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2016 IEEE Sensor Array and Multichannel Signal Processing Workshop (SAM)最新文献

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Sparse antenna array design for directional modulation 方向调制稀疏天线阵列设计
2016 IEEE Sensor Array and Multichannel Signal Processing Workshop (SAM) Pub Date : 2016-07-10 DOI: 10.1109/SAM.2016.7569671
Bo Zhang, W. Liu, Xiaoming Gou
{"title":"Sparse antenna array design for directional modulation","authors":"Bo Zhang, W. Liu, Xiaoming Gou","doi":"10.1109/SAM.2016.7569671","DOIUrl":"https://doi.org/10.1109/SAM.2016.7569671","url":null,"abstract":"Directional modulation (DM) can be achieved based on uniform linear arrays (ULAs), where the maximum half wavelength spacing is needed to avoid spatial aliasing. To exploit the degrees of freedom (DOFs) in the spatial domain, sparse arrays can be employed for more effective DM design. In this paper, the problem of antenna location optimisation for sparse arrays in the context of DM is addressed for the first time, where compressive sensing based formulations are proposed employing the group sparsity concept. Design examples are provided to verify the effectiveness of the proposed designs.","PeriodicalId":159236,"journal":{"name":"2016 IEEE Sensor Array and Multichannel Signal Processing Workshop (SAM)","volume":"36 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2016-07-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124929648","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: 3
Prediction of stride interval time series 步长间隔时间序列的预测
2016 IEEE Sensor Array and Multichannel Signal Processing Workshop (SAM) Pub Date : 2016-07-10 DOI: 10.1109/SAM.2016.7569660
Etienne Zahnd, J. Brach, S. Perera, E. Sejdić
{"title":"Prediction of stride interval time series","authors":"Etienne Zahnd, J. Brach, S. Perera, E. Sejdić","doi":"10.1109/SAM.2016.7569660","DOIUrl":"https://doi.org/10.1109/SAM.2016.7569660","url":null,"abstract":"The power law in the frequency spectrum S(f) = 1/fβ allows for a good representation of the various time evolution and complex interactions of many physiological processes. The spectral exponent β can be interpreted as the degree of fractal characteristic which in turn makes it some sort of biomarker that gives an idea of the relative health of an individual. The prediction of the 1/fβ time series can thus prove to be an asset in the medical field where forecasting the future health state of an individual can be important for rehabilitation purposes. The goal of this paper is to consider the accuracy of several time series prediction methods such as the neural networks, regression trees and bagged regression trees learning method. To test these methods we simulate stride intervals time series as 1/fβ processes. Our results show that the regression trees can accurately predict between five and fifteen points.","PeriodicalId":159236,"journal":{"name":"2016 IEEE Sensor Array and Multichannel Signal Processing Workshop (SAM)","volume":"38 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2016-07-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127670550","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
Switched-randomized robust PCA for foreground and background separation in video surveillance 切换随机鲁棒PCA用于视频监控的前景和背景分离
2016 IEEE Sensor Array and Multichannel Signal Processing Workshop (SAM) Pub Date : 2016-07-10 DOI: 10.1109/SAM.2016.7569605
M. Kaloorazi, R. Lamare
{"title":"Switched-randomized robust PCA for foreground and background separation in video surveillance","authors":"M. Kaloorazi, R. Lamare","doi":"10.1109/SAM.2016.7569605","DOIUrl":"https://doi.org/10.1109/SAM.2016.7569605","url":null,"abstract":"In this paper we propose a new robust principal component analysis method to separate the background and foreground scenes in video surveillance. Our approach uses a random projection method called Bilateral Random Projections (BRP) in conjunction with a switching between random projection matrices and a singular value estimation technique to separate the background and moving objects. The proposed approach called switched randomized robust principal component analysis (SR-RPCA) switches among different random projection matrices and chooses the best one in order to obtain a lower distortion. To demonstrate the effectiveness of our approach, we conducted experiments on two real-time datasets and experimental results are reported.","PeriodicalId":159236,"journal":{"name":"2016 IEEE Sensor Array and Multichannel Signal Processing Workshop (SAM)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2016-07-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130256989","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: 3
Two-dimensional DOA estimation using parallel coprime subarrays 基于并行协素子阵列的二维DOA估计
2016 IEEE Sensor Array and Multichannel Signal Processing Workshop (SAM) Pub Date : 2016-07-10 DOI: 10.1109/SAM.2016.7569635
Si Qin, Yimin D. Zhang, M. Amin
