This paper proposes a novel swarm-based metaheuristics algorithm, the Egyptian mosquito optimization algorithm (EMOA), designed to solve global optimization problems. The EMOA is inspired by the natural behavior of Egyptian mosquitoes and achieves a balance between exploitation and exploration in the solution search space, thereby effectively tackling optimization challenges. The effectiveness of the EMOA is evaluated using 23 classical benchmark functions and the CEC 2017 test suite. According to the analysis of the root mean square error (RMSE) values, the RMSE values of the EMOA are 8.5424 and 32.3887, respectively. Finally, the analysis of the exploration and utilization of EMOA in high-dimensional spaces proves that the algorithm has the potential to be a tool for solving high-dimensional optimization problems.
{"title":"Egyptian Mosquito Optimization Algorithm: A Novel Swarm-Based Metaheuristic Algorithm to Solve Electronic and Industrial Problems","authors":"Ruiyang Sun;Wenjuan Cheng;Xiao Liang;Hao Tang;Yan Xiong","doi":"10.23919/cje.2024.00.223","DOIUrl":"https://doi.org/10.23919/cje.2024.00.223","url":null,"abstract":"This paper proposes a novel swarm-based metaheuristics algorithm, the Egyptian mosquito optimization algorithm (EMOA), designed to solve global optimization problems. The EMOA is inspired by the natural behavior of Egyptian mosquitoes and achieves a balance between exploitation and exploration in the solution search space, thereby effectively tackling optimization challenges. The effectiveness of the EMOA is evaluated using 23 classical benchmark functions and the CEC 2017 test suite. According to the analysis of the root mean square error (RMSE) values, the RMSE values of the EMOA are 8.5424 and 32.3887, respectively. Finally, the analysis of the exploration and utilization of EMOA in high-dimensional spaces proves that the algorithm has the potential to be a tool for solving high-dimensional optimization problems.","PeriodicalId":50701,"journal":{"name":"Chinese Journal of Electronics","volume":"34 6","pages":"1903-1910"},"PeriodicalIF":3.0,"publicationDate":"2025-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=11322827","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145886550","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2025-11-01DOI: 10.23919/cje.2024.00.212
Rongheng Lin;Shuo Chen;Budan Wu;Xin Zhao;Qiushuang Li
Short-term load forecasting (STLF) is an essential component of smart grids, enabling power departments to anticipate grid operations in advance, thereby controlling electricity usage in a timely manner, allocating power resources reasonably, and ensuring the quality and reliability of grid services. In the field of electric load forecasting, existing prediction models perform poorly on load data with frequent fluctuations and have issues with prediction lag. To address these issues, this paper proposes an improved TimesNet model based on wavelet decomposition, called WaveTimes. Firstly, the model uses wavelet decomposition to decompose load data, obtaining sequences with smaller mutation amplitudes and weaker autocorrelation. Secondly, a feature extraction module is introduced, which uses Fourier transformation and computer vision models for periodic analysis, effectively capturing periodic changes in load data across different frequency domains. Finally, a residual connection and prediction module are used to complete the forecasting task. This paper evaluates the proposed method on public datasets and load data from a certain province in China, showing significant improvements compared to the baseline. The model can more effectively support relevant departments in load control and demand response, contributing to the construction of smart grids.
