This paper deals with the issue of monitoring physical phenomena using wireless sensor networks. It provides principal component analysis for the time series of sensors' measurements. Without the need to compute t...
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ISBN:
(纸本)9781479914814
This paper deals with the issue of monitoring physical phenomena using wireless sensor networks. It provides principal component analysis for the time series of sensors' measurements. Without the need to compute the sample covariance matrix, we derive several in-network strategies to estimate the principal axis, including noncooperative and diffusion strategies. The performance of the proposed strategies is illustrated in the issue of monitoring gas diffusion.
In this paper, random switch antenna array (RSAA) is proposed to apply to the switch antenna array (SAA) frequency-modulated continuous-wave (FMCW) radar system. Firstly, the signal model and signalprocessing method ...
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ISBN:
(纸本)9781467310710
In this paper, random switch antenna array (RSAA) is proposed to apply to the switch antenna array (SAA) frequency-modulated continuous-wave (FMCW) radar system. Firstly, the signal model and signalprocessing method of RSAA is analyzed and it shows that RSAA can successfully solve azimuth-velocity coupling problem. Then we suppose a method by using RSAA to reduce the switching frequency and sampling rate based on sparse signal representation with multiple measurement vectors (MMV). It is shown in simulations that the proposed algorithms yield better performance in terms of azimuth-velocity decoupling and can obtain high image accuracy with less observation data.
In this paper, we propose angle of arrival estimation algorithms for arbitrary array geometries. The proposed methods extend the root-WSF [1] and Modified Variable Projection (MVP) [2] algorithms to arbitrary array co...
ISBN:
(纸本)9781424422401
In this paper, we propose angle of arrival estimation algorithms for arbitrary array geometries. The proposed methods extend the root-WSF [1] and Modified Variable Projection (MVP) [2] algorithms to arbitrary array configurations. This is accomplished by employing the recently introduced Manifold Separation Technique (MST) [3], which stems from wavefield modelling [4]. The algorithms process the data in the element-space domain, i.e. no mapping of the data that introduces errors is required. Moreover, coherent sources can be handled. The proposed MST-based MVP algorithm shows a statistical performance close to the Cramer-Rao Lower Bound (CRLB) [5, 6]. The performance is illustrated using calibration data from two real-world arrays.
A large size phased array is a powerful system for surveillance, but must be appropriately decomposed as subarrays for efficient digital beamforming. One fundamental question is how to configure a large array as subar...
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ISBN:
(纸本)9781538647523
A large size phased array is a powerful system for surveillance, but must be appropriately decomposed as subarrays for efficient digital beamforming. One fundamental question is how to configure a large array as subarrays to satisfy various signalprocessing requirements. This work deals with two basic signalprocessing tasks, synthesizing multiple beams at subarray level and adaptively suppressing multiple interferences. Two optimization criteria to jointly design subarray configuration and digital weights for subarrays are proposed. To handle the large number of variables in the optimization formulations, we propose an alternating minimization approach with low computation cost. Numerical simulations are presented to demonstrate the effectiveness of the proposed algorithm.
This paper presents a statistical analysis of two schemes for intelligent STAP training data selection in Gaussian and non-Gaussian interference backgrounds. Performance analysis of the two methods is carried out usin...
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ISBN:
(纸本)0780375513
This paper presents a statistical analysis of two schemes for intelligent STAP training data selection in Gaussian and non-Gaussian interference backgrounds. Performance analysis of the two methods is carried out using simulated as well as measured radar data.
Direction-of-arrival (DOA) estimation is an interesting research topic with various applications. Existing algorithms provide superior estimation performance, at the cost of accurate quantified measurements. In this p...
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ISBN:
(纸本)9781728119465
Direction-of-arrival (DOA) estimation is an interesting research topic with various applications. Existing algorithms provide superior estimation performance, at the cost of accurate quantified measurements. In this paper, we stress the problem of 2D DOA estimation for uniform rectangular array using one-bit measurements. The relationship between the covariance matrices of one-bit measurement and that of the accurately quantified measurement is analyzed in detail, from which we find the existing tensor algorithm can be directly applied. As a result, a one-bit parallel factor analysis (PARAFAC) estimator is proposed. Simulation results show the effectiveness of the proposed method.
In this paper, we consider distributed signalprocessing in a MIMO radar network. We suppose that transmitting and receiving nodes of MIMO radar are distributed in a large-scale area. In this network the neighboring r...
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ISBN:
(纸本)9781538647523
In this paper, we consider distributed signalprocessing in a MIMO radar network. We suppose that transmitting and receiving nodes of MIMO radar are distributed in a large-scale area. In this network the neighboring receiving nodes communicate with each other to exchange data. A fully distributed algorithm for detection and imaging is proposed. This algorithm is based on the averaging consensus approach. The effectiveness of the proposed technique is confirmed by numerical examples. It is compared to the centralized solution in a fusion center, the local solution in an individual receiving node and the proposed distributed algorithm.
The ambiguity problem in direction-of-arrival (DOA) estimation using a sensorarray, manifests itself as spurious peaks in the DOA spectrum, making the true targets indistinguishable from the false alarms. A criterion...
ISBN:
(纸本)0780375513
The ambiguity problem in direction-of-arrival (DOA) estimation using a sensorarray, manifests itself as spurious peaks in the DOA spectrum, making the true targets indistinguishable from the false alarms. A criterion that determines the presence of certain ambiguities inherent to a symmetric linear array was proposed in the literature. The criterion is a useful tool to design reliable sensorarrays. In this paper, a generalization of this ambiguity criterion is presented. The new ambiguity criterion encompasses more ambiguous DOAs and therefore gives a more accurate measurement of the reliability of an array design.
The problem of optimal node density for ad hoc sensor networks deployed for making inferences about two dimensional correlated random fields is considered. Using a symmetric first order conditional autoregressive Gaus...
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ISBN:
(纸本)9781424422401
The problem of optimal node density for ad hoc sensor networks deployed for making inferences about two dimensional correlated random fields is considered. Using a symmetric first order conditional autoregressive Gauss-Markov random field model, large deviations results are used to characterize the asymptotic per-node information gained from the array. This result then allows an analysis of the node density that maximizes the information under an energy constraints yielding insights into the trade-offs among the information, density and energy.
We describe a method of tuning a simple detection process of stationary targets in SAR images. The tuning metric accounts for the squared-error performance of prescient estimators of target location and reflectivity. ...
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ISBN:
(纸本)1424403081
We describe a method of tuning a simple detection process of stationary targets in SAR images. The tuning metric accounts for the squared-error performance of prescient estimators of target location and reflectivity. The efficiencies of these prescient estimators are compared to their Cramer Rao bounds (CRBs). The off-line tuning is performed by collecting statistics of scatterer estimation in SAR images created using sparse-array spotlight mode simulations.
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