The Experts below are selected from a list of 113802 Experts worldwide ranked by ideXlab platform
Toru Sato - One of the best experts on this subject based on the ideXlab platform.
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super resolution uwb radar imaging algorithm based on extended capon with Reference Signal optimization
IEEE Transactions on Antennas and Propagation, 2011Co-Authors: Shouhei Kidera, Takuya Sakamoto, Toru SatoAbstract:Near field radar employing ultrawideband (UWB) Signals with its high range resolution has great promise for various sensing applications. It enables non-contact measurement of precision devices with specular surfaces like an aircraft fuselage and wing, or a robotic sensor that can identify a human body in invisible situations. As one of the most promising radar algorithms, the range points migration (RPM) was proposed. This achieves fast and accurate surface extraction, even for complex-shaped objects, by eliminating the difficulty of connecting range points. However, in the case of a more complex shape whose variation scale is less than a pulsewidth, it still suffers from image distortion caused by multiple interference Signals with different waveforms. As a substantial solution, this paper proposes a novel range extraction algorithm by extending the Capon method, known as frequency domain interferometry (FDI). This algorithm combines Reference Signal optimization with the original Capon method to enhance the accuracy and resolution for an observed range into which a deformed waveform model is introduced. The results obtained from numerical simulations and an experiment with bi-static extension of the RPM prove that super-resolution UWB radar imaging is accomplished by the combination between the RPM and the extended Capon methods, even for an extremely complex-surface target including edges.
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super resolution uwb radar imaging algorithm based on extended capon with Reference Signal optimization
European Conference on Antennas and Propagation, 2010Co-Authors: Shouhei Kidera, Takuya Sakamoto, Toru SatoAbstract:Near field radar employing UWB (Ultra Wideband) Signals with its high range resolution provides various sensing applications. It enables a robotic or security sensor that can identify a human body even in invisible situations. As one of the most efficient radar algorithms, the RPM (Range Points Migration) is proposed. This achieves fast and accurate estimating shapes of surfaces, even for complex-shaped targets by eliminating the difficulty of connecting range points. However, in the case of a complicated target surface whose variation scale is less than wavelength, it still suffers from image distortion caused by multiple interference Signals mixed together by different waveforms. As a substantial solution, this paper proposes a novel range extraction algorithm by extending the Capon, known as FDI (Frequency Domain Interferometry). This algorithm combines Reference Signal optimization with the original Capon method to enhance the accuracy and resolution for an observed range into which a deformed waveform model is introduced. The result obtained from numerical simulation proves that superresolution UWB radar imaging is accomplished by the proposed method, even for an extremely complex-shaped targets including edges.
Shouhei Kidera - One of the best experts on this subject based on the ideXlab platform.
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super resolution uwb radar imaging algorithm based on extended capon with Reference Signal optimization
IEEE Transactions on Antennas and Propagation, 2011Co-Authors: Shouhei Kidera, Takuya Sakamoto, Toru SatoAbstract:Near field radar employing ultrawideband (UWB) Signals with its high range resolution has great promise for various sensing applications. It enables non-contact measurement of precision devices with specular surfaces like an aircraft fuselage and wing, or a robotic sensor that can identify a human body in invisible situations. As one of the most promising radar algorithms, the range points migration (RPM) was proposed. This achieves fast and accurate surface extraction, even for complex-shaped objects, by eliminating the difficulty of connecting range points. However, in the case of a more complex shape whose variation scale is less than a pulsewidth, it still suffers from image distortion caused by multiple interference Signals with different waveforms. As a substantial solution, this paper proposes a novel range extraction algorithm by extending the Capon method, known as frequency domain interferometry (FDI). This algorithm combines Reference Signal optimization with the original Capon method to enhance the accuracy and resolution for an observed range into which a deformed waveform model is introduced. The results obtained from numerical simulations and an experiment with bi-static extension of the RPM prove that super-resolution UWB radar imaging is accomplished by the combination between the RPM and the extended Capon methods, even for an extremely complex-surface target including edges.