{"title":"WaveTimes: Short-Term Load Forecast Based on Wavelet Decomposition and Improved TimesNet","authors":"Rongheng Lin;Shuo Chen;Budan Wu;Xin Zhao;Qiushuang Li","doi":"10.23919/cje.2024.00.212","DOIUrl":"https://doi.org/10.23919/cje.2024.00.212","url":null,"abstract":"Short-term load forecasting (STLF) is an essential component of smart grids, enabling power departments to anticipate grid operations in advance, thereby controlling electricity usage in a timely manner, allocating power resources reasonably, and ensuring the quality and reliability of grid services. In the field of electric load forecasting, existing prediction models perform poorly on load data with frequent fluctuations and have issues with prediction lag. To address these issues, this paper proposes an improved TimesNet model based on wavelet decomposition, called WaveTimes. Firstly, the model uses wavelet decomposition to decompose load data, obtaining sequences with smaller mutation amplitudes and weaker autocorrelation. Secondly, a feature extraction module is introduced, which uses Fourier transformation and computer vision models for periodic analysis, effectively capturing periodic changes in load data across different frequency domains. Finally, a residual connection and prediction module are used to complete the forecasting task. This paper evaluates the proposed method on public datasets and load data from a certain province in China, showing significant improvements compared to the baseline. The model can more effectively support relevant departments in load control and demand response, contributing to the construction of smart grids.","PeriodicalId":50701,"journal":{"name":"Chinese Journal of Electronics","volume":"34 6","pages":"1911-1923"},"PeriodicalIF":3.0,"publicationDate":"2025-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=11322771","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145886549","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2025-09-01DOI: 10.23919/cje.2024.00.250
Puchen Liu;Ming Yang;Qiankun Li
The higher-order neural network system with both leakage delays and S-type distributed transmission delays is introduced. By means of topological degree theory, properties of M-matrices and inequality tricks, the exis-tence of the equilibrium point for the system is deduced. In existing work, authors mainly employed the Lyapunov functional or multiple integral inequalities or matrix inequalities, which usually required more computations. On the other hand, in treating the infiniteness of the distributed delays, most scholars had explored the intercept method or the generalized Halanay differential inequality. Instead of constructing complicated Lyapunov functionals, the principle of reductio ad absurdum and simple algebra inequality strategy are explored to prove the global exponential stability of the system, which has largely reduced the computational complexity. Finally, two examples, their simulations and the related remark are demonstrated for illustrating the effectiveness and generality of the theoretical results. Our model is more general and the sufficient results are easily verifiable and have wider adaptiveness.
{"title":"Inequality Methods and Global Exponential Stability for Higher-Order Neural Networks with Time-Varying Leakage Delays and S-Type Distributed Delays","authors":"Puchen Liu;Ming Yang;Qiankun Li","doi":"10.23919/cje.2024.00.250","DOIUrl":"https://doi.org/10.23919/cje.2024.00.250","url":null,"abstract":"The higher-order neural network system with both leakage delays and S-type distributed transmission delays is introduced. By means of topological degree theory, properties of M-matrices and inequality tricks, the exis-tence of the equilibrium point for the system is deduced. In existing work, authors mainly employed the Lyapunov functional or multiple integral inequalities or matrix inequalities, which usually required more computations. On the other hand, in treating the infiniteness of the distributed delays, most scholars had explored the intercept method or the generalized Halanay differential inequality. Instead of constructing complicated Lyapunov functionals, the principle of reductio ad absurdum and simple algebra inequality strategy are explored to prove the global exponential stability of the system, which has largely reduced the computational complexity. Finally, two examples, their simulations and the related remark are demonstrated for illustrating the effectiveness and generality of the theoretical results. Our model is more general and the sufficient results are easily verifiable and have wider adaptiveness.","PeriodicalId":50701,"journal":{"name":"Chinese Journal of Electronics","volume":"34 5","pages":"1652-1660"},"PeriodicalIF":3.0,"publicationDate":"2025-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=11232555","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145456079","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Unmanned aerial vehicle (UAV) swarm is widely used in tasks such as post-disaster rescue and battle-field monitoring. These tasks are often executed in unknown or complex environments, necessitating the programming of safe and efficient paths for UAV swarm to ensure the completion of missions. To address the path planning problem for UAV swarm in unknown electromagnetic environment, we propose a multi-agent deep deterministic policy gradient algorithm based on environment sensing where a safe learning mechanism is designed by using control barrier function. Additionally, a weakly supervised learning-based generative adversarial network algorithm is employed to construct an electromagnetic environment sensing module. By using the algrothim we propose, UAV swarm can avoid zones with strong electromagnetic interference and guarantee inter-UAV collisions avoidance during task execution. Compared to reinforcement learning algorithm without environment sensing module and safe learning mechanism, the algorithm we propose reduces convergence time by approximately 2.5 times. Simultaneously, it prevents individual trial-and-error learning process from violating safety constraints, ensuring the safety of UAV swarm in unknown environment. Finally, we verified the effectiveness of our algorithm on the experimental platform which is constructed by using universal software radio peripherals and quadcopter UAVs.
