The Experts below are selected from a list of 294 Experts worldwide ranked by ideXlab platform
Hongqiang Wang - One of the best experts on this subject based on the ideXlab platform.
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Estimation of Translational Motion Parameters in Terahertz Interferometric Inverse Synthetic Aperture Radar (InISAR) Imaging Based on a Strong Scattering Centers Fusion Technique
Remote Sensing, 2019Co-Authors: Ye Zhang, Qi Yang, Bin Deng, Yuliang Qin, Hongqiang WangAbstract:Translational Motion of a target will lead to image misregistration in interferometric inverse synthetic aperture radar (InISAR) imaging. In this paper, a strong scattering centers fusion (SSCF) technique is proposed to estimate Translational Motion parameters of a maneuvering target. Compared to past InISAR image registration methods, the SSCF technique is advantageous in its high computing efficiency, excellent antinoise performance, high registration precision, and simple system structure. With a one-input three-output terahertz InISAR system, Translational Motion parameters in both the azimuth and height direction are precisely estimated. Firstly, the Motion measurement curves are extracted from the spatial spectrums of mutually independent strong scattering centers, which avoids the unfavorable influences of noise and the “angle scintillation” phenomenon. Then, the Translational Motion parameters are obtained by fitting the Motion measurement curves with phase unwrapping and intensity-weighted fusion processing. Finally, ISAR images are registered precisely by compensating the estimated Translational Motion parameters, and high-quality InISAR imaging results are achieved. Both simulation and experimental results are used to verify the validity of the proposed method.
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Adaptive Translational Motion Compensation Method for Rotational Parameter Estimation Under Low SNR Based on HRRP
IEEE Sensors Journal, 2019Co-Authors: Yu Xing, Peng You, Hongqiang Wang, Shao-wei Yong, Dong-fang GuanAbstract:Micro-range (m-R) signatures expressed by high resolution range profiles (HRRPs) are important in target classification. However, when the measured rotational target has maneuverability, the Translational Motion of that would destroy the periodicity of m-R signatures and makes a challenge for rotational parameter estimation. In this paper, we proposed a novel method to compensate the Translational Motion and estimate the rotational parameter under low SNR based on particle swarm optimization (PSO) algorithm. First, a HRRP-based method is utilized for the coarse estimation of the rotational period and Translational parameters, then compensating the HRRPs with coarse Translational Motion. Second, a two-level iterative algorithm is used to estimate precise rotational period and the parameter of residual Translational Motion. In the inner iteration, the image entropy of the inverse radon transform result of compensated HRRPs (IEIRCH) is utilized as the objective function to estimate the residual Translational parameters and accurate period, which is solved by the PSO algorithm and one-dimension search alternately. In the outer iteration, the final IEIRCH motivated by the inner iteration is regarded as a criterion to determine the polynomial order. Finally, the HRRPs compensated by estimated Translational Motion and period are used to obtain the rotational amplitude and initial phase by inverse radon transform. The effectiveness and robustness of the proposed method are verified by measured radar data.
Zijing Zhang - One of the best experts on this subject based on the ideXlab platform.
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adaptive Translational Motion compensation method for isar imaging under low snr based on particle swarm optimization
IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, 2015Co-Authors: Lei Liu, Feng Zhou, Mingliang Tao, Pange Sun, Zijing ZhangAbstract:Under low signal-to-noise ratio (SNR), the performance of conventional envelop-based range alignment methods for inverse synthetic aperture radar (ISAR) imaging degrades, resulting in the following phase adjustment or autofocus inapplicable. In this paper, a novel method for the Translational Motion compensation of ISAR imaging under low SNR is proposed. Translational Motion is first modeled as a polynomial, and image quality evaluation metric (IQEM) such as image entropy, contrast, or peak value is utilized as the objective function to estimate the polynomial coefficient vector based on the particle swarm optimization (PSO). A PSO-based iteration process is presented to determine the polynomial order adaptively. Meanwhile, the computation burden of the proposed method is analyzed. In addition, a coarse estimation method of the polynomial coefficient vector is also discussed. Extensive experimental results verify the effectiveness and robustness of the proposed method.
John H. Reif - One of the best experts on this subject based on the ideXlab platform.
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Design of an autonomous DNA nanomechanical device capable of universal computation and universal Translational Motion
Lecture Notes in Computer Science, 2005Co-Authors: Peng Yin, Andrew J. Turberfield, Sudheer Sahu, John H. ReifAbstract:Intelligent nanomechanical devices that operate in an autonomous fashion are of great theoretical and practical interest. Recent successes in building large scale DNA nano-structures, in constructing DNA mechanical devices, and in DNA computing provide a solid foundation for the next step forward: designing autonomous DNA mechanical devices capable of arbitrarily complex behavior. One prototype system towards this goal can be an autonomous DNA mechanical device capable of universal computation, by mimicking the operation of a universal Turing machine. Building on our prior theoretical design and prototype experimental construction of an autonomous unidirectional DNA walking device moving along a linear track, we present here the design of a nanomechanical DNA device that autonomously mimics the operation of a 2-state 5-color universal Turing machine. Our autonomous nanomechanical device, called an Autonomous DNA Turing Machine (ADTM), is thus capable of universal computation and hence complex Translational Motion, which we define as universal Translational Motion.
