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joint estimation algorithm for multi-targets' motion parameters

IET RADAR SONAR AND NAVIGATION 2014年第8期8卷 939-945页

作者： Tian, Jing Cui, Wei Lv, Xiao-Lei Wu, Shuang Hou, Jian-Gang Wu, Si-Liang Beijing Inst Technol Radar Res Lab Beijing 100081 Peoples R China Chinese Acad Sci Inst Elect Sci & Technol Microwave Imaging Lab Beijing 100081 Peoples R China

When multiple targets are within the same radar antenna beam and cannot be separated in the range dimension, the conventional imaging methods cannot be directly used to obtain a focused radar image. In this study, a new joint estimation algorithm for multi-targets' motion parameters is proposed. In this method, the first-order Keystone transform is first applied to correct the range walk of multiple targets simultaneously, and then the Lv's transform is used to estimate the motion parameters of targets including velocity and acceleration. The signal-to-noise ratio threshold for the proposed method is also given. The proposed method is fast and can obtain the accurate parameter estimation without knowing the number of targets and their motion information. Experimental results demonstrate the performance of the proposed algorithm. Comparisons between the proposed method and other methods, the maximum-likelihood method, fractional Fourier transform and discrete polynomial transform, are performed, which show that the proposed method can efficiently obtain the accurate parameter estimation with low computational burden.

关键词： motion estimation radar imaging maximum likelihood estimation Fourier transforms joint estimation algorithm multitarget motion parameter estimation radar antenna beam focused radar image method first-order Keystone transform range walk correction Lv transform signal-to-noise ratio threshold maximum-likelihood method fractional Fourier transform discrete polynomial transform

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Improved multi-scale cosine control whale optimization-error feedforward double Kalman filtering for the online state of charge and state of health co-estimation of lithium-ion batteries

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IONICS 2024年第4期30卷 2039-2053页

作者： Tao, Junjie Wang, Shunli Cao, Wen Zhang, Mengyun Wang, Chao Southwest Univ Sci & Technol Sch Informat Engn Mianyang 621010 Sichuan Peoples R China

Lithium-ion batteries play a pivotal role in diverse applications, necessitating the precise estimation of their parameters for safe and efficient energy utilization. In the context of ternary lithium-ion battery research, this study introduces the cosine control whale optimization (CCWO) method to real-time optimization of the forgetting factor. Concurrently, an innovative multi-scale error feedforward extended double Kalman filter (EFDKF) algorithm, featuring model error feedforward, is presented for dynamic optimization of the state noise covariance matrix. This approach diminishes reliance on the model while jointly estimating the state of charge (SOC) and state of health (SOH). The algorithm's feasibility is validated under varied operational conditions, encompassing both normal and low temperatures. The maximum absolute errors of SOC and SOH estimation are 1.09% and 3.16% at normal temperature, and 3.46% and 4.96% at low temperature, respectively. The results affirm the algorithm's enhanced precision in joint SOC and SOH estimation, heightened robustness, and superior convergence. This contribution introduces a novel methodology for lithium-ion battery state estimation.

关键词： Lithium-ion battery state estimation CCWO algorithm Model error feedforward algorithm EFDKF algorithm joint estimation algorithm Broad temperature adaptability

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UKF-based soft sensor design for joint estimation of chemical processes with multi-sensor information fusion and infrequent measurements

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IET SCIENCE MEASUREMENT & TECHNOLOGY 2018年第6期12卷 755-763页

作者： Mosalanejad, Mohammad Arefi, Mohammad Mehdi Shiraz Univ Sch Elect & Comp Engn Dept Power & Control Engn Shiraz Iran

Having a proper and real-time process monitoring and control requires accurate and frequent measurement of process variables. However, using a particular sensor for an important variable has high cost and low precision limitations. In such cases, laboratory analyses are an excellent choice for their high precision, but as their measurements are obtained manually and infrequently, they are not practical for every application in industries. This study presents an advanced soft sensor for a highly non-linear continuous stirred-tank reactor (CSTR) system which is observed with multiple sensors with different sampling rates under the assumption that there are different kinds of non-idealities in data acquisition for sensors. Some rules are assigned in order to vanquish these non-idealities in joint estimation algorithm. Therefore, the problem of simultaneous state and parameter estimation based on data fusion technique and unscented Kalman filter (UKF) is presented, and the effectiveness of the proposed method is investigated. Moreover, the proposed method is such that the effects of the inaccurate sensor on the parameter estimation are reduced. Simulation results on the estimation of four states and two parameters in a typical CSTR process show the proficiency of the proposed approach.

