. In this paper, a novel index modulation-based non-orthogonal multiple access (IM-NOMA) system is proposed and investigated for both perfect and imperfect channel state information (CSI) uncertainty over Nakagami-m fading channel. The proposed system has added advantages of NOMA and IM systems. NOMA supports more users by allowing all users to utilize the same resources simultaneously whereas IM boosts spectral efficiency by conveying information to the users through both constellation domain and index domain symbols. Maximum likelihood (ML) and successive interference cancellation (SIC) detectors are used at the receiver side to detect index and data symbols. The proposed system is analyzed for different values of Nakagami-m channel parameters as well as for three different CSI conditions - perfect, fixed, and MMSE-based variable CSI uncertainty. The simulation results for the bit error rate and spectral efficiency parameters show that the proposed system outperforms the existing NOMA and OMA schemes.
{"title":"Performance Analysis of Novel Index Modulation-Based Non-Orthogonal Multiple Access Systems over Nakagami-m Fading Channels with Imperfect CSI","authors":"H. Shwetha, S. Anuradha","doi":"10.13164/re.2023.0425","DOIUrl":"https://doi.org/10.13164/re.2023.0425","url":null,"abstract":". In this paper, a novel index modulation-based non-orthogonal multiple access (IM-NOMA) system is proposed and investigated for both perfect and imperfect channel state information (CSI) uncertainty over Nakagami-m fading channel. The proposed system has added advantages of NOMA and IM systems. NOMA supports more users by allowing all users to utilize the same resources simultaneously whereas IM boosts spectral efficiency by conveying information to the users through both constellation domain and index domain symbols. Maximum likelihood (ML) and successive interference cancellation (SIC) detectors are used at the receiver side to detect index and data symbols. The proposed system is analyzed for different values of Nakagami-m channel parameters as well as for three different CSI conditions - perfect, fixed, and MMSE-based variable CSI uncertainty. The simulation results for the bit error rate and spectral efficiency parameters show that the proposed system outperforms the existing NOMA and OMA schemes.","PeriodicalId":54514,"journal":{"name":"Radioengineering","volume":null,"pages":null},"PeriodicalIF":1.1,"publicationDate":"2023-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"45926039","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
. Class imbalance is a prevalent problem in many real-world applications, and imbalanced data distribution can dramatically skew the performance of classifiers. In general, the higher the imbalance ratio of a dataset, the more difficult it is to classify. However, it is found that standard classifiers can still achieve good classification results on some highly imbalanced datasets. Obviously, the class imbalance is only a superficial characteristic of the data, and the underlying structural information is often the key factor affecting the classification performance. As implicit prior knowledge, structural information has been validated to be crucial for designing a good classifier. This paper proposes a Wasserstein-based cost-sensitive support vector machine (CS-WSVM) for class imbalance learning, incorporating prior structural information and a cost-sensitive strategy. The Wasserstein distance is introduced to model the distribution of majority and minority samples to capture the structural information, which is employed to weight the majority and minority samples. Comprehensive experiments on synthetic and real-world datasets, especially on the radar emitter signal dataset, demonstrated that CS-WSVM can achieve outstanding performance in imbalanced scenarios.