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DNA - Design of an autonomous DNA nanomechanical device capable of universal computation and universal Translational Motion
DNA Computing, 2005Co-Authors: Peng Yin, Andrew J. Turberfield, Sudheer Sahu, John H. ReifAbstract:Intelligent nanomechanical devices that operate in an autonomous fashion are of great theoretical and practical interest. Recent successes in building large scale DNA nano-structures, in constructing DNA mechanical devices, and in DNA computing provide a solid foundation for the next step forward: designing autonomous DNA mechanical devices capable of arbitrarily complex behavior. One prototype system towards this goal can be an autonomous DNA mechanical device capable of universal computation, by mimicking the operation of a universal Turing machine. Building on our prior theoretical design and prototype experimental construction of an autonomous unidirectional DNA walking device moving along a linear track, we present here the design of a nanomechanical DNA device that autonomously mimics the operation of a 2-state 5-color universal Turing machine. Our autonomous nanomechanical device, called an Autonomous DNA Turing Machine (ADTM), is thus capable of universal computation and hence complex Translational Motion, which we define as universal Translational Motion.
Vincent T. Coppola - One of the best experts on this subject based on the ideXlab platform.
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Vibration suppression of multi-modal Translational Motion using a rotational actuator
Proceedings of 1994 33rd IEEE Conference on Decision and Control, 1Co-Authors: Robert T. Bupp, Dennis S. Bernstein, Vincent T. CoppolaAbstract:In recent the work of Wan et al. it was shown that a rotational torque actuator with attached eccentric mass can be used to globally stabilize a one-mode Translational oscillator. A family of globally stabilizing nonlinear feedback control laws was derived by using partial feedback linearization and integrator backstepping. These control laws accounted for the strongly nonlinear coupling between the rotational Motion of the eccentric mass and the Translational Motion of the oscillator. In the present paper, we extend these results to address the problem of stabilizing the Translational Motion of multi-mode systems with a rotational actuator. The controller synthesis methodology extends the previous work to address a system involving six state variables. Detailed numerical simulation of the closed-loop system illustrates the angular position of the eccentric mass and the harmonic content of its Motion in suppressing both modal frequencies. >
Gwo-long Lin - One of the best experts on this subject based on the ideXlab platform.
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Acquisition of Translational Motion by the parallel trinocular
Information Sciences, 2008Co-Authors: Chi-cheng Cheng, Gwo-long LinAbstract:This study presents a technique for recovering Translational Motion parameters using a parallel trinocular system and a least squares estimation scheme. The proposed approach overcomes the matrix singularity problem encountered when attempting to recover the Motion parameters using a binocular scheme. To further reduce the computational complexity of the Motion estimation process, the study also presents a compact closed-form scheme for estimating the Translational Motion parameters. The closed-form algorithm not only resolves the matrix singularity problem, but also avoids the requirement for matrix manipulation. As a result, it has a low computational complexity and is therefore an ideal solution for performing Motion estimation in complex, real-world visual imaging applications. The performance of the closed-form algorithm is evaluated by performing a series of numerical simulations in which Translational Motions of various magnitudes and in various directions are recovered in both noise-free and perturbed environments. In general, the results demonstrate that the Translational Motion parameters can be accurately reconstructed provided that the Motion in the depth direction is limited to small displacements only. Overall, the simulation results suggest that the parallel trinocular system and the Motion parameter estimation scheme presented in this study represent a suitable basis for the development of artificial planar-array compound-like eyes for enhanced performance tracking and imaging applications.
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ROBIO - Determining 3-D Translational Motion by the Parallel Trinocular
2006 IEEE International Conference on Robotics and Biomimetics, 2006Co-Authors: Gwo-long Lin, Chi-cheng ChengAbstract:Incorporating a third CCD camera into a conventional binocular is verified to be very helpful to solve Translational Motion. The extra device not only provides more image information, but also plays a significant role regarding the solution issue. In this paper, a novel algorithm to recover parameters for Translational Motion using such a parallel trinocular system is presented. This approach overcomes the difficulty of matrix singularity happened in binocular. In order to fit into application requirements, a compact close form solution is also derived. This solution owns some important features, such as no matrix manipulation, no danger of matrix singularity, and easy to apply. To validate this close form solution, extensive experiments were conducted It is concluded that the movement magnitude in the depth direction has great influence on the estimation performance of the Translational Motion. Simulations in a perturbed environment are also performed to study the effect of possible image uncertainty. Compared with a conventional binocular, the presented parallel trinocular system demonstrates excellent performance on recovering parameters of Translational Motion under the circumstance of limited Motion along the depth direction.