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super resolution uwb radar imaging algorithm based on extended capon with Reference Signal optimization
European Conference on Antennas and Propagation, 2010Co-Authors: Shouhei Kidera, Takuya Sakamoto, Toru SatoAbstract:Near field radar employing UWB (Ultra Wideband) Signals with its high range resolution provides various sensing applications. It enables a robotic or security sensor that can identify a human body even in invisible situations. As one of the most efficient radar algorithms, the RPM (Range Points Migration) is proposed. This achieves fast and accurate estimating shapes of surfaces, even for complex-shaped targets by eliminating the difficulty of connecting range points. However, in the case of a complicated target surface whose variation scale is less than wavelength, it still suffers from image distortion caused by multiple interference Signals mixed together by different waveforms. As a substantial solution, this paper proposes a novel range extraction algorithm by extending the Capon, known as FDI (Frequency Domain Interferometry). This algorithm combines Reference Signal optimization with the original Capon method to enhance the accuracy and resolution for an observed range into which a deformed waveform model is introduced. The result obtained from numerical simulation proves that superresolution UWB radar imaging is accomplished by the proposed method, even for an extremely complex-shaped targets including edges.
Raj Rao Nadakuditi - One of the best experts on this subject based on the ideXlab platform.
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passive radar detection with noisy Reference Signal using measured data
IEEE Radar Conference, 2017Co-Authors: Sandeep Gogineni, Pawan Setlur, Muralidhar Rangaswamy, Raj Rao NadakuditiAbstract:Traditional passive radar systems with a noisy Reference Signal use the cross-correlation (CC) statistic for detection. However, owing to the composite nature of this hypothesis testing problem, no claims can be made about the optimality of this detector. Further, most modern day commercial digital illuminators and non-cooperative radar transmit Signals which have an inherent low-rank structure. Therefore, exploiting this low-rank structure of most passive radar illuminators, we recently proposed singular value decomposition (SVD) based detector that outperforms the CC detector while offering “near CFAR” behavior with respect to varying Signal strengths on the Reference channel. In this paper, we compare these detectors using measured data collected from experiments in a controlled laboratory setting. We demonstrate the improved performance offered by the SVD detector when compared to the traditional CC detector while transmitting LFM as well as pseudo noise waveforms.
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comparison of passive radar detectors with noisy Reference Signal
IEEE Signal Processing Workshop on Statistical Signal Processing, 2016Co-Authors: Sandeep Gogineni, Pawan Setlur, Muralidhar Rangaswamy, Raj Rao NadakuditiAbstract:Traditional passive radar systems with a noisy Reference Signal use the cross-correlation statistic for detection. However, owing to the composite nature of this hypothesis testing problem, no claims can be made about the optimality of this detector. Therefore, exploiting the low-rank structure of most passive radar illuminators, we recently proposed singular value decomposition based detectors that outperform the CC detector. In this paper, we derive the generalized likelihood ratio tests for this Signal model and compare with our proposed SVD based detectors. We demonstrate the near CFAR behavior (highly desirable) of our SVD detectors. We show that on the other hand, the GLRT detectors have a varying probability of false alarm with changing Reference channel characteristics making it impractical to use them in a passive radar system.
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random matrix theory inspired passive bistatic radar detection with noisy Reference Signal
International Conference on Acoustics Speech and Signal Processing, 2015Co-Authors: Sandeep Gogineni, Pawan Setlur, Muralidhar Rangaswamy, Raj Rao NadakuditiAbstract:Traditional passive radar systems with a noisy Reference Signal use the cross-correlation statistic for detection. However, owing to the composite nature of this hypothesis testing problem, no claims can be made about the optimality of this detector. In this paper, we consider digital illuminators such that the transmitted Signal in a processing interval is a weighted periodic summation of several identical pulses. The target reflectivity is assumed to change independently from one pulse to another within a processing interval. Inspired by random matrix theory, we propose a singular value decomposition (SVD) and Eigen detector for this model that significantly outperforms the conventional cross-correlation detector. We demonstrate this performance improvement through extensive numerical simulations across various surveillance and Reference Signal-to-noise ratio (SNR) regimes.
Takuya Sakamoto - One of the best experts on this subject based on the ideXlab platform.
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super resolution uwb radar imaging algorithm based on extended capon with Reference Signal optimization
IEEE Transactions on Antennas and Propagation, 2011Co-Authors: Shouhei Kidera, Takuya Sakamoto, Toru SatoAbstract:Near field radar employing ultrawideband (UWB) Signals with its high range resolution has great promise for various sensing applications. It enables non-contact measurement of precision devices with specular surfaces like an aircraft fuselage and wing, or a robotic sensor that can identify a human body in invisible situations. As one of the most promising radar algorithms, the range points migration (RPM) was proposed. This achieves fast and accurate surface extraction, even for complex-shaped objects, by eliminating the difficulty of connecting range points. However, in the case of a more complex shape whose variation scale is less than a pulsewidth, it still suffers from image distortion caused by multiple interference Signals with different waveforms. As a substantial solution, this paper proposes a novel range extraction algorithm by extending the Capon method, known as frequency domain interferometry (FDI). This algorithm combines Reference Signal optimization with the original Capon method to enhance the accuracy and resolution for an observed range into which a deformed waveform model is introduced. The results obtained from numerical simulations and an experiment with bi-static extension of the RPM prove that super-resolution UWB radar imaging is accomplished by the combination between the RPM and the extended Capon methods, even for an extremely complex-surface target including edges.