{"title":"A Wasserstein Distance-Based Cost-Sensitive Framework for Imbalanced Data Classification","authors":"R. Feng, H. Ji, Z. Zhu, L. Wang","doi":"10.13164/re.2023.0451","DOIUrl":"https://doi.org/10.13164/re.2023.0451","url":null,"abstract":". Class imbalance is a prevalent problem in many real-world applications, and imbalanced data distribution can dramatically skew the performance of classifiers. In general, the higher the imbalance ratio of a dataset, the more difficult it is to classify. However, it is found that standard classifiers can still achieve good classification results on some highly imbalanced datasets. Obviously, the class imbalance is only a superficial characteristic of the data, and the underlying structural information is often the key factor affecting the classification performance. As implicit prior knowledge, structural information has been validated to be crucial for designing a good classifier. This paper proposes a Wasserstein-based cost-sensitive support vector machine (CS-WSVM) for class imbalance learning, incorporating prior structural information and a cost-sensitive strategy. The Wasserstein distance is introduced to model the distribution of majority and minority samples to capture the structural information, which is employed to weight the majority and minority samples. Comprehensive experiments on synthetic and real-world datasets, especially on the radar emitter signal dataset, demonstrated that CS-WSVM can achieve outstanding performance in imbalanced scenarios.","PeriodicalId":54514,"journal":{"name":"Radioengineering","volume":null,"pages":null},"PeriodicalIF":1.1,"publicationDate":"2023-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"42780388","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
. There are nonlinear drift memristor models uti-lizing window functions in the literature. The resistive memories can also be modeled using memristors. If the memristor’s resistance switches from its minimum value to its maximum value or from its maximum value to its minimum value, the transition phenomenon is called resistive or memristive switching. The value of the time required for this transition is especially important for resistive computer memory applications. The switching time is measured by experiments and should be calculatable from the parameters of the memristor model used. In the literature, to the best of our knowledge, the resistive switching times have not been calculated except for the HP memristor model and a piecewise linear memristor model. In this study, the memristive switching times of some of the well-known memristor models using a window function are calculated and found to be infinite. This is not feasible according to the experiments in which a finite memristive switching time is reported. Inspired by these results, a new memristor window function that results in a finite switching time is proposed. The results of this study and the criteria given here can be used to make more realistic memristor models in the future.
{"title":"A Zeno Paradox: Some Well-known Nonlinear Dopant Drift Memristor Models Have Infinite Resistive Switching Time","authors":"R. Mutlu, T. D. Kumru","doi":"10.13164/re.2023.0312","DOIUrl":"https://doi.org/10.13164/re.2023.0312","url":null,"abstract":". There are nonlinear drift memristor models uti-lizing window functions in the literature. The resistive memories can also be modeled using memristors. If the memristor’s resistance switches from its minimum value to its maximum value or from its maximum value to its minimum value, the transition phenomenon is called resistive or memristive switching. The value of the time required for this transition is especially important for resistive computer memory applications. The switching time is measured by experiments and should be calculatable from the parameters of the memristor model used. In the literature, to the best of our knowledge, the resistive switching times have not been calculated except for the HP memristor model and a piecewise linear memristor model. In this study, the memristive switching times of some of the well-known memristor models using a window function are calculated and found to be infinite. This is not feasible according to the experiments in which a finite memristive switching time is reported. Inspired by these results, a new memristor window function that results in a finite switching time is proposed. The results of this study and the criteria given here can be used to make more realistic memristor models in the future.","PeriodicalId":54514,"journal":{"name":"Radioengineering","volume":null,"pages":null},"PeriodicalIF":1.1,"publicationDate":"2023-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"42280842","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
. This paper presents a detection method of DCAM-YOLOv5 for ground penetrating radar (GPR) to address the difficulty of identifying complex and multi-type defects in tunnel linings. The diversity of tunnel-lining defects and the multiple reflections and scattering caused by water-bearing defects make GPR images quite complex. Although exist-ing methods can identify the position of underground defects from B-scans, their classification accuracy is not high. The DCAM-YOLOv5 adopts YOLOv5 as the baseline model and integrates deformable convolution and convolutional block attention module (CBAM) without adding a large number of parameters to improve the adaptive learning ability for irregular geometric shapes and boundary fuzzy defects. In this study, dielectric constant models of tunnel linings are es-tablished based on the electromagnetic simulation software (GPRMAX), including rebar and various structural defects. The simulated and field GPR B-scan images show that the DCAM-YOLOv5 method has better results for detecting dif-ferent types of defects than other methods, which validates the effectiveness of the proposed detection method.
