the following topics are dealt with: arraysignalprocessing; direction-of-arrival estimation; minimisation; MIMO radar; radar signalprocessing; MIMO communication; acoustic signalprocessing; optimisation; covarianc...
the following topics are dealt with: arraysignalprocessing; direction-of-arrival estimation; minimisation; MIMO radar; radar signalprocessing; MIMO communication; acoustic signalprocessing; optimisation; covariance matrices; computational complexity.
the proceedings contain 133 papers. the topics discussed include: SVM-based tool to detect patients with multiple sclerosis using a commercial EMG sensor;hybrid particle filtering based on an elitist resampling scheme...
Many real world applications of target tracking and state estimation are non-linear filtering problems and can therefore not be solved by closed-form analytical solutions. In the recent past, tensor based approaches h...
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ISBN:
(纸本)9781538647523
Many real world applications of target tracking and state estimation are non-linear filtering problems and can therefore not be solved by closed-form analytical solutions. In the recent past, tensor based approaches have become increasingly popular due to very effective decomposition algorithms, which allow the representation of discretized, high-dimensional data in compressed form. In this paper, a solution of the prediction step for a Bayesian filter is proposed, where the probability density function (pdf) is approximated by a tensor in Hierarchical Tucker Decomposition. It is shown, that the computation of the predicted pdf is about five times faster than the previously proposed Canonical Polyadic Decomposition format.
Direction of arrival (DOA) estimation from array observations in a noisy environment is discussed. the source amplitudes are assumed to be correlated zero-mean complex Gaussian distributed with unknown covariance matr...
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ISBN:
(纸本)9781538647523
Direction of arrival (DOA) estimation from array observations in a noisy environment is discussed. the source amplitudes are assumed to be correlated zero-mean complex Gaussian distributed with unknown covariance matrix. the DOAs and covariance parameters of plane waves are estimated from multi-snapshot sensorarray data using sparse Bayesian learning (SBL). the performance of SBL is evaluated in terms of the fidelity of the reconstructed coherency matrix of the estimated plane waves.
In this paper, we address the problem of devising a Quality of Experience (QoE) aware flight plan for UAV mounted Base Station within heterogeneous networks. Specifically, we propose a QoE aware flight planning algori...
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ISBN:
(纸本)9781538647523
In this paper, we address the problem of devising a Quality of Experience (QoE) aware flight plan for UAV mounted Base Station within heterogeneous networks. Specifically, we propose a QoE aware flight planning algorithm leveraging the well established Q-learning approach and introducing a reward related to relevant QoE metrics. Numerical simulation results show the effectiveness of the QoE-aware learning algorithm to devise a flight path such that the UAVs mounted Base Station actually improves the QoE of the heterogeneous network users.
Traditional directional modulation (DM) designs are based on the assumption that there is no multi-path effect between transmitters and receivers. One problem withthese designs is that the resultant systems will be v...
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ISBN:
(纸本)9781538647523
Traditional directional modulation (DM) designs are based on the assumption that there is no multi-path effect between transmitters and receivers. One problem withthese designs is that the resultant systems will be vulnerable to eavesdroppers which are aligned with or very close to the desired directions, as the received modulation pattern at these positions is similar to the given one. To solve the problem, a two-ray multi-path model is studied for positional modulation and the coefficients design problem for a given array geometry and a location-optimised antenna array is solved, where the multi-path effect is exploited to generate a given modulation pattern at desired positions, with scrambled values at positions around them.
Sparse sensorarrays can achieve significantly more degrees of freedom than the number of elements by leveraging the co-array, a virtual structure that arises from the far field narrowband signal model. Although sever...
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ISBN:
(纸本)9781538647523
Sparse sensorarrays can achieve significantly more degrees of freedom than the number of elements by leveraging the co-array, a virtual structure that arises from the far field narrowband signal model. Although several sparse array configurations have been developed for passive sensing tasks, less attention has been paid to arrays suitable for active sensing. this paper presents a novel active sparse linear array, called the Interleaved Wichmann array (IWA). the IWA only has a few closely spaced elements, which may make it more robust to mutual coupling effects. Closed-form expressions are provided for the key properties of the IWA. the parameters maximizing the array aperture for a given even number of elements are also found. the near field wideband performance of the array is demonstrated numerically in a coherent imaging scenario.
In this paper, we apply a nonlinear frequency modulation scheme based on arctangent function to waveform diverse array system to design a transmitted beampattern to focus the signal power at a specific position. Disti...
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ISBN:
(纸本)9781538647523
In this paper, we apply a nonlinear frequency modulation scheme based on arctangent function to waveform diverse array system to design a transmitted beampattern to focus the signal power at a specific position. Distinct from most of the existing methodologies, the proposed method overcomes the problem that the focusing performance of the signal power will decrease when considering the propagation process of the transmitted signal. As a result, the transmitted signal power can be focused at a desired position and be lasting for a period of time. Numerical simulations validate the theoretical analysis of the proposed methodology.
Target parameter estimation from noisy and quantized received signals is of paramount importance in radar applications. In this paper, we propose a novel method to estimate the unknown target parameters via one-bit sa...
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ISBN:
(纸本)9781538647523
Target parameter estimation from noisy and quantized received signals is of paramount importance in radar applications. In this paper, we propose a novel method to estimate the unknown target parameters via one-bit sampling, where the samples are produced by comparing the received signal with a time-varying threshold. the proposed approach utilizes a weighted least-squares criterion to establish a connection to previous results in radar target estimation and signalprocessing. Several numerical examples are provided to demonstrate the effectiveness of the proposed approach.
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.
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