{"title":"Path Planning for Unmanned Aerial Vehicle Swarm Based on Electromagnetic Environment Sensing","authors":"Tong Li;Zhuangzhuang Ma;Jinliang Shao;Yuan Zhao;Xilin Zhang;Yuhua Cheng","doi":"10.23919/cje.2024.00.088","DOIUrl":"https://doi.org/10.23919/cje.2024.00.088","url":null,"abstract":"Unmanned aerial vehicle (UAV) swarm is widely used in tasks such as post-disaster rescue and battle-field monitoring. These tasks are often executed in unknown or complex environments, necessitating the programming of safe and efficient paths for UAV swarm to ensure the completion of missions. To address the path planning problem for UAV swarm in unknown electromagnetic environment, we propose a multi-agent deep deterministic policy gradient algorithm based on environment sensing where a safe learning mechanism is designed by using control barrier function. Additionally, a weakly supervised learning-based generative adversarial network algorithm is employed to construct an electromagnetic environment sensing module. By using the algrothim we propose, UAV swarm can avoid zones with strong electromagnetic interference and guarantee inter-UAV collisions avoidance during task execution. Compared to reinforcement learning algorithm without environment sensing module and safe learning mechanism, the algorithm we propose reduces convergence time by approximately 2.5 times. Simultaneously, it prevents individual trial-and-error learning process from violating safety constraints, ensuring the safety of UAV swarm in unknown environment. Finally, we verified the effectiveness of our algorithm on the experimental platform which is constructed by using universal software radio peripherals and quadcopter UAVs.","PeriodicalId":50701,"journal":{"name":"Chinese Journal of Electronics","volume":"34 4","pages":"1156-1171"},"PeriodicalIF":3.0,"publicationDate":"2025-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=11151183","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144990278","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2025-07-01DOI: 10.23919/cje.2024.00.085
Yihong Su;Mingtang Li;Xianqi Lin;Yong Fan
This paper proposes a duplexing power divider (DPD) with a large frequency ratio based on the mode composite coplanar waveguide (MCCPW). The DPD is a five-port network circuit. It integrates the function of the duplexer and power divider within a compact size. The overall DPD can be regarded as a combination of two filtering power dividers and a frequency splitter. The low-band channel circuit is a filtering power divider with harmonic suppression, the bandwidth ranges from 2 GHz to 6 GHz, covering some of the typical frequencies (2.4 GHz, 3.5 GHz, and 5.8 GHz) in sub-6 GHz. The high-frequency band filtering power divider works in substrate integrated waveguide (SIW)-TE10 mode. The bandwidth ranges from 27 GHz to 29 GHz targeting 5G millimeter wave application. The two bands of the duplexer can be designed independently with very high freedom due to the mode separation used in the MCCPW. The DPD can be fabricated using a single PCB process and assembled by the fixing screws. The measured results of the DPD have good agreement with its simulation. The MCCPW-based DPD has the benefits of multi-function, large frequency ratio, high design freedom, high isolation, and high mid-band suppression at the same time with compact size. It is a promising candidate in the multiband system with large frequency ratios such as 5G.