{"title":"Research on Detection Method for Tunnel Lining Defects Based on DCAM-YOLOv5 in GPR B-Scan","authors":"D. Chen, S. Xiong, L. Guo","doi":"10.13164/re.2023.0299","DOIUrl":"https://doi.org/10.13164/re.2023.0299","url":null,"abstract":". This paper presents a detection method of DCAM-YOLOv5 for ground penetrating radar (GPR) to address the difficulty of identifying complex and multi-type defects in tunnel linings. The diversity of tunnel-lining defects and the multiple reflections and scattering caused by water-bearing defects make GPR images quite complex. Although exist-ing methods can identify the position of underground defects from B-scans, their classification accuracy is not high. The DCAM-YOLOv5 adopts YOLOv5 as the baseline model and integrates deformable convolution and convolutional block attention module (CBAM) without adding a large number of parameters to improve the adaptive learning ability for irregular geometric shapes and boundary fuzzy defects. In this study, dielectric constant models of tunnel linings are es-tablished based on the electromagnetic simulation software (GPRMAX), including rebar and various structural defects. The simulated and field GPR B-scan images show that the DCAM-YOLOv5 method has better results for detecting dif-ferent types of defects than other methods, which validates the effectiveness of the proposed detection method.","PeriodicalId":54514,"journal":{"name":"Radioengineering","volume":null,"pages":null},"PeriodicalIF":1.1,"publicationDate":"2023-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"44585914","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
. With the extreme density of devices and fast change of their directions in massive MIMO networks, a fast adaptive beamforming algorithm is required to provide high directivity and an enhanced signal-to-interference and noise ratio (SINR). Blind adaptive beamforming is suitable but less efficient, while non-blind adaptive beamforming is more efficient but requires significant training time. This study proposes a hybrid adaptive beamforming algorithm that addresses these issues. The algorithm integrates an improved direction-finding method to estimate the directions of arrival (DoAs) of incident signals at the antenna array, even in coherent signals cases, and a cascading combination of a blind and non-blind algorithms. The proposed algorithm generates an accurate main beam toward the desired direction and deep nulls in the direction of interfering signals, resulting in enhanced SINR. Compared to other algorithms, our approach achieves better performance without requiring additional antenna elements.
{"title":"A Hybrid Adaptive Beamforming Algorithm for SINR Enhancement in Massive MIMO Systems","authors":"Hosni Manai, L. B. Slama, R. Bouallègue","doi":"10.13164/re.2023.0345","DOIUrl":"https://doi.org/10.13164/re.2023.0345","url":null,"abstract":". With the extreme density of devices and fast change of their directions in massive MIMO networks, a fast adaptive beamforming algorithm is required to provide high directivity and an enhanced signal-to-interference and noise ratio (SINR). Blind adaptive beamforming is suitable but less efficient, while non-blind adaptive beamforming is more efficient but requires significant training time. This study proposes a hybrid adaptive beamforming algorithm that addresses these issues. The algorithm integrates an improved direction-finding method to estimate the directions of arrival (DoAs) of incident signals at the antenna array, even in coherent signals cases, and a cascading combination of a blind and non-blind algorithms. The proposed algorithm generates an accurate main beam toward the desired direction and deep nulls in the direction of interfering signals, resulting in enhanced SINR. Compared to other algorithms, our approach achieves better performance without requiring additional antenna elements.","PeriodicalId":54514,"journal":{"name":"Radioengineering","volume":null,"pages":null},"PeriodicalIF":1.1,"publicationDate":"2023-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"48041223","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
. In order to alleviate the adverse effects resulted from complex scenes for object tracking, such as fast movement, mottled background, interference of similar objects, and occlusion etc., an algorithm using dual-template Siamese network with attention feature fusion, named SiamDT, is proposed in this paper. The main idea include that the original ResNet-50 network is improved to extract deep semantic information and shallow spatial information, which are effectively fused using the attention mechanism to achieve accurate feature representation of objects. In addition, a template branch is added to the traditional Siamese network in which a dynamic template is generated together with the first frame image to solve the problems of template failure and model drift. Experimental results on OTB100 dataset and VOT2018 dataset show that the proposed approach obtains the excellent performance compared with the state-of-the-art tracking algorithms, which verifies the feasibility and effectiveness of the proposed approach.
