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2007 2nd IEEE International Workshop on Computational Advances in Multi-Sensor Adaptive Processing最新文献

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Particle Filtering-Based Target Tracking in Binary Sensor Networks Using Adaptive Thresholds 基于粒子滤波的自适应阈值二值传感器网络目标跟踪
2007 2nd IEEE International Workshop on Computational Advances in Multi-Sensor Adaptive Processing Pub Date : 2007-12-01 DOI: 10.1109/CAMSAP.2007.4497954
M. Vemula, M. Bugallo, P. Djuric
{"title":"Particle Filtering-Based Target Tracking in Binary Sensor Networks Using Adaptive Thresholds","authors":"M. Vemula, M. Bugallo, P. Djuric","doi":"10.1109/CAMSAP.2007.4497954","DOIUrl":"https://doi.org/10.1109/CAMSAP.2007.4497954","url":null,"abstract":"Target tracking in wireless sensor networks with constrained resources is a challenging problem. In this paper we consider scenarios where sensors sense an object of interest and process the received measurements using adaptive thresholds to obtain quantized data in the form of two levels. The data are quantized to address resource constraints in sensor networks. The processed data are then sent to a fusion center which resolves the tracking problem by means of a particle filter which can handle non-linearities in the state model. The performance of various strategies for threshold adaptation is studied by computer simulations and the results reveal that improvement is obtained over scenarios with fixed thresholds.","PeriodicalId":220687,"journal":{"name":"2007 2nd IEEE International Workshop on Computational Advances in Multi-Sensor Adaptive Processing","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2007-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131065178","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: 11
Radar Estimation of Building Layouts Using Jump-Diffusion 基于跳跃扩散的建筑布局雷达估计
2007 2nd IEEE International Workshop on Computational Advances in Multi-Sensor Adaptive Processing Pub Date : 2007-12-01 DOI: 10.1109/CAMSAP.2007.4497994
M. Nikolic, M. Ortner, A. Nehorai, A. Djordjevic
{"title":"Radar Estimation of Building Layouts Using Jump-Diffusion","authors":"M. Nikolic, M. Ortner, A. Nehorai, A. Djordjevic","doi":"10.1109/CAMSAP.2007.4497994","DOIUrl":"https://doi.org/10.1109/CAMSAP.2007.4497994","url":null,"abstract":"Estimating buildings layouts using exterior radar measurements is a challenging task involving the electromagnetic modeling, many unknown parameters, and limited number of sensors. We propose using the jump-diffusion algorithm as a powerful stochastic tool that can be used to determine the number of walls, estimate their unknown positions and other parameters. We improve the convergence rate of the jump-diffusion algorithm by developing an iterative procedure that first finds low- resolution estimates, which are then used to initiate our more accurate estimation. Our efficient usage of the available frequency bandwidth, improves the computational speed that otherwise would be hampered by the forward electromagnetic modeling.","PeriodicalId":220687,"journal":{"name":"2007 2nd IEEE International Workshop on Computational Advances in Multi-Sensor Adaptive Processing","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2007-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"134097685","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
Maximum A Posteriori Estimation of Time Delay 时延的最大后验估计
2007 2nd IEEE International Workshop on Computational Advances in Multi-Sensor Adaptive Processing Pub Date : 2007-12-01 DOI: 10.1109/CAMSAP.2007.4498021
Bowon Lee, T. Kalker
{"title":"Maximum A Posteriori Estimation of Time Delay","authors":"Bowon Lee, T. Kalker","doi":"10.1109/CAMSAP.2007.4498021","DOIUrl":"https://doi.org/10.1109/CAMSAP.2007.4498021","url":null,"abstract":"Time-delay estimation (TDE) is an important topic of array signal processing for applications such as source localization and beam-forming. With a pair of sensors, the generalized cross correlation (GCC) method is widely used for TDE and the maximum-likelihood (ML) estimation can be considered as a GCC prefilter. Unfortunately, the ML estimation suffers from performance degradation due to the limitation of having only finite duration signals available for estimating source and noise power spectral densities. Also, its optimality is governed by the signal to noise ratio (SNR) and multipath environments. In this paper, we propose a method of Maximum a posteriori (MAP) estimation of time delay based on the ML estimation by modeling the prior probability of time delay. Experimental results show that the proposed method outperforms the conventional ML estimation. It also ourperforms the phase transform (PHAT) method with moderate SNR in multipath environments.","PeriodicalId":220687,"journal":{"name":"2007 2nd IEEE International Workshop on Computational Advances in Multi-Sensor Adaptive Processing","volume":"66 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2007-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116076454","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
Remote Sensing Signature Fields Reconstruction Via Robust Regularization of Bayesian Minimum Risk Technique 基于贝叶斯最小风险鲁棒正则化技术的遥感特征场重建
2007 2nd IEEE International Workshop on Computational Advances in Multi-Sensor Adaptive Processing Pub Date : 2007-12-01 DOI: 10.1109/CAMSAP.2007.4498009
Y. Shkvarko, I. Villalón-Turrubiates, J.L. Leyva-Montiel
