2020 IEEE 11th Sensor Array and Multichannel Signal Processing Workshop (SAM)最新文献_第2页

Automotive Dual-Function Radar Communications Systems: An Overview 汽车双功能雷达通信系统:概述

2020 IEEE 11th Sensor Array and Multichannel Signal Processing Workshop (SAM) Pub Date : 2020-06-01 DOI: 10.1109/SAM48682.2020.9104258

Dingyou Ma, Nir Shlezinger, Tianyao Huang, Yimin Liu, Yonina C. Eldar

引用次数: 6

Feasible Sparse Spectrum Fitting of DOA and Range Estimation for Collocated FDA-MIMO radars 并置FDA-MIMO雷达的可行稀疏频谱拟合和距离估计

2020 IEEE 11th Sensor Array and Multichannel Signal Processing Workshop (SAM) Pub Date : 2020-06-01 DOI: 10.1109/SAM48682.2020.9104380

Jingyu Cong, Xianpeng Wang, Mengxing Huang, G. Bi

{"title":"Feasible Sparse Spectrum Fitting of DOA and Range Estimation for Collocated FDA-MIMO radars","authors":"Jingyu Cong, Xianpeng Wang, Mengxing Huang, G. Bi","doi":"10.1109/SAM48682.2020.9104380","DOIUrl":"https://doi.org/10.1109/SAM48682.2020.9104380","url":null,"abstract":"The size of an over complete dictionary seriously affects the computation speed of on-grid sparse algorithms. In the case of multi parameter estimation, the required dictionary size increases rapidly by multiplication to ensure the accuracy of the results. Therefore, it becomes infeasible to estimate all of the parameters directly by on-grid methods. In this paper, the feasible sparse spectrum fitting (SpSF) algorithm for computing both the direction of arrival (DOA) and range estimation in collocated FDA-MIMO radars is introduced. Firstly, due to fact that a receive spatial frequency only depends on the angle, a covariance fitting technique for data preprocessing is adopted to reshape the data for DOA estimation. Next, the range is calculated in the transmit-receive spatial frequency domain by the SpSF algorithm. In addition, to improve the computational efficiency for an increased number of targets, the traditional convex optimization is replaced with a one-dimensional peak search approximation. Numerical simulations are carried out to verify the effectiveness of the proposed approach.","PeriodicalId":6753,"journal":{"name":"2020 IEEE 11th Sensor Array and Multichannel Signal Processing Workshop (SAM)","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2020-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"89012270","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 2

Hybrid Interference Mitigation Using Analog Prewhitening 基于模拟预白化的混合干扰抑制

2020 IEEE 11th Sensor Array and Multichannel Signal Processing Workshop (SAM) Pub Date : 2020-06-01 DOI: 10.1109/SAM48682.2020.9104309

Wei Zhang, Yi Jiang, Bin Zhou, Die Hu

{"title":"Hybrid Interference Mitigation Using Analog Prewhitening","authors":"Wei Zhang, Yi Jiang, Bin Zhou, Die Hu","doi":"10.1109/SAM48682.2020.9104309","DOIUrl":"https://doi.org/10.1109/SAM48682.2020.9104309","url":null,"abstract":"Strong interferences occur in several wireless scenarios, such as full-duplex wireless communications and heterogenous networks in unlicensed spectrum. Because strong interferences can cause excessive quantization noise in the receiver’s analog-to-digital converters (ADC), mitigation of strong interferences needs to be conducted not only after but before the ADCs, i.e., via hybrid processing – an actively researched topic in recent years. In this paper, we propose to use an M-input M-output analog phase shifter network (PSN) between the receiving antennas and the ADCs to prewhiten spatially the interferences (plus signal and noise). This scheme, referred to as the Hybrid Interference Mitigation using Analog Prewhitening (HIMAP), requires no information about the interferences except an estimated spatial covariance matrix. Before the ADCs, the HIMAP scheme suppresses the strong interferences through optimizing the PSN; after the ADCs, the HIMAP suppresses the residual interferences through employing minimum mean squared error (MMSE) beamforming. The simulation results verify the effectiveness of the HIMAP scheme.","PeriodicalId":6753,"journal":{"name":"2020 IEEE 11th Sensor Array and Multichannel Signal Processing Workshop (SAM)","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2020-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"83775224","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Mitigating Outliers for Bayesian Mixture of Factor Analyzers 贝叶斯混合因子分析的缓和异常值

2020 IEEE 11th Sensor Array and Multichannel Signal Processing Workshop (SAM) Pub Date : 2020-06-01 DOI: 10.1109/SAM48682.2020.9104356

Zhongtao Chen, Lei Cheng

引用次数: 0

Online Robust Reduced-Rank Regression 在线鲁棒降秩回归

2020 IEEE 11th Sensor Array and Multichannel Signal Processing Workshop (SAM) Pub Date : 2020-06-01 DOI: 10.1109/SAM48682.2020.9104268