{"title":"Dual-Template Siamese Network with Attention Feature Fusion for Object Tracking","authors":"Mengxing Liu, J. Shi, Y. Wang","doi":"10.13164/re.2023.0371","DOIUrl":"https://doi.org/10.13164/re.2023.0371","url":null,"abstract":". In order to alleviate the adverse effects resulted from complex scenes for object tracking, such as fast movement, mottled background, interference of similar objects, and occlusion etc., an algorithm using dual-template Siamese network with attention feature fusion, named SiamDT, is proposed in this paper. The main idea include that the original ResNet-50 network is improved to extract deep semantic information and shallow spatial information, which are effectively fused using the attention mechanism to achieve accurate feature representation of objects. In addition, a template branch is added to the traditional Siamese network in which a dynamic template is generated together with the first frame image to solve the problems of template failure and model drift. Experimental results on OTB100 dataset and VOT2018 dataset show that the proposed approach obtains the excellent performance compared with the state-of-the-art tracking algorithms, which verifies the feasibility and effectiveness of the proposed approach.","PeriodicalId":54514,"journal":{"name":"Radioengineering","volume":null,"pages":null},"PeriodicalIF":1.1,"publicationDate":"2023-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"44386990","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
. Focusing on the real-time tracking of the extended target labeled multi-Bernoulli (ET-LMB) filter, this paper proposes an extended target fast labeled multi-Bernoulli (ET-FLMB) filter based on beta gamma box particle (BGBP) and Gaussian process (GP), called ET-BGBP-GP-FLMB filter. First, a new ET-FLMB filter is derived to reduce the computational complexity of the ET-LMB filter. Then, by modeling the target state as an augmented state including detection probability, measurement rate, kinematic state and extension state, the BGBP-GP implementation of the ET-FLMB filter is presented. Compared with the traditional sequential Monte Carlo (SMC) implementation, the proposed implementation can not only greatly reduce the number of particles and the amount of computation, but also estimate the detection probabilities, measurement rates and extension states while estimating the number and kinematic states of extended targets. Finally, the simulation results show that the proposed filter can significantly reduce the computational burden and improve the real-time performance.
{"title":"Extended Target Fast Labeled Multi-Bernoulli Filter","authors":"Xuan Cheng, Ji Hongbing, Yongquan Zhang","doi":"10.13164/re.2023.0356","DOIUrl":"https://doi.org/10.13164/re.2023.0356","url":null,"abstract":". Focusing on the real-time tracking of the extended target labeled multi-Bernoulli (ET-LMB) filter, this paper proposes an extended target fast labeled multi-Bernoulli (ET-FLMB) filter based on beta gamma box particle (BGBP) and Gaussian process (GP), called ET-BGBP-GP-FLMB filter. First, a new ET-FLMB filter is derived to reduce the computational complexity of the ET-LMB filter. Then, by modeling the target state as an augmented state including detection probability, measurement rate, kinematic state and extension state, the BGBP-GP implementation of the ET-FLMB filter is presented. Compared with the traditional sequential Monte Carlo (SMC) implementation, the proposed implementation can not only greatly reduce the number of particles and the amount of computation, but also estimate the detection probabilities, measurement rates and extension states while estimating the number and kinematic states of extended targets. Finally, the simulation results show that the proposed filter can significantly reduce the computational burden and improve the real-time performance.","PeriodicalId":54514,"journal":{"name":"Radioengineering","volume":null,"pages":null},"PeriodicalIF":1.1,"publicationDate":"2023-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"43215138","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"Study on the Generation of Vortex Waves Based on Coding Metasurfaces and Genetic Algorithms","authors":"S. Lv, X. Cao, J. Gao, R. Xue","doi":"10.13164/re.2023.0332","DOIUrl":"https://doi.org/10.13164/re.2023.0332","url":null,"abstract":"","PeriodicalId":54514,"journal":{"name":"Radioengineering","volume":null,"pages":null},"PeriodicalIF":1.1,"publicationDate":"2023-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"46508487","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
. In this work, an ultra-wide stopband low pass filter (LPF) with high selectivity is proposed using coupled stepped impedance resonators (SIRs), open shunt stubs and circular slots in the ground plane. The proposed LPF has been modeled using a lumped equivalent circuit which is extracted from the EM model. The design has been validated through the simulation and experimental results. The fabricated prototype has a 3-dB cutoff frequency (f c ) of 2.44 GHz and an ultra-wide stopband extended up to 20.5 GHz (8.4 f c ) with an attenuation level > 20 dB. The transition bandwidth (from 3 dB to 20 dB) is 0.09 GHz and the roll-off rate is 225 dB / GHz (reference to 30 dB). The passband insertion loss is 0.35 dB at 1.22 GHz and the normalized circuit size of the filter is 0.045.