{"title":"Remote Sensing Signature Fields Reconstruction Via Robust Regularization of Bayesian Minimum Risk Technique","authors":"Y. Shkvarko, I. Villalón-Turrubiates, J.L. Leyva-Montiel","doi":"10.1109/CAMSAP.2007.4498009","DOIUrl":"https://doi.org/10.1109/CAMSAP.2007.4498009","url":null,"abstract":"The robust numerical technique for high-resolution reconstructive imaging and scene analysis is developed as required for enhanced remote sensing with large scale sensor array radar/synthetic aperture radar. The problem-oriented modification of the previously proposed fused Bayesian-regularization (FBR) enhanced radar imaging method is performed to enable it to reconstruct remote sensing signatures (RSS) of interest alleviating problem ill-poseness due to system-level and model-level uncertainties. We report some simulation results of hydrological RSS reconstruction from enhanced real-world environmental images indicative of the efficiency of the developed method.","PeriodicalId":220687,"journal":{"name":"2007 2nd IEEE International Workshop on Computational Advances in Multi-Sensor Adaptive Processing","volume":"4 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2007-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121443502","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
An Effective Global Optimization Algorithm for Wireless Mimo Channel Estimation 一种有效的无线Mimo信道估计全局优化算法
2007 2nd IEEE International Workshop on Computational Advances in Multi-Sensor Adaptive Processing Pub Date : 2007-12-01 DOI: 10.1109/CAMSAP.2007.4498006
H. Tuan, H. Nguyen, N. N. Tran, V. Nguyen
{"title":"An Effective Global Optimization Algorithm for Wireless Mimo Channel Estimation","authors":"H. Tuan, H. Nguyen, N. N. Tran, V. Nguyen","doi":"10.1109/CAMSAP.2007.4498006","DOIUrl":"https://doi.org/10.1109/CAMSAP.2007.4498006","url":null,"abstract":"The problem of channel estimation for spatially correlated fading multiple-input multiple-output (MIMO) channels is considered. Based on the channel's second order statistic, the minimum mean-square error (MMSE) channel estimator that works with the superimposed training signal is proposed. The problem of designing the optimal superimposed signal is then addressed and solved with an iterative global optimization algorithm. Simulation results show that our optimal design of the superimposed training signal leads to a significant reduction in channel estimation error when compared to the conventional design of time-multiplexing training.","PeriodicalId":220687,"journal":{"name":"2007 2nd IEEE International Workshop on Computational Advances in Multi-Sensor Adaptive Processing","volume":"108 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2007-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124155421","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: 4
Reduction of Spatial Sampling Requirement in Sound-Based Synthesis 降低基于声音合成的空间采样要求
2007 2nd IEEE International Workshop on Computational Advances in Multi-Sensor Adaptive Processing Pub Date : 2007-12-01 DOI: 10.1109/CAMSAP.2007.4498022
Cac T. Nguyen, R. Morrison, M. Do
{"title":"Reduction of Spatial Sampling Requirement in Sound-Based Synthesis","authors":"Cac T. Nguyen, R. Morrison, M. Do","doi":"10.1109/CAMSAP.2007.4498022","DOIUrl":"https://doi.org/10.1109/CAMSAP.2007.4498022","url":null,"abstract":"We study the problem of synthesizing the sound field at arbitrary locations and times from the recordings of an array of audio sensors. Given prior estimates of the locations and frequencies of the sound sources, such as those obtained using adaptive source localization, we characterize the spatio-temporal support of the sound field spectrum. This characterization allows the spatial sampling requirements to be reduced in comparison to when no prior estimates of the sources are utilized. We derive an adaptive interpolation kernel, based on the estimated spectral support, to reconstruct the sound-field function using measurements from sensors on a coarse spatial-sampling grid. Simulation results demonstrate the gain achieved in reduced sampling requirements by using the proposed adaptive interpolation approach.","PeriodicalId":220687,"journal":{"name":"2007 2nd IEEE International Workshop on Computational Advances in Multi-Sensor Adaptive Processing","volume":"5 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2007-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122142313","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
Wireless EGG Monitor 无线卵子监测仪
2007 2nd IEEE International Workshop on Computational Advances in Multi-Sensor Adaptive Processing Pub Date : 2007-12-01 DOI: 10.1109/CAMSAP.2007.4497990
E. R. Grigorian, R. Adhami, O. Toutonji
{"title":"Wireless EGG Monitor","authors":"E. R. Grigorian, R. Adhami, O. Toutonji","doi":"10.1109/CAMSAP.2007.4497990","DOIUrl":"https://doi.org/10.1109/CAMSAP.2007.4497990","url":null,"abstract":"Real time monitoring and detection of abnormal heart rhythms, specifically through acquisition of electrocardiogram (ECG) signals for extended periods (24 to 48 hours) have been sought by many researchers. Abnormal ECG signals could appear any time in the day during regular patient activities. Spurious noise associated with motion and muscular contraction is usually coupled with the acquired ECG signal. Cancelling muscle contraction and motion artifacts from real time ECG signals is extremely vital for accurate ECG signal classification for analysis by trained medical specialists. The intent of this research was to develop a bi-electrode wireless acquisition system that captured and transmitted ECG signals and motion acceleration information to a host computer system for data capture and analysis. The designed wireless ECG system includes a 3-axis micro electromechanical (MEMS) accelerometer for motion detection.","PeriodicalId":220687,"journal":{"name":"2007 2nd IEEE International Workshop on Computational Advances in Multi-Sensor Adaptive Processing","volume":"6 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2007-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127790669","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