关键词： chemical sensors chemical variables measurement sensor fusion chemical reactors estimation theory parameter estimation state estimation nonlinear filters Kalman filters UKF-based soft sensor design chemical processing multisensor information fusion nonlinear continuous stirred-tank reactor system CSTR system data acquisition joint estimation algorithm parameter estimation state estimation data fusion technique unscented Kalman filter

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joint estimation of DOA and polarisation for radar signals based on dual-polarised antenna array

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IET MICROWAVES ANTENNAS & PROPAGATION 2020年第10期14卷 989-998页

作者： Wu, Jian Zhu, Xiaojin He, Xiaoming Gao, Zhiyuan Fang, Yubin Shanghai Univ Sch Mechatron Engn & Automat Shanghai 200072 Peoples R China Shanghai Microwave Equipment Res Inst Shanghai 201802 Peoples R China

To apply polarisation information of radar signal in radar reconnaissance equipment, a joint estimation algorithm of the radar signal direction of arrival (DOA) and polarisation parameters based on dual-polarisation antenna array has been researched in this study. The mathematical model of dual-polarised circular array has been given, and the joint estimation method of DOA and polarisation parameters for radar signal based on multiple signal classification (MUSIC) algorithm has been analysed. To overcome the shortcomings such as high calculation cost for the MUSIC algorithm, the DOA-matrix algorithm has been presented. DOA-matrix algorithm can effectively distinguish the radar signals with different polarisation states in the same direction by use of eigen-decomposition of the DOA-matrix. Through matrix correlation calculation, spectral peak search has been avoided, and the computational cost and algorithm complexity are greatly reduced. Finally, the feasibility of the DOA-matrix algorithm has been simulated and analysed. The simulation results show that the DOA-matrix algorithm can effectively complete the joint estimation of DOA and polarisation parameters for radar signal. The running time reaches millisecond level, which has a strong application value in engineering.

关键词： array signal processing radar signal processing matrix algebra antenna arrays direction-of-arrival estimation polarisation signal classification DOA-matrix algorithm different polarisation states computational cost algorithm complexity polarisation parameters dual-polarised antenna array polarisation information radar reconnaissance equipment joint estimation algorithm radar signal direction dual-polarisation antenna array dual-polarised circular array joint estimation method multiple signal classification algorithm MUSIC algorithm

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Time-domain and frequency-domain exponential ambiguity functions and their application in joint estimation of delay and Doppler shift

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IET RADAR SONAR AND NAVIGATION 2022年第3期16卷 437-455页

作者： Liu, Lubo Ji, Yuandong Zhang, Lu Southwest Inst Elect Technol China Chengdu Peoples R China Sichuan Univ Sch Aeronaut & Astronaut Chengdu Peoples R China Sichuan Univ Coll Math Chengdu 610065 Peoples R China

The classical ambiguity function (AF) in radar signal processing often has a low and fixed resolution in the presence of adjacent multi-targets. The frequency-domain exponential ambiguity function (FEAF) was previously presented with a variable exponent p introduced in the frequency-domain expression of the AF whose range resolution and output signal-to-noise ratio can be mutually replaced by controlling the exponent p. However, the FEAF mainly improves the range resolution of reference signals, but it cannot improve its velocity resolution. In this study, on the basis of symmetry theory in the time and frequency domains, a time-domain exponential ambiguity function (TEAF) was defined by indexing the time-domain expression of AF. The time-frequency properties of the defined TEAF are similar and symmetric to those of the FEAF. On the basis of the combination of the FEAF and TEAF with multi-exponents and a modified CLEAN algorithm for stepwise elimination and estimation of targets, the authors proposed a new joint estimation algorithm for delays and Doppler shifts of multi-targets. Simulation experiments indicated that the proposed estimation algorithm achieves higher accuracies in delay and Doppler shift estimation in comparison with the traditional AF-based estimation algorithm and the FEAF-based estimation algorithm.