． 在这项工作中，提出了一种具有高选择性的超宽阻带低通滤波器(LPF)，该滤波器采用耦合阶跃阻抗谐振器(SIRs)、开路分流存根和接地面的圆形槽。所提出的LPF采用从EM模型中提取的集总等效电路进行建模。通过仿真和实验结果验证了设计的正确性。制作的原型具有2.44 GHz的3db截止频率(f c)和扩展至20.5 GHz (8.4 f c)的超宽阻带，衰减水平为bbb20 dB。转换带宽(从3db到20db)为0.09 GHz，滚降速率为225 dB / GHz(参考30db)。在1.22 GHz时通带插入损耗为0.35 dB，滤波器的归一化电路尺寸为0.045。
{"title":"A Miniaturized Low Pass Filter with Extended Stopband and High Passband Selectivity","authors":"P. Singh, M. Tomar, Parihar","doi":"10.13164/re.2023.0408","DOIUrl":"https://doi.org/10.13164/re.2023.0408","url":null,"abstract":". In this work, an ultra-wide stopband low pass filter (LPF) with high selectivity is proposed using coupled stepped impedance resonators (SIRs), open shunt stubs and circular slots in the ground plane. The proposed LPF has been modeled using a lumped equivalent circuit which is extracted from the EM model. The design has been validated through the simulation and experimental results. The fabricated prototype has a 3-dB cutoff frequency (f c ) of 2.44 GHz and an ultra-wide stopband extended up to 20.5 GHz (8.4 f c ) with an attenuation level > 20 dB. The transition bandwidth (from 3 dB to 20 dB) is 0.09 GHz and the roll-off rate is 225 dB / GHz (reference to 30 dB). The passband insertion loss is 0.35 dB at 1.22 GHz and the normalized circuit size of the filter is 0.045.","PeriodicalId":54514,"journal":{"name":"Radioengineering","volume":null,"pages":null},"PeriodicalIF":1.1,"publicationDate":"2023-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"44384844","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Jing Yang, Chengcheng Liu, Jie Huang, HU Dexiu, Chuang Zhao
. This paper investigates the issue of multistatic target localization using measurements including angle of arrival (AOA), time delay (TD), and Doppler shift (DS). We delve into a practically driven nonideal localization scenario where the measurement noise powers remain unknown. An algorithm that jointly estimates target posi-tion-velocity and measurement noise powers is proposed. Initially, an optimization model for the joint estimation is developed following the maximum likelihood estimation criterion. Subsequently, we cyclically minimize the optimization model to yield estimates for target position-velocity and measurement noise powers. The Cramér-Rao lower bound (CRLB) for this joint estimation is also derived. Contrary to existing algorithms, our proposed method eliminates the need for prior knowledge of measurement noise powers, simultaneously estimating the target posi-tion-velocity and measurement noise powers. Simulation results indicate superior localization accuracy with our algorithm, particularly in scenarios with unknown measurement noise powers. Furthermore, at moderate noise levels, the algorithm's estimation accuracy for target posi-tion-velocity and measurement noise powers meets the CRLB.
{"title":"Overcoming Unknown Measurement Noise Powers in Multistatic Target Localization: A Cyclic Minimization and Joint Estimation Algorithm","authors":"Jing Yang, Chengcheng Liu, Jie Huang, HU Dexiu, Chuang Zhao","doi":"10.13164/re.2023.0415","DOIUrl":"https://doi.org/10.13164/re.2023.0415","url":null,"abstract":". This paper investigates the issue of multistatic target localization using measurements including angle of arrival (AOA), time delay (TD), and Doppler shift (DS). We delve into a practically driven nonideal localization scenario where the measurement noise powers remain unknown. An algorithm that jointly estimates target posi-tion-velocity and measurement noise powers is proposed. Initially, an optimization model for the joint estimation is developed following the maximum likelihood estimation criterion. Subsequently, we cyclically minimize the optimization model to yield estimates for target position-velocity and measurement noise powers. The Cramér-Rao lower bound (CRLB) for this joint estimation is also derived. Contrary to existing algorithms, our proposed method eliminates the need for prior knowledge of measurement noise powers, simultaneously estimating the target posi-tion-velocity and measurement noise powers. Simulation results indicate superior localization accuracy with our algorithm, particularly in scenarios with unknown measurement noise powers. Furthermore, at moderate noise levels, the algorithm's estimation accuracy for target posi-tion-velocity and measurement noise powers meets the CRLB.","PeriodicalId":54514,"journal":{"name":"Radioengineering","volume":null,"pages":null},"PeriodicalIF":1.1,"publicationDate":"2023-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"44498291","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
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