On the Resolution Improvement of Radar Target Identification with Filtering Antenna Effects

Bannawat, Lakkhana; Boonpoonga, Akkarat; Burintramart, Santana; Akkaraekthalin, Prayoot

doi:10.1155/2018/3405908

Cited by 10 publications

(9 citation statements)

References 15 publications

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“…The signals with the swept frequencies are transmitted by using a transmitting antenna to a chipless RFID tag and the backscattering signals are then received by using the receiving antenna. In order to mitigate the unwanted effects caused by the unflat antenna response and surrounding environments, calibration is introduced [15], [16]. According to Fig.…”

Section: A Calibrationmentioning

confidence: 99%

“…Fifth, the similarity measurement using the Mahalanobis distance is carried out in the space defined by the relevant feature (16) where Cr is a positive definite covariance matrix. Finally, the standardized Euclidean distance, often called the Seuclidean distance, can be calculated by (17) where Vr is the standard deviation.…”

Section: K-nearest Neighbor Algorithmmentioning

confidence: 99%

“…Instead of redesigning the tag, the calibration is also introduced in order to reduce the unwanted effect due to the container's characteristic and other surrounding environments. The main purpose of the use of the calibration is to mitigate the effect due to the frequency response variation and mutual coupling caused by the antenna [11], [16], [17]. In fact, calibration cannot completely remove the unwanted effect.…”

Section: Detection Of the Chipless Rfid Systemmentioning

confidence: 99%

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Robust Chipless RFID Detection Using Complex Natural Frequency Along With the k-Nearest Neighbor Algorithm

2021

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This paper proposes a detection technique for the chipless RFID system. In the proposed technique, the experiments for measuring the scattering responses of all possible tags were conducted first in a free-space anechoic chamber in order to avoid the effect of unwanted signals due to the environment. The responses of all possible tags were exploited in order to extract poles, including natural frequencies and damping factors, by using the short-time matrix pencil method. All extracted poles successively chosen from the late-time portions were exploited to create the decision boundary by using the k-nearest neighbor algorithm. In order to validate the robustness of the proposed detection technique, experiments with the chipless RFID system with tags attached to containers, i.e. parcel and plastic boxes, were conducted. Poles extracted from the response of the tag attached to a container were fed to the decision boundary for ID detection. The poles that had fallen into the region labeled as logic "1" were detected as logic "1," and vice versa. The experiment results showed that the attachment of the tags to the containers caused a change in the poles. The conventional technique using only natural frequencies has exhibited poor performance regarding tag ID detection. On the other hand, the proposed detection technique achieved a 100% detection rate, although the extracted poles used to detect the bit logic were disturbed by the container. The experimental results confirm the superiority of the proposed system over conventional chipless RFID detection. Moreover, the proposed technique can be considered a robust detection technique.

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Section: A Calibrationmentioning

confidence: 99%

Section: K-nearest Neighbor Algorithmmentioning

confidence: 99%

Section: Detection Of the Chipless Rfid Systemmentioning

confidence: 99%

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Robust Chipless RFID Detection Using Complex Natural Frequency Along With the k-Nearest Neighbor Algorithm

2021

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“…The captured data were fed to a computer in order to perform signal processing. Antenna calibration was performed in order to reduce the antenna effect resulting in the pulse dispersion [23]. A STMPM was then exploited to extract poles, which are tools for identifying the property of the soil.…”

Section: Ground-penetrating Radar-based Identificationmentioning

confidence: 99%

“…Thus, distinguishing soil type was determined through the Euclidean distance of the point values of the bulk density and the damping factor of each soil layer. The Euclidean distance was calculated from the smallest distance between each averaged point value [23]. The circle line stands for the region of distinguishing soil type differentiated by the soil layer, which was calculated by half of the Euclidean distance.…”

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Mapping the Physical and Dielectric Properties of Layered Soil Using Short-Time Matrix Pencil Method-Based Ground-Penetrating Radar

et al. 2020

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This paper presents the mapping of the physical and dielectric properties of layered soil by using ground-penetrating radar (GPR). Poles extracted from the GPR signals by using the short-time matrix pencil method, along with preprocessing, including filtering and antenna calibration, were employed in order to map the physical and dielectric properties of the layered soil. With the proposed system, the conjugate gradient method was also introduced to solve the time-domain inverse problem faced in the antenna calibration. Experimentations were conducted on four different days in Nakhon Ratchasima province in Thailand, which is a potential area for the occurrence of hardpan. These were done based on the hypothesis that the soil properties, such as water content and dielectric constant, should change when the experimentation day changes in spite of the experimentations in the same area. In the experimentations, soil samples were collected using a core method, and their physical and dielectric properties were measured by using a standard laboratory method and a commercial dielectric probe kit. The measured soil properties and extracted poles for each experiment and each soil layer are shown and analyzed. The results indicate that the real part of the dielectric constants, strongly related to water content, can be mapped using extracted natural frequency. In order to map the dielectric properties, i.e. the water content and dielectric constants of the layered soil, the experimental results were fitted to 2 nd-order polynomial curve. The largest regression value of the fitted curve was 0.9994. The bulk density, which is a physical property of the soil, distinguishes the soil type here differentiated by different soil layers. According to the experimental results, the hardpan occurred at the second soil layer because its bulk density was higher than 1.8 g/cm 3. The bulk density was mapped by extracted poles, including damping factors and natural frequencies. INDEX TERMS dielectric property, permittivity estimation, layered soil, ground-penetrating radar, GPR, short-time matrix pencil method

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Antennas and Wave Propagation

Asplund¹,

Astély²,

Butovitsch³

et al. 2020

Advanced Antenna Systems for 5G Network Deployments

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On the Resolution Improvement of Radar Target Identification with Filtering Antenna Effects

Cited by 10 publications

References 15 publications

Robust Chipless RFID Detection Using Complex Natural Frequency Along With the k-Nearest Neighbor Algorithm

Robust Chipless RFID Detection Using Complex Natural Frequency Along With the k-Nearest Neighbor Algorithm

Mapping the Physical and Dielectric Properties of Layered Soil Using Short-Time Matrix Pencil Method-Based Ground-Penetrating Radar

Antennas and Wave Propagation

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