DDS(Direct Digital Synthesizer). Also the compressive receiver is fabricated to be installed into the RFID reader. Test results show the maximum frequency error of 25 kHz for single signal input, the receiver sensitivity of -44 dBm, and the maximum frequency error is 75 kHz for 6 multi-tone input signals. These results indicate that the fabricated compressive receiver is working well even in dense RFID operating environments.

• The Journal of Korean Institute of Electromagnetic Engineering and Science
• /
• v.21 no.5
• /
• pp.501-509
• /
• 2010

In this paper, the interference avoidance performance of the RFID reader with the compressive receiver was analyzed. In the environment of the multiple dense readers operating, the recognition rates of the conventional RFID reader and the proposed RFID reader with the compressive receiver were measured and compared. The recognition rate of the proposed reader was improved more than 2.7 times compared to the conventional reader. Especially, in the environment of two proposed RFID readers operating simultaneously, little degradation of the recognition rate was observed.

• The Journal of Korean Institute of Electromagnetic Engineering and Science
• /
• v.20 no.11
• /
• pp.1186-1193
• /
• 2009

In this paper, we propose DDS(Direct Digital Synthesizer) as a new implementation method of chirp LO(Local Oscillator) for compressive receiver applied for RFID signal detection in UHF band. We designed a receiver whose input frequency range is 908.5~914 MHz, DDL(Dispersive Delay Line) bandwidth is 6 MHz, and dispersion delay time is $13\;{\mu}s$. Chirp LO based on DDS is designed to meet $26\;{\mu}s$ sweep time and 12 MHz bandwidth for complete compressive mechanism. The measured 3 dB pulse width of the compressed signal of the fabricated receiver is 260 ns and the frequency resolution for simultaneous input signals is below 200 kHz. These performances indicate that the proposed chirp LO based on DDS and the compressive receiver is suitable for RFID signal detection in UHF band.

• Journal of electromagnetic engineering and science
• /
• v.6 no.2
• /
• pp.110-116
• /
• 2006

A reflective array type surface acoustic wave(SAW) dispersive delay line(DDL) with high time-bandwidth at the V/UHF-band is designed and fabricated for compressive receiver applications. This type of the SAW DDL has the properties of the relative bandwidth of 20 %, the time delay of 49.89 usec, the insertion loss of 38.5 dB and the side lobe rejection of 39 dB. In comparison with a commercial SAW DDL, the insertion loss, amplitude ripple and side lobe rejection are improved by $1.5dB{\pm}0.6dB$ and 4 dB respectively. Using the fabricated SAW DDL, the prototype of the compressive receiver is developed. It is composed of RF converter, fast tunable LO, chirp LO, A/D converter, signal processing unit and control unit. This prototype system shows a fine frequency resolution of below 30 kHz with high scan rate.

• Journal of the Korea Institute of Military Science and Technology
• /
• v.21 no.4
• /
• pp.437-446
• /
• 2018

This paper describes the real-time logic implementation of orthogonal matching pursuit(OMP) algorithm for compressive sensing digital receiver. OMP contains various complex-valued linear algebra operations, such as matrix multiplication and matrix inversion, in an iterative manner. Xilinx Vivado high-level synthesis(HLS) is introduced to design the digital logic more efficiently. The real-time signal processing is realized by applying dataflow architecture allowing functions and loops to execute concurrently. Compared with the prior works, the proposed design requires 2.5 times more DSP resources, but 10 times less signal reconstruction time of $1.024{\mu}s$ with a vector of length 48 with 2 non-zero elements.

• Smart Structures and Systems
• /
• v.20 no.1
• /
• pp.35-42
• /
• 2017

Recently, compressive sensing based data loss recovery techniques have become popular for Structural Health Monitoring (SHM) applications. These techniques involve an encoding process which is onerous to sensor node because of random sensing matrices used in compressive sensing. In this paper, we are presenting a model where the sampled raw acceleration data is directly transmitted to base station/receiver without performing any type of encoding at transmitter. The received incomplete acceleration data after data losses can be reconstructed faithfully using compressive sensing based reconstruction techniques. An in-depth simulated analysis is presented on how random losses and continuous losses affects the reconstruction of acceleration signals (obtained from a real bridge). Along with performance analysis for different simulated data losses (from 10 to 50%), advantages of performing interleaving before transmission are also presented.

• Smart Structures and Systems
• /
• v.22 no.2
• /
• pp.231-237
• /
• 2018

A significant data problem is encountered with condition monitoring because the sensors need to measure vibration data at a continuous and sometimes high sampling rate. In this study, compressive sensing approaches for condition monitoring are proposed to demonstrate their efficiency in handling a large amount of data and to improve the damage detection capability of the current condition monitoring process. Compressive sensing is a novel sensing/sampling paradigm that takes much fewer data than traditional data sampling methods. This sensing paradigm is applied to condition monitoring with an improved machine learning algorithm in this study. For the experiments, a built-in rotating system was used, and all data were compressively sampled to obtain compressed data. The optimal signal features were then selected without the signal reconstruction process. For damage classification, we used the Variance Considered Machine, utilizing only the compressed data. The experimental results show that the proposed compressive sensing method could effectively improve the data processing speed and the accuracy of condition monitoring of rotating systems.

• Journal of Information Processing Systems
• /
• v.11 no.3
• /
• pp.342-353
• /
• 2015

It is widely accepted that single carrier frequency division multiple access (SC-FDMA) is an excellent candidate for broadband wireless systems. Channel estimation is one of the key challenges in SC-FDMA, since accurate channel estimation can significantly improve equalization at the receiver and, consequently, enhance the communication performances. In this paper, we study the application of compressive sensing for sparse channel estimation in a SC-FDMA system. By skillfully designing pilots, their patterns, and taking advantages of the sparsity of the channel impulse response, the proposed system realizes channel estimation at a low cost. Simulation results show that it can achieve significantly improved performance in a frequency selective fading sparse channel with fewer pilots.

• Transactions of the Korean Society for Noise and Vibration Engineering
• /
• v.26 no.6_spc
• /
• pp.651-659
• /
• 2016

Condition monitoring (CM) encounters a large data problem due to sensors that measure vibration data with a continuous, and sometimes, high sampling rate. In this study, compressive sensing approaches for condition monitoring are proposed to demonstrate the efficiency in handling a large amount of data and to improve the damage detection capability of the current condition monitoring process. Compressive sensing is a novel sensing/sampling paradigm that takes much fewer samples compared to traditional sampling methods. For the experiments a built-in rotating system was used and all data were compressively sampled to obtain compressed data. Optimal signal features were then selected without the reconstruction process and were used to detect and classify damage. The experimental results show that the proposed method could improve the data processing speed and the accuracy of condition monitoring of rotating systems.

• The Journal of Korean Institute of Electromagnetic Engineering and Science
• /
• v.23 no.7
• /
• pp.797-804
• /
• 2012

In this paper, we propose a QAPM(Quadrature Amplitude Position Modulation) modulation using compressive sensing for the purpose of power efficiency improvement. QAPM modulation is a combination technique of QAM (quadrature amplitude modulation) and PPM(Pulse Position Modulation). Therefore it can decrease the transmission power and improve BER performance. Moreover, even if the band width is widened when the number of positions is increased, high sparsity characteristic caused by position number can be applied to compressive sensing technique. Compressive sensing has recently studied as a method that can be successfully reconstructed from the small number of measurements for sparse signal. Therefore, the proposed system can lower price of receiver by reducing sampling rate and has performance improved by using QAPM modulation. And the results are confirmed through simulations.