{"title":"Two-dimensional DOA estimation using parallel coprime subarrays","authors":"Si Qin, Yimin D. Zhang, M. Amin","doi":"10.1109/SAM.2016.7569635","DOIUrl":"https://doi.org/10.1109/SAM.2016.7569635","url":null,"abstract":"A conventional coprime array is a linear array, which consists of two uniform linear subarrays to construct an effective difference coarray with certain desirable characteristics. In this paper, we propose a parallel coprime array structure and a novel algorithm for two-dimensional (2-D) direction-of-arrival (DOA) estimation. By vectorizing the cross-covariance matrix of subarray data, the resulting virtual difference coarray enables resolving more signals than the number of antennas. The 2-D DOA estimation problem is cast as two separate one-dimensional DOA estimation problems, where the estimated azimuth and elevation angles can be properly associated. Compared with other methods, such as, the propagator method (PM) and the rank-reduction (RARE) based algorithms, the proposed method resolves more signals and achieves improved estimation performance.","PeriodicalId":159236,"journal":{"name":"2016 IEEE Sensor Array and Multichannel Signal Processing Workshop (SAM)","volume":"13 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2016-07-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121272029","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: 13
Ambiguity function for sequential antenna selection 序贯天线选择的模糊函数
2016 IEEE Sensor Array and Multichannel Signal Processing Workshop (SAM) Pub Date : 2016-07-10 DOI: 10.1109/SAM.2016.7569753
S. Villeval, J. Tabrikian, I. Bilik
{"title":"Ambiguity function for sequential antenna selection","authors":"S. Villeval, J. Tabrikian, I. Bilik","doi":"10.1109/SAM.2016.7569753","DOIUrl":"https://doi.org/10.1109/SAM.2016.7569753","url":null,"abstract":"In problems with large number of antenna elements and small number of receive channels, sequential antenna selection allows to obtain high spatial accuracy and resolution, similar to the full array configuration. By using this configuration in passive or active array processing, the system cost can be significantly reduced. In conventional single-input multiple-output (SIMO) radar systems, direction-of-arrival (DOA) estimation and Doppler estimation are decoupled. However, sequential antenna selection introduces coupling between DOA and Doppler. In this paper, the ambiguity function of switched antenna radar system is formulated and its properties are investigated. A number of switching schemes are studied and analyzed. It is shown that judicious design of the antenna switching scheme can greatly reduce the sidelobes in the DOA-Doppler ambiguity function.","PeriodicalId":159236,"journal":{"name":"2016 IEEE Sensor Array and Multichannel Signal Processing Workshop (SAM)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2016-07-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130733231","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: 5
Quantifying the repeatability of wireless channels by quantized channel state information 通过量化信道状态信息量化无线信道的可重复性
2016 IEEE Sensor Array and Multichannel Signal Processing Workshop (SAM) Pub Date : 2016-07-10 DOI: 10.1109/SAM.2016.7569702
M. Lerch, S. Caban, E. Zöchmann, M. Rupp
{"title":"Quantifying the repeatability of wireless channels by quantized channel state information","authors":"M. Lerch, S. Caban, E. Zöchmann, M. Rupp","doi":"10.1109/SAM.2016.7569702","DOIUrl":"https://doi.org/10.1109/SAM.2016.7569702","url":null,"abstract":"Repeatability is the prerequisite for scientific evaluation of wireless measurements. However, in real-world scenarios, the channel always slightly changes with time as, for example, trees move in the wind. In this paper, we propose a methodology that uses quantized channel state information and a technique similar to non-substractive SNR-dithering to quantify the repeatablility of wireless channels. Thereby, we introduce a new metric that allows for a comparison of different setups and scenarios in terms of repeatability. In a measurement campaign, we compare (1) a directional link to (2) an outdoor to indoor urban scenario with a fixed receiver and (3) the same scenario with the receiver moving in a circle, thereby experiencing the same high speed channel again and again.","PeriodicalId":159236,"journal":{"name":"2016 IEEE Sensor Array and Multichannel Signal Processing Workshop (SAM)","volume":"8 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2016-07-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129690547","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: 6
Clustering using the fisher-rao distance 使用fisher-rao距离聚类
2016 IEEE Sensor Array and Multichannel Signal Processing Workshop (SAM) Pub Date : 2016-07-10 DOI: 10.1109/SAM.2016.7569717
J. Strapasson, Julianna Pinele, S. Costa
{"title":"Clustering using the fisher-rao distance","authors":"J. Strapasson, Julianna Pinele, S. Costa","doi":"10.1109/SAM.2016.7569717","DOIUrl":"https://doi.org/10.1109/SAM.2016.7569717","url":null,"abstract":"In this paper we consider the Fisher-Rao distance in the space of the multivariate diagonal Gaussian distributions for clustering methods. Centroids in this space are derived and used to introduce two clustering algorithms for diagonal Gaussian mixture models associated to this metric: the k-means and the hierarchical clustering. These algorithms allow to reduce the number of components of such mixture models in the context of image segmentation. The algorithms presented here are compared with the Bregman hard and hierarchical clustering algorithms regarding the advantages of each method in different situations.","PeriodicalId":159236,"journal":{"name":"2016 IEEE Sensor Array and Multichannel Signal Processing Workshop (SAM)","volume":"129 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2016-07-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131611510","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