Y. Yang, Ziping Zhao

引用次数: 0

Robust Coexistence Design of MIMO Radar and MIMO Communication under Model Uncertainty 模型不确定性下MIMO雷达与MIMO通信鲁棒共存设计

2020 IEEE 11th Sensor Array and Multichannel Signal Processing Workshop (SAM) Pub Date : 2020-06-01 DOI: 10.1109/SAM48682.2020.9104369

Xin He, Lei Huang

引用次数: 0

Low-cost Beamforming-based DOA Estimation with Model Order Determination 基于模型阶数确定的低成本波束形成DOA估计

2020 IEEE 11th Sensor Array and Multichannel Signal Processing Workshop (SAM) Pub Date : 2020-06-01 DOI: 10.1109/SAM48682.2020.9104347

E. Aboutanios, A. Hassanien

{"title":"Low-cost Beamforming-based DOA Estimation with Model Order Determination","authors":"E. Aboutanios, A. Hassanien","doi":"10.1109/SAM48682.2020.9104347","DOIUrl":"https://doi.org/10.1109/SAM48682.2020.9104347","url":null,"abstract":"Direction of Arrival (DOA) estimation algorithms generally assume knowledge of the number of sources. This crucial parameter is either determined by the problem or estimated from the available observations prior to the application of the DOA estimators. Model order estimation (MOE) strategies via information theoretic criteria such as the Akaike Information Criterion (AIC), Minimum Description Length (MDL), and Hannan-Quinn Criterion (HQC), are usually implemented using the singular value decomposition (SVD) which is computationally expensive. In this work, we incorporate the information theoretic criteria directly into the recently proposed Fast Iterative Interpolation Beamformer (FIIB), thus avoiding the SVD. We derive the expressions for the likelihood function as well as the penalty parameters of the three criteria in terms of the number of sources. The resulting FIIB with MOE algorithm is then able to at once determine the number of sources and estimate their parameters. Simulation results demonstrate that the FIIB-based MOE outperforms the SVD-based MOE. Furthermore the FIIB with MDL achieves a performance that is very close to the original FIIB algorithm.","PeriodicalId":6753,"journal":{"name":"2020 IEEE 11th Sensor Array and Multichannel Signal Processing Workshop (SAM)","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2020-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"84816883","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 7

Hybrid Transceiver Design for Dual-Functional Radar-Communication System 双功能雷达通信系统的混合收发器设计

2020 IEEE 11th Sensor Array and Multichannel Signal Processing Workshop (SAM) Pub Date : 2020-06-01 DOI: 10.1109/SAM48682.2020.9104387

Ziyang Cheng, B. Liao, Zishu He

引用次数: 5

3D Parametric Channel Estimation for Multi-User Massive-MIMO OFDM Systems 多用户大规模mimo OFDM系统的三维参数信道估计

2020 IEEE 11th Sensor Array and Multichannel Signal Processing Workshop (SAM) Pub Date : 2020-06-01 DOI: 10.1109/SAM48682.2020.9104326

Junhui Liang, Jin He, Wenxian Yu

引用次数: 2

A General Framework for the Robustness of Structured Difference Coarrays to Element Failures 结构差分阵对单元失效鲁棒性的一般框架

2020 IEEE 11th Sensor Array and Multichannel Signal Processing Workshop (SAM) Pub Date : 2020-06-01 DOI: 10.1109/SAM48682.2020.9104370

Chun-Lin Liu

{"title":"A General Framework for the Robustness of Structured Difference Coarrays to Element Failures","authors":"Chun-Lin Liu","doi":"10.1109/SAM48682.2020.9104370","DOIUrl":"https://doi.org/10.1109/SAM48682.2020.9104370","url":null,"abstract":"Sparse arrays have received attention in array signal processing since they can resolve $mathcal{O}left( {{N^2}} right)$ uncorrelated sources using N physical sensors. The reason is that the difference coarray, which consists of the differences between sensor locations, has a central uniform linear array (ULA) segment of size $mathcal{O}left( {{N^2}} right)$. From the theory of the k-essentialness property and the k-fragility, the difference coarrays of some sparse arrays are not robust to sensor failures, possibly affecting the applicability of coarray-based direction-of-arrival (DOA) estimators. However, the k-essentialness property might not fully reflect the conditions under which these estimators fail. This paper proposes a framework for the robustness of array geometries based on the importance function and the generalized k-fragility. The importance function characterizes the importance of the subarrays in an array subject to some defining properties. The importance function is also compatible with the k-essentialness property and the size of the central ULA segment in the difference coarray. The latter is closely related to the performance of some coarray-based DOA estimators. Based on the importance function, the generalized k-fragility is proposed to quantify the robustness of an array. Properties of the importance function and the generalized k-fragility are also studied and demonstrated through numerical examples.","PeriodicalId":6753,"journal":{"name":"2020 IEEE 11th Sensor Array and Multichannel Signal Processing Workshop (SAM)","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2020-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"79582304","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 1