Multichannel Particle Filters for Tracking A Frequency Hopped Signal 用于跟踪跳频信号的多通道粒子滤波器
2007 2nd IEEE International Workshop on Computational Advances in Multi-Sensor Adaptive Processing Pub Date : 2007-12-01 DOI: 10.1109/CAMSAP.2007.4498013
A. Valyrakis, N. Sidiropoulos, A. Swami
{"title":"Multichannel Particle Filters for Tracking A Frequency Hopped Signal","authors":"A. Valyrakis, N. Sidiropoulos, A. Swami","doi":"10.1109/CAMSAP.2007.4498013","DOIUrl":"https://doi.org/10.1109/CAMSAP.2007.4498013","url":null,"abstract":"We consider the problem of tracking a frequency-hopped signal without knowledge of its hopping pattern. The problem is of interest in military communications, where, in addition to frequency, hop timing may also be randomly shifted to guard against unauthorized reception and jamming. We have recently proposed (Sidiropoulos et al., 2006) a conceptually simple stochastic state-space model that captures the randomness in carrier frequency and hop timing, and is well- suited for application of particle filtering tools. In this contribution, we generalize the approach in (Sidiropoulos et al., 2006) to the multichannel case. In particular, we show that the importance function that minimizes the variance of particle weights can again be computed in closed form. The resulting multichannel particle filters are assessed and compared to their single-channel counterparts in pertinent simulation experiments.","PeriodicalId":220687,"journal":{"name":"2007 2nd IEEE International Workshop on Computational Advances in Multi-Sensor Adaptive Processing","volume":"34 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2007-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132251989","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
Analysis of the Cramer-Rao Bound Integrating a Prior-Knowledge 基于先验知识的Cramer-Rao界分析
2007 2nd IEEE International Workshop on Computational Advances in Multi-Sensor Adaptive Processing Pub Date : 2007-12-01 DOI: 10.1109/CAMSAP.2007.4497956
R. Boyer
{"title":"Analysis of the Cramer-Rao Bound Integrating a Prior-Knowledge","authors":"R. Boyer","doi":"10.1109/CAMSAP.2007.4497956","DOIUrl":"https://doi.org/10.1109/CAMSAP.2007.4497956","url":null,"abstract":"Introducing prior-knowledge of some damped/undamped poles in the estimation of the parameters of a mutlipoles sinusoidal model is an important problem as for instance in bearing estimation or in biomedical signal analysis. The principle is to orthogonally project the data onto the noise space associated with the known poles. As the Cramer-Rao Lower Bound (CRB) gives a benchmark against which algorithms performance can be compared, it is useful to derive the CRB associated with this model, named Prior-CRB (P-CRB). In particular, we analyze this bound in the context of close subspaces context, ie., when the known poles are close to the unknown ones.","PeriodicalId":220687,"journal":{"name":"2007 2nd IEEE International Workshop on Computational Advances in Multi-Sensor Adaptive Processing","volume":"10 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2007-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132098864","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
Bayesian Processing for the Detection of Radioactive Contraband from Uncertain Measurements 不确定测量中放射性违禁品检测的贝叶斯处理
2007 2nd IEEE International Workshop on Computational Advances in Multi-Sensor Adaptive Processing Pub Date : 2007-06-26 DOI: 10.1109/CAMSAP.2007.4497962
J. Candy, K. Sale, B. Guidry, E. Breitfeller, D. Manatt, D. Chambers, A. Meyer
{"title":"Bayesian Processing for the Detection of Radioactive Contraband from Uncertain Measurements","authors":"J. Candy, K. Sale, B. Guidry, E. Breitfeller, D. Manatt, D. Chambers, A. Meyer","doi":"10.1109/CAMSAP.2007.4497962","DOIUrl":"https://doi.org/10.1109/CAMSAP.2007.4497962","url":null,"abstract":"With the increase in terrorist activities throughout the world, the need to develop techniques capable of detecting radioactive contraband in a timely manner is a critical requirement. The development of Bayesian processors for the detection of contraband stems from the fact that the posterior distribution is clearly multimodal eliminating the usual Gaussian-based processors. The development of a sequential bootstrap processor for this problem is discussed and shown how it is capable of providing an enhanced signal for eventual detection.","PeriodicalId":220687,"journal":{"name":"2007 2nd IEEE International Workshop on Computational Advances in Multi-Sensor Adaptive Processing","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2007-06-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131061776","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: 4
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