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super resolution uwb radar imaging algorithm based on extended capon with Reference Signal optimization
European Conference on Antennas and Propagation, 2010Co-Authors: Shouhei Kidera, Takuya Sakamoto, Toru SatoAbstract:Near field radar employing UWB (Ultra Wideband) Signals with its high range resolution provides various sensing applications. It enables a robotic or security sensor that can identify a human body even in invisible situations. As one of the most efficient radar algorithms, the RPM (Range Points Migration) is proposed. This achieves fast and accurate estimating shapes of surfaces, even for complex-shaped targets by eliminating the difficulty of connecting range points. However, in the case of a complicated target surface whose variation scale is less than wavelength, it still suffers from image distortion caused by multiple interference Signals mixed together by different waveforms. As a substantial solution, this paper proposes a novel range extraction algorithm by extending the Capon, known as FDI (Frequency Domain Interferometry). This algorithm combines Reference Signal optimization with the original Capon method to enhance the accuracy and resolution for an observed range into which a deformed waveform model is introduced. The result obtained from numerical simulation proves that superresolution UWB radar imaging is accomplished by the proposed method, even for an extremely complex-shaped targets including edges.
Joo Sun Choi - One of the best experts on this subject based on the ideXlab platform.
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a 0 13 mu m cmos 6 gb s pin memory transceiver using pseudo differential Signaling for removing common mode noise due to ssn
IEEE Journal of Solid-state Circuits, 2009Co-Authors: Kyung-soo Ha, Kwang-il Park, Joo Sun ChoiAbstract:A 6 Gb/s/pin transceiver for DRAM interfaces is implemented in a 0.13-mum CMOS process. Pseudo-differential Signaling to overcome problems of conventional single-ended Signaling is proposed. In a conventional single-ended Signaling, the Reference Signal from a transmitter is generally used to reduce the common-mode noise which is induced by simultaneous switching noise (SSN). However, as supply voltage becomes low and data rate increases, the Reference Signal reduces the voltage and timing margin of receiver inputs. The proposed transceiver uses the pseudo-differential Signaling without the Reference Signal and encoding schemes using the relation between neighboring data are proposed to remove the Reference Signal. In the receiver, transition-check circuit (TCC) is used to convert encoded data into original data before encoding. The proposed pseudo-differential Signaling increases the eye-opening of 1:2 demuxed outputs of the receiver by 65 ps. The transceiver dissipates 242.5 mW and its active area is 1.0 mm times 0.3 mm.
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a 6gb s pin pseudo differential Signaling using common mode noise rejection techniques without Reference Signal for dram interfaces
International Solid-State Circuits Conference, 2009Co-Authors: Kyung-soo Ha, Kwang-il Park, Joo Sun ChoiAbstract:Differential Signaling is effective in suppressing common-mode noise in parallel links as well as in high-speed serial links. However, differential Signaling is not cost effective for DRAM interfaces because the I/O-pin count is a significant portion of the chip cost. Since differential Signaling requires 2n pins and channels to transmit n bits of data, the data rate must be doubled compared to single-ended Signaling to accomplish the same per-pin data rate. However, ISI due to channel-bandwidth limits and technology limits degrade the performance [1]. Although single-ended Signaling achieves a higher data rate per pin, two major problems limit increases of the data rate: Reference ambiguity and power-supply fluctuation [2]. Several works are reported to solve the problems of single-ended Signaling [3–7]. However, the skew between encoder outputs in [3] and receiver outputs in [4,5] degrades the performance of transceivers and the Signaling in [6,7] keeps the Reference Signal. We describe pseudo-differential Signaling schemes for DRAM interfaces that minimize the skew between data and suppress common-mode noise. The chip is implemented in a 0.13µm process and occupies 2.7×2.3mm2 and the active area is 1.0×0.3mm2.