{"title":"Mode Composite Coplanar Waveguide Duplexing Power Divider with Large Frequency Ratio for 5G Multiband System Application","authors":"Yihong Su;Mingtang Li;Xianqi Lin;Yong Fan","doi":"10.23919/cje.2024.00.085","DOIUrl":"https://doi.org/10.23919/cje.2024.00.085","url":null,"abstract":"This paper proposes a duplexing power divider (DPD) with a large frequency ratio based on the mode composite coplanar waveguide (MCCPW). The DPD is a five-port network circuit. It integrates the function of the duplexer and power divider within a compact size. The overall DPD can be regarded as a combination of two filtering power dividers and a frequency splitter. The low-band channel circuit is a filtering power divider with harmonic suppression, the bandwidth ranges from 2 GHz to 6 GHz, covering some of the typical frequencies (2.4 GHz, 3.5 GHz, and 5.8 GHz) in sub-6 GHz. The high-frequency band filtering power divider works in substrate integrated waveguide (SIW)-TE<inf>10</inf> mode. The bandwidth ranges from 27 GHz to 29 GHz targeting 5G millimeter wave application. The two bands of the duplexer can be designed independently with very high freedom due to the mode separation used in the MCCPW. The DPD can be fabricated using a single PCB process and assembled by the fixing screws. The measured results of the DPD have good agreement with its simulation. The MCCPW-based DPD has the benefits of multi-function, large frequency ratio, high design freedom, high isolation, and high mid-band suppression at the same time with compact size. It is a promising candidate in the multiband system with large frequency ratios such as 5G.","PeriodicalId":50701,"journal":{"name":"Chinese Journal of Electronics","volume":"34 4","pages":"1064-1077"},"PeriodicalIF":3.0,"publicationDate":"2025-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=11151246","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144989945","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Grant-free-based non-terrestrial networks (GF-NTN) hold immense potential for future networks due to the benefits of wider coverage and lower access latency. However, it is challenging to estimate the number of active devices and data since synchronization cannot be guaranteed in GF-NTN systems. To address this issue, a multiple-slots approximate expectation propagation (MS-AEP) detector is proposed. Concretely, we first conceive an asynchronous detection model for GF-NTN. Based on the model, we propose a symbols-based approximate expectation propagation (AEP) detector, utilizing the property of discrete constellation symbols. Then, to fully exploit the structured sparsity for performance enhancement, we extend the AEP detector to the proposed MS-AEP detector. Further-more, a power-assisted solution is developed to estimate unknown delay based on MS-AEP. Simulation results show that the proposed detector approaches the performance of Oracle least squares detector in asynchronous detection for GF-NTN scenario.
{"title":"Joint Activity and Data Detection for Asynchronous Grant-Free Access in NTN","authors":"Jiaqi Huang;Lixia Xiao;Shuo Li;Jiaxi Zhou;Tao Jiang","doi":"10.23919/cje.2024.00.317","DOIUrl":"https://doi.org/10.23919/cje.2024.00.317","url":null,"abstract":"Grant-free-based non-terrestrial networks (GF-NTN) hold immense potential for future networks due to the benefits of wider coverage and lower access latency. However, it is challenging to estimate the number of active devices and data since synchronization cannot be guaranteed in GF-NTN systems. To address this issue, a multiple-slots approximate expectation propagation (MS-AEP) detector is proposed. Concretely, we first conceive an asynchronous detection model for GF-NTN. Based on the model, we propose a symbols-based approximate expectation propagation (AEP) detector, utilizing the property of discrete constellation symbols. Then, to fully exploit the structured sparsity for performance enhancement, we extend the AEP detector to the proposed MS-AEP detector. Further-more, a power-assisted solution is developed to estimate unknown delay based on MS-AEP. Simulation results show that the proposed detector approaches the performance of Oracle least squares detector in asynchronous detection for GF-NTN scenario.","PeriodicalId":50701,"journal":{"name":"Chinese Journal of Electronics","volume":"34 4","pages":"1226-1232"},"PeriodicalIF":3.0,"publicationDate":"2025-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=11151178","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144990187","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
This paper proposes a deep learning-based time-frequency representation approach that employs the enhanced time-frequency micro-Doppler network (ETF-MDNet) model to improve the characterization of micro-Doppler features for radar targets, particularly “low, slow, and small” ones. The ETF-MDNet model consists of four key components: the micro-Doppler target signal input module, the basis function selection module, the feature aggregation module, and the energy concentration module. A notable characteristic of this method is its utilization of the inherent adaptive learning capabilities of deep learning, which are combined with an attention mechanism to enhance the aggregation of time-frequency energy. This integration optimizes the method's capacity to represent micro-motion features across both channel and spatial dimensions. Consequently, this approach effectively captures the micro-motion information of the target while suppressing extraneous noise. In comparison to traditional short time Fourier transform, generalized warblet and reassigned spectrogram analysis methods, the proposed method achieves an average enhancement of 31.5% in time-frequency energy concentration, higher time-frequency energy aggregation, and the ability to reveal micro-motion feature details not captured by traditional methods.
