Space-time estimation algorithms for wideband signals

2015 ◽  
Author(s):  
Laghmardi Noureddine ◽  
Ferid Harabi ◽  
Ali Gharsallah
Keyword(s):  
Time Estimation ◽  
Space Time ◽  
Estimation Algorithms ◽  
Wideband Signals

scholarly journals Finite-time estimation algorithms for LPV discrete-time systems with application to output feedback stabilization

Automatica ◽  
2021 ◽  
Vol 125 ◽  
pp. 109436
Author(s):  
Khadidja Chaib-Draa ◽  
Ali Zemouche ◽  
Fazia Bedouhene ◽  
Rajesh Rajamani ◽  
Yan Wang ◽  
...  
Keyword(s):  
Discrete Time ◽  
Output Feedback ◽  
Finite Time ◽  
Time Estimation ◽  
Feedback Stabilization ◽  
Estimation Algorithms ◽  
Output Feedback Stabilization ◽  
Discrete Time Systems ◽  
Time Systems

scholarly journals Accurate Direction-of-Arrival Estimation Method based on Space-Time Modulated Metasurface

2022 ◽  
Author(s):  
Mengmeng Li
Keyword(s):  
Plane Wave ◽  
Incident Angle ◽  
Estimation Method ◽  
Time Estimation ◽  
Direction Of Arrival ◽  
Doa Estimation ◽  
Space Time ◽  
Estimation Methods ◽  
Estimation Accuracy ◽  
Hardware Complexity

In this paper, we present a metasurface-based Direction of Arrival (DoA) estimation method that exploits the properties of space-time modulated reflecting metasurfaces to estimate in real-time the impinging angle of an illuminating monochromatic plane wave. The approach makes use of the amplitude unbalance of the received fields at broadside at the frequencies of the two first-order harmonics generated by the interaction between the incident plane wave and the modulated metasurface. Here, we first describe analytically how to generate the desired higher-order harmonics in the reflected spectrum and how to realize the breaking of the spatial symmetry of each order harmonic scattering pattern. Then, the one dimensional (1D) omnidirectional incident angle can be analytically computed using +1st and -1st order harmonics. The approach is also extended to 2D DoA estimation by using two orthogonally arranged 1D DoA modulation arrays. The accuracy of 1D DoA estimation is verified through full-wave numerical simulations. Compared to conventional DoA estimation methods, the proposed approach simplifies the computation and hardware complexity, ensuring at the same time estimation accuracy. The proposed method may have potential applications in wireless communications, target recognition, and identification.

scholarly journals Dual Nonlinear Kalman Filter-Based SoC and Remaining Capacity Estimation for an Electric Scooter Li-NMC Battery Pack

Energies ◽  
2020 ◽  
Vol 13 (3) ◽  
pp. 540 ◽  
Author(s):  
Filip Maletić ◽  
Mario Hrgetić ◽  
Joško Deur
Keyword(s):  
Kalman Filter ◽  
Time Estimation ◽  
Detection Algorithm ◽  
Open Circuit ◽  
Battery Management ◽  
Adaptation Mechanism ◽  
Sigma Point ◽  
Estimation Algorithms ◽  
Electric Scooter ◽  
Remaining Capacity

Accurate, real-time estimation of battery state-of-charge (SoC) and state-of-health represents a crucial task of modern battery management systems. Due to nonlinear and battery degradation-dependent behavior of output voltage, the design of these estimation algorithms should be based on nonlinear parameter-varying models. The paper first describes the experimental setup that consists of commercially available electric scooter equipped with telemetry measurement equipment. Next, dual extended Kalman filter-based (DEKF) estimator of battery SoC, internal resistances, and parameters of open-circuit voltage (OCV) vs. SoC characteristic is presented under the assumption of fixed polarization time constant vs. SoC characteristic. The DEKF is upgraded with an adaptation mechanism to capture the battery OCV hysteresis without explicitly modelling it. Parameterization of an explicit hysteresis model and its inclusion in the DEKF is also considered. Finally, a slow time scale, sigma-point Kalman filter-based capacity estimator is designed and inter-coupled with the DEKF. A convergence detection algorithm is proposed to ensure that the two estimators are coupled automatically only after the capacity estimate has converged. The overall estimator performance is experimentally validated for real electric scooter driving cycles.

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