scholarly journals The New Mathematical Model of Motion Compensation for Stepped-Frequency Radar Signal

2014 ◽  
Vol 2014 ◽  
pp. 1-9 ◽  
Author(s):  
Yun Lin ◽  
Xiaochun Xu ◽  
Jinfeng Pang ◽  
Bin Li ◽  
Ruolin Zhou
Keyword(s):  
Motion Compensation ◽  
High Speed ◽  
Entropy Method ◽  
Estimation Accuracy ◽  
Radar Signal ◽  
Accurate Estimation ◽  
Minimum Entropy ◽  
Target Speed ◽  
Low Snr ◽  
Stepped Frequency

When a stepped-frequency radar is used to obtain the high-resolution range profile (HRRP) of high-speed target, accurate speed estimation and motion compensation must be considered. Therefore, in this paper, a novel mathematical method is presented for estimating the target speed. Firstly, the pulse Doppler method is used to calculate the initial estimation value. Secondly, based on the initial estimation value, the minimum entropy method is used to calculate the coarse estimation value. Finally, based on the coarse estimation value, the minimuml1-Norms method is used to calculate the accurate estimation value. The numeric simulation results confirm that this new method is effective and predominant, which has a much higher estimation accuracy in a low SNR and a much larger estimation range of target speed. The final estimation value can be used to well compensate for the influence of target speed on HRRP.

scholarly journals Translational motion compensation for ISAR imaging under low SNR by minimum entropy

2013 ◽  
Vol 2013 (1) ◽  
Author(s):  
Lei Zhang ◽  
Jia-lian Sheng ◽  
Jia Duan ◽  
Meng-dao Xing ◽  
Zhi-jun Qiao ◽  
...  
Keyword(s):  
Motion Compensation ◽  
Translational Motion ◽  
Minimum Entropy ◽  
Low Snr ◽  
Isar Imaging

A New OFDM Phase-coded Stepped-frequency Radar Signal and Its Characteristic

2011 ◽  
Vol 33 (3) ◽  
pp. 677-683 ◽  
Author(s):  
Kai Huo ◽  
Wei-dong Jiang ◽  
Xiang Li ◽  
Jun-jie Mao
Keyword(s):  
Radar Signal ◽  
Stepped Frequency

scholarly journals Online State-of-Charge Estimation Based on the Gas–Liquid Dynamics Model for Li(NiMnCo)O2 Battery

Energies ◽  
2021 ◽  
Vol 14 (2) ◽  
pp. 324
Author(s):  
Haobin Jiang ◽  
Xijia Chen ◽  
Yifu Liu ◽  
Qian Zhao ◽  
Huanhuan Li ◽  
...  
Keyword(s):  
Stress Test ◽  
Robustness Analysis ◽  
Open Circuit ◽  
Combined Cycle ◽  
State Of Charge ◽  
Constant Current ◽  
Estimation Accuracy ◽  
Accurate Estimation ◽  
Battery Management System ◽  
Liquid Dynamics

Accurately estimating the online state-of-charge (SOC) of the battery is one of the crucial issues of the battery management system. In this paper, the gas–liquid dynamics (GLD) battery model with direct temperature input is selected to model Li(NiMnCo)O2 battery. The extended Kalman Filter (EKF) algorithm is elaborated to couple the offline model and online model to achieve the goal of quickly eliminating initial errors in the online SOC estimation. An implementation of the hybrid pulse power characterization test is performed to identify the offline parameters and determine the open-circuit voltage vs. SOC curve. Apart from the standard cycles including Constant Current cycle, Federal Urban Driving Schedule cycle, Urban Dynamometer Driving Schedule cycle and Dynamic Stress Test cycle, a combined cycle is constructed for experimental validation. Furthermore, the study of the effect of sampling time on estimation accuracy and the robustness analysis of the initial value are carried out. The results demonstrate that the proposed method realizes the accurate estimation of SOC with a maximum mean absolute error at 0.50% in five working conditions and shows strong robustness against the sparse sampling and input error.