{"title":"A Time-Frequency Representation Method Based on ETF-MDNet for Radar Target Micro-Motion Features","authors":"Jinhao Wang;Xiaolong Chen;Jian Guan;Ningyuan Su;Wang Yuan","doi":"10.23919/cje.2024.00.233","DOIUrl":"https://doi.org/10.23919/cje.2024.00.233","url":null,"abstract":"This paper proposes a deep learning-based time-frequency representation approach that employs the enhanced time-frequency micro-Doppler network (ETF-MDNet) model to improve the characterization of micro-Doppler features for radar targets, particularly “low, slow, and small” ones. The ETF-MDNet model consists of four key components: the micro-Doppler target signal input module, the basis function selection module, the feature aggregation module, and the energy concentration module. A notable characteristic of this method is its utilization of the inherent adaptive learning capabilities of deep learning, which are combined with an attention mechanism to enhance the aggregation of time-frequency energy. This integration optimizes the method's capacity to represent micro-motion features across both channel and spatial dimensions. Consequently, this approach effectively captures the micro-motion information of the target while suppressing extraneous noise. In comparison to traditional short time Fourier transform, generalized warblet and reassigned spectrogram analysis methods, the proposed method achieves an average enhancement of 31.5% in time-frequency energy concentration, higher time-frequency energy aggregation, and the ability to reveal micro-motion feature details not captured by traditional methods.","PeriodicalId":50701,"journal":{"name":"Chinese Journal of Electronics","volume":"34 4","pages":"1199-1208"},"PeriodicalIF":3.0,"publicationDate":"2025-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=11151189","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144990276","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2025-07-01DOI: 10.23919/cje.2024.00.151
Fan Xie;Dan Zeng;Qiaomu Shen;Bo Tang
Since the release of Sora, the text-to-video (T2V) generation has brought profound changes to artificial intelligence-generated content. T2V generation aims to generate high-quality videos based on a given text description, which is challenging due to the lack of large-scale, high-quality text-video pairs for training and the complexity of modeling high-dimensional video data. Although there have been some valuable and impressive surveys on T2V generation, these surveys introduce approaches in a relatively isolated way, lack the development of evaluation metrics, and lack the latest advances in T2V generation since 2023. Due to the rapid expansion of the field of T2V generation, a comprehensive review of the relevant studies is both necessary and challenging. This survey attempts to connect and systematize existing research in a comprehensive way. Unlike previous surveys, this survey reviews nearly one hundred representative T2V generation approaches and includes the latest method published on July 2024 from the perspectives of model, data, evaluation metrics, and available open source. It may help readers better understand the current research status and ideas and have a quick start with accessible open-source models. Finally, the future challenges and method trends of T2V generation are thoroughly discussed.