Selective detection with adaptive channel estimation for MIMO OFDM 基于自适应信道估计的MIMO OFDM选择性检测
2016 IEEE Sensor Array and Multichannel Signal Processing Workshop (SAM) Pub Date : 2016-07-10 DOI: 10.1109/SAM.2016.7569679
Mohammed Kashoob, Y. Zakharov
{"title":"Selective detection with adaptive channel estimation for MIMO OFDM","authors":"Mohammed Kashoob, Y. Zakharov","doi":"10.1109/SAM.2016.7569679","DOIUrl":"https://doi.org/10.1109/SAM.2016.7569679","url":null,"abstract":"In this paper, we investigate the performance of a new selective detection algorithm that is a modification of that proposed in [1]. The channel estimation used is based on adaptive model-based regularization in Multi Input Multi Output (MIMO) OFDM systems. The Basis Expansion Model (BEM) approach is employed for channel estimation. For the adaptive regularization, regularization matrices are computed for a set of uniform power delay profiles. The generalized cross-validation method is then used to select a best matrix from the precomputed set. We compare the performance of the detector implementing the channel estimation with adaptive regularization with the performance of the detector using the Linear Minimum Mean Square Error (LMMSE) channel estimation.","PeriodicalId":159236,"journal":{"name":"2016 IEEE Sensor Array and Multichannel Signal Processing Workshop (SAM)","volume":"55 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2016-07-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115527790","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: 3
Revisiting maximal response-based local identification of overcomplete dictionaries 重述基于最大响应的超完整字典局部识别
2016 IEEE Sensor Array and Multichannel Signal Processing Workshop (SAM) Pub Date : 2016-07-10 DOI: 10.1109/SAM.2016.7569722
Z. Shakeri, W. Bajwa
{"title":"Revisiting maximal response-based local identification of overcomplete dictionaries","authors":"Z. Shakeri, W. Bajwa","doi":"10.1109/SAM.2016.7569722","DOIUrl":"https://doi.org/10.1109/SAM.2016.7569722","url":null,"abstract":"This paper revisits the problem of recovery of an overcomplete dictionary in a local neighborhood from training samples using the so-called maximal response criterion (MRC). While it is known in the literature that MRC can be used for asymptotic exact recovery of a dictionary in a local neighborhood, those results do not allow for linear (in the ambient dimension) scaling of sparsity levels in signal representations. In this paper, a new proof technique is leveraged to establish that MRC can in fact handle linear sparsity (modulo a logarithmic factor) of signal representations. While the focus of this work is on asymptotic exact recovery, the same ideas can be used in a straightforward manner to strengthen the original MRC-based results involving noisy observations and finite number of training samples.","PeriodicalId":159236,"journal":{"name":"2016 IEEE Sensor Array and Multichannel Signal Processing Workshop (SAM)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2016-07-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121289577","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
Radar system design for dual-functionality platforms 双功能平台雷达系统设计
2016 IEEE Sensor Array and Multichannel Signal Processing Workshop (SAM) Pub Date : 2016-07-10 DOI: 10.1109/SAM.2016.7569751
A. Hassanien, M. Amin
{"title":"Radar system design for dual-functionality platforms","authors":"A. Hassanien, M. Amin","doi":"10.1109/SAM.2016.7569751","DOIUrl":"https://doi.org/10.1109/SAM.2016.7569751","url":null,"abstract":"Dual-functionality platforms have recently been proposed to jointly and simultaneously enable radar target illumination and establish wireless communication links. This duality serves as means to alleviate the spectrum congestion crisis. In this paper, we consider the problem of radar system design for dual-function radar-communications (DFRC). We develop a new transmit signaling scheme which permits the embedding of communication symbols in the radar signal emissions. The proposed scheme recognizes the radar and communication signal deliveries as the primary and secondary functions, respectively, and strives to have a minimum impact of the DFRC system on radar operation integrity. In particular, we investigate how the embedding of communication symbols into the radar emission affects the transmit power efficiency. The performance of the proposed technique is validated using simulation examples.","PeriodicalId":159236,"journal":{"name":"2016 IEEE Sensor Array and Multichannel Signal Processing Workshop (SAM)","volume":"7 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2016-07-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128511444","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: 3
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