Fast and Accurate Estimation of Statistical Eye Diagram for Nonlinear High-Speed Links

2021 ◽  
pp. 1-9
Author(s):  
Xiuqin Chu ◽  
Wenting Guo ◽  
Jun Wang ◽  
Feng Wu ◽  
Yuhuan Luo ◽  
...  
Keyword(s):  
High Speed ◽  
Accurate Estimation ◽  
Eye Diagram

scholarly journals Development of a Deep Neural Network Model for Estimating Joint Location of Occupant Indoor Activities for Providing Thermal Comfort

Energies ◽  
2021 ◽  
Vol 14 (3) ◽  
pp. 696
Author(s):  
Eun Ji Choi ◽  
Jin Woo Moon ◽  
Ji-hoon Han ◽  
Yongseok Yoo
Keyword(s):  
Neural Network ◽  
Thermal Comfort ◽  
Deep Neural Network ◽  
Mean Squared Error ◽  
Thermal Environment ◽  
The Body ◽  
Estimation Accuracy ◽  
Accurate Estimation ◽  
Body Parts ◽  
Joint Location

The type of occupant activities is a significantly important factor to determine indoor thermal comfort; thus, an accurate method to estimate occupant activity needs to be developed. The purpose of this study was to develop a deep neural network (DNN) model for estimating the joint location of diverse human activities, which will be used to provide a comfortable thermal environment. The DNN model was trained with images to estimate 14 joints of a person performing 10 common indoor activities. The DNN contained numerous shortcut connections for efficient training and had two stages of sequential and parallel layers for accurate joint localization. Estimation accuracy was quantified using the mean squared error (MSE) for the estimated joints and the percentage of correct parts (PCP) for the body parts. The results show that the joint MSEs for the head and neck were lowest, and the PCP was highest for the torso. The PCP for individual activities ranged from 0.71 to 0.92, while typing and standing in a relaxed manner were the activities with the highest PCP. Estimation accuracy was higher for relatively still activities and lower for activities involving wide-ranging arm or leg motion. This study thus highlights the potential for the accurate estimation of occupant indoor activities by proposing a novel DNN model. This approach holds significant promise for finding the actual type of occupant activities and for use in target indoor applications related to thermal comfort in buildings.

Algorithm to process the stepped frequency radar signal for a thin road surface application

2018 ◽  
Vol 158 ◽  
pp. 1090-1098 ◽  
Author(s):  
Ari Hartikainen ◽  
Terhi Pellinen ◽  
Eeva Huuskonen-Snicker ◽  
Pekka Eskelinen
Keyword(s):  
Road Surface ◽  
Radar Signal ◽  
Surface Application ◽  
Stepped Frequency

syris: a flexible and efficient framework for X-ray imaging experiments simulation

2017 ◽  
Vol 24 (6) ◽  
pp. 1283-1295 ◽  
Author(s):  
Tomáš Faragó ◽  
Petr Mikulík ◽  
Alexey Ershov ◽  
Matthias Vogelgesang ◽  
Daniel Hänschke ◽  
...  
Keyword(s):  
Motion Estimation ◽  
Data Processing ◽  
Graphics Processing Units ◽  
High Speed ◽  
Real Data ◽  
Estimation Accuracy ◽  
Processing Parameter ◽  
X Ray ◽  
X Ray Imaging ◽  
Imaging Conditions

An open-source framework for conducting a broad range of virtual X-ray imaging experiments,syris, is presented. The simulated wavefield created by a source propagates through an arbitrary number of objects until it reaches a detector. The objects in the light path and the source are time-dependent, which enables simulations of dynamic experiments,e.g.four-dimensional time-resolved tomography and laminography. The high-level interface ofsyrisis written in Python and its modularity makes the framework very flexible. The computationally demanding parts behind this interface are implemented in OpenCL, which enables fast calculations on modern graphics processing units. The combination of flexibility and speed opens new possibilities for studying novel imaging methods and systematic search of optimal combinations of measurement conditions and data processing parameters. This can help to increase the success rates and efficiency of valuable synchrotron beam time. To demonstrate the capabilities of the framework, various experiments have been simulated and compared with real data. To show the use case of measurement and data processing parameter optimization based on simulation, a virtual counterpart of a high-speed radiography experiment was created and the simulated data were used to select a suitable motion estimation algorithm; one of its parameters was optimized in order to achieve the best motion estimation accuracy when applied on the real data.syriswas also used to simulate tomographic data sets under various imaging conditions which impact the tomographic reconstruction accuracy, and it is shown how the accuracy may guide the selection of imaging conditions for particular use cases.

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