{"title":"A Comprehensive Survey on Text-to-Video Generation","authors":"Fan Xie;Dan Zeng;Qiaomu Shen;Bo Tang","doi":"10.23919/cje.2024.00.151","DOIUrl":"https://doi.org/10.23919/cje.2024.00.151","url":null,"abstract":"Since the release of Sora, the text-to-video (T2V) generation has brought profound changes to artificial intelligence-generated content. T2V generation aims to generate high-quality videos based on a given text description, which is challenging due to the lack of large-scale, high-quality text-video pairs for training and the complexity of modeling high-dimensional video data. Although there have been some valuable and impressive surveys on T2V generation, these surveys introduce approaches in a relatively isolated way, lack the development of evaluation metrics, and lack the latest advances in T2V generation since 2023. Due to the rapid expansion of the field of T2V generation, a comprehensive review of the relevant studies is both necessary and challenging. This survey attempts to connect and systematize existing research in a comprehensive way. Unlike previous surveys, this survey reviews nearly one hundred representative T2V generation approaches and includes the latest method published on July 2024 from the perspectives of model, data, evaluation metrics, and available open source. It may help readers better understand the current research status and ideas and have a quick start with accessible open-source models. Finally, the future challenges and method trends of T2V generation are thoroughly discussed.","PeriodicalId":50701,"journal":{"name":"Chinese Journal of Electronics","volume":"34 4","pages":"1009-1036"},"PeriodicalIF":3.0,"publicationDate":"2025-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=11151234","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144990044","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
The BeiDou-3 satellite navigation system (BDS-3) provides all-weather, all-time, high-precision positioning, navigation, and timing services for global users. However, compared with the Asia-Pacific region, the BDS-3 suffers from a relatively small number of visible satellites at high latitudes, which makes it difficult to provide high-performance services that meet application requirements. Moreover, traditional satellite positioning algorithms, such as iterative least squares (ILS) and extended Kalman filter (EKF), yield unsatisfactory positioning results when con-fronted with nonlinear models and abnormal noise. The rapid movement of low Earth orbit (LEO) satellites can enhance geometric diversity and effectively improve the geometry of BDS-3. The adaptive iterative extended Kalman filter (AIEKF) can adaptively adjust the noise covariance matrix and iteratively optimize the filtered estimates to converge more closely towards the true values. Therefore, we leverage the Iridium NEXT constellation to enhance the performance of BDS-3, and based on this, employ the AIEKF to estimate the system state parameters. The results indicated that with the integration of the LEO constellations, the number of visible satellites of BDS-3 at high latitudes improved by about 3 satellites and the position dilution of precision decreased by about 0.1821. The positioning accuracy was improved by 54.81% and 23.30% through the proposed algorithm, when compared with the ILS and EKF respectively. The algorithm provides a reference for comprehensive assessment of hybrid constellation positioning performance.
{"title":"Low-Orbit Augmented Positioning Technology Based on Adaptive Iterative Extended Kalman Filter","authors":"Jixi Liu;Shuaiyong Zheng;Xuanwen Wang;Shuailong Chen;Heng Yang;Yuhan Zhou;Xiaoqin Jin;Ailing Zhang","doi":"10.23919/cje.2024.00.112","DOIUrl":"https://doi.org/10.23919/cje.2024.00.112","url":null,"abstract":"The BeiDou-3 satellite navigation system (BDS-3) provides all-weather, all-time, high-precision positioning, navigation, and timing services for global users. However, compared with the Asia-Pacific region, the BDS-3 suffers from a relatively small number of visible satellites at high latitudes, which makes it difficult to provide high-performance services that meet application requirements. Moreover, traditional satellite positioning algorithms, such as iterative least squares (ILS) and extended Kalman filter (EKF), yield unsatisfactory positioning results when con-fronted with nonlinear models and abnormal noise. The rapid movement of low Earth orbit (LEO) satellites can enhance geometric diversity and effectively improve the geometry of BDS-3. The adaptive iterative extended Kalman filter (AIEKF) can adaptively adjust the noise covariance matrix and iteratively optimize the filtered estimates to converge more closely towards the true values. Therefore, we leverage the Iridium NEXT constellation to enhance the performance of BDS-3, and based on this, employ the AIEKF to estimate the system state parameters. The results indicated that with the integration of the LEO constellations, the number of visible satellites of BDS-3 at high latitudes improved by about 3 satellites and the position dilution of precision decreased by about 0.1821. The positioning accuracy was improved by 54.81% and 23.30% through the proposed algorithm, when compared with the ILS and EKF respectively. The algorithm provides a reference for comprehensive assessment of hybrid constellation positioning performance.","PeriodicalId":50701,"journal":{"name":"Chinese Journal of Electronics","volume":"34 4","pages":"1136-1145"},"PeriodicalIF":3.0,"publicationDate":"2025-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=11151172","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144990058","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
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