关键词： target estimation adjacent multitargets frequency-domain analysis frequency-domain expression Doppler shift time-domain exponential ambiguity function Doppler shift estimation defined TEAF range resolution improvement radar signal processing output signal-to-noise ratio velocity resolution improvement FEAF-based estimation algorithm reference signals time-domain analysis object detection fixed resolution modified CLEAN algorithm frequency-domain exponential ambiguity function time-domain expression variable exponent AF-based estimation algorithm symmetry theory joint estimation algorithm stepwise elimination delay estimation low resolution time-frequency properties

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Fast joint estimation for time delay and angle of arrival based on smooth preprocessing with orthogonal frequency division multiplexing

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IET RADAR SONAR AND NAVIGATION 2022年第11期16卷 1809-1820页

作者： Du, Jinzhi Cui, Weijia Ba, Bin Jian, Chunxiao Li, Hao Natl Digital Switching Syst Engn & Technol Res Ct Zhengzhou 450001 Henan Peoples R China

In order to solve the problems of high complexity and absence of adaptability with the joint estimation for time delay (TD) and angle of arrival (AOA) in coherent multipath environments, a fast estimation algorithm based on orthogonal frequency division multiplexing (OFDM) technique is proposed. First, we combine OFDM signal characteristics with array features to obtain extended arrays. Then, we obtain the channel frequency domain response covariance matrices for TD and AOA estimation separately by smoothing preprocessing in the spatial and frequency domains, respectively. Finally, we estimate the TD values by a one-dimensional (1-D) spectral peak search, as well as determine the closed-form solution for AOA by Unitary-ESPRIT. In comparison with previous work, the proposed algorithm not only improves the adaptability in correlated or mixed multipath environments but also significantly reduces the complexity. The simulation results show the effectiveness and robustness of the proposed joint estimation algorithm.

关键词： channel frequency domain response covariance matrices OFDM signal characteristics AOA smooth preprocessing orthogonal frequency division multiplexing time delay spatial frequency domains extended arrays fast joint estimation coherent multipath environments joint estimation algorithm multipath channels correlated environments mixed multipath environments fast estimation algorithm OFDM modulation array features direction-of-arrival estimation covariance matrices

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A hybrid multilayerperceptron-extremegradientboost approach for precise state of charge and state of health assessment

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e-Prime - Advances in Electrical Engineering, Electronics and Energy 2024年 8卷

作者： Divya, R. Karunanithi, K. Ramesh, S. Raja, S.P. Vel Tech Rangarajan Dr. Sagunthala R&D Institute of Science and Technology Chennai India School of Computer Science and Engineering Vellore Institute of Technology Vellore India

Lithium ion batteries are popularly used in various energy storage systems. Accurate battery's State of Charge (SoC) and State of Health (SoH) estimate is essential for energy storage system's safety. This manuscript proposes a hybrid approach for estimating SoC and SoH of lithium ion battery. The proposed hybrid technique is the joint execution of both the Multi-Layer Perceptron (MLP) with Extreme Gradient boosting (XGBoost) algorithm. Hence, it is named as MLP-XG Boost algorithm. The major objective of the proposed system is to improve the safety of energy storage systems and to achieve the highly accurate SoH. The MLP algorithm is utilized to analyze and trained the battery data. The XG Boosting algorithm is utilized to preprocessed and estimate the SoC and SoH of a lithium-ion battery. The proposed method's effectiveness is assessed using the MATLAB platform and contrasted with other methods that are currently in use. In every system now in use, including Long Short-Term Memory (LSTM), Convolutional Neural Networks (CNN), and Recurrent Neural Networks (RNN), the proposed approach produces better results. From the result it is concluded that the proposed method based Mean Square Error and Mean Absolute Error Root is less than 1 at various temperatures such as 0^∘C, 25^∘Cand 45^∘C and it is better and efficient. © 2024 The Author(s)

关键词： CNN joint estimation algorithm Lithium-ion battery LSTM MLP-XGboost algorithm RNN State of charge (SoC) State of health (SoH)

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