sensor networks offer an opportunity for improving submarine detection. Let each sensor firstly make a binary local decision-'0' or '1', and then a fusion center collects them to make a system-level in...
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ISBN:
(纸本)9781467310710
sensor networks offer an opportunity for improving submarine detection. Let each sensor firstly make a binary local decision-'0' or '1', and then a fusion center collects them to make a system-level inference without knowledge of probabilities of local detection. An obvious strategy is a counting rule test, which simply counts the total number of 1's and compares it to a threshold. This approach equally considers all network subareas. However, reflected signals from a submarine are highly aspect dependent, and in many instances only sensors in a particular zone could receive the echoes. This paper focuses on the scan statistic, which slides a window across the sensor field, and selects the subarea with the largest number of 1's to make a decision. The scan statistic integrates the spatial distinction of local decisions into detection fusion. With a proper window size, it may suppress subarea interference, and improve system-level performance.
Space Time Adaptive processing. STAP) is a two-dimensional adaptive filtering technique which uses jointly temporal and spatial dimensions to suppress disturbance and to improve target detection. Disturbance contains ...
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ISBN:
(纸本)9781467310710
Space Time Adaptive processing. STAP) is a two-dimensional adaptive filtering technique which uses jointly temporal and spatial dimensions to suppress disturbance and to improve target detection. Disturbance contains both the clutter arriving from signal backscattering of the ground and the thermal noise resulting from the sensors noise. In practical cases, the STAP clutter can be considered to have a low rank structure. Using this assumption, a low rank vector STAP filter is derived based on the projector onto the clutter subspace. With new STAP applications like MIMO STAP or polarimetric STAP, the generalization of the classic filters to multidimensional configurations arises. A possible solution consists in keeping the multidimensional structure and in extending the classic filters with multilinear algebra. Using the low-rank structure of the clutter, we propose in this paper a new low-rank tensor STAP filter based on a generalization of the Higher Order Singular Value Decomposition. HOSVD) in order to use at the same time the simple. for example time, spatial, polarimetric, ...) and the combined information. for example spatio-temporal). Results are shown for two cases : classic 2D STAP and 3D polarimetric STAP. In the classic case, vector and tensor filters are equivalent. In the polarimetric case, we show the enhancement of the tensor filter.
A heterogeneous Markov chain (MC) model, instead of the homogeneous MC model, is proposed in this paper to describe target existence variable for Bayesian track-before-detect. The proposed model is more consistent wit...
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We study channel-aware binary decision fusion over a Rayleigh flat fading shared channel with multiple antennas at the Decision Fusion Center (DFC). We derive the optimum and three sub-optimal fusion rules, namely the...
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The delay constraints imposed by future wireless applications require a suitable metric for assessing their impact on the overall system performance. Since the classical Shannon's ergodic capacity fails to do so, ...
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The proceedings contain 68 papers. The topics discussed include: target tracking in mixed LOS/NLOS environments based on individual TOA measurement detection;band-diagonal regularization of Gaussian interference covar...
ISBN:
(纸本)9781424489770
The proceedings contain 68 papers. The topics discussed include: target tracking in mixed LOS/NLOS environments based on individual TOA measurement detection;band-diagonal regularization of Gaussian interference covariance matrices ml estimates;combining multiband joint position-pitch algorithm and particle filters for speaker localization;a reference-free time difference of arrival source localization using a passive sensorarray;the breakdown point of signal subspace estimation;hypothesis testing in high-dimensional space with the sparse matrix transform;likelihood-ratio and channel based access for energy-efficient detection in wireless sensor networks;on Toeplitz and Kronecker structured covariance matrix estimation;robust focusing for wideband MVDR beamforming;nonparametric Bayesian matrix completion;and expected likelihood support for deterministic maximum likelihood DOA estimation.
This paper considers consensus control problem of multiple nonlinear systems with uncertainty. Consensus algorithms are proposed with the aid of Lyapunov techniques and results from graph theory. To show the effective...
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This paper considers consensus control problem of multiple nonlinear systems with uncertainty. Consensus algorithms are proposed with the aid of Lyapunov techniques and results from graph theory. To show the effectiveness of the proposed algorithms, simulation results are presented.
We propose a low complexity arrayprocessing method for differential detection of OFDM signals over underwater acoustic channels. Partial FFT technique, developed previously for mitigating inter-carrier interference i...
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We propose a low complexity arrayprocessing method for differential detection of OFDM signals over underwater acoustic channels. Partial FFT technique, developed previously for mitigating inter-carrier interference in single-channel receivers operating over time-varying channels, is extended to multichannel configuration. Performance results based on simulation and experimental data demonstrate the advantage of the proposed method compared to conventional differential and coherent detection.
A heterogeneous Markov chain (MC) model, instead of the homogeneous MC model, is proposed in this paper to describe target existence variable for Bayesian track-before-detect. The proposed model is more consistent wit...
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A heterogeneous Markov chain (MC) model, instead of the homogeneous MC model, is proposed in this paper to describe target existence variable for Bayesian track-before-detect. The proposed model is more consistent with the transitions of target existence variable, which leads to the improvement of the performance of detection and tracking.
In this paper, we develop a new class of time division multiple access schemes for bi-directional multiuser communications in cooperative amplify-and-forward relay networks. The proposed schemes enable a flexible trad...
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In this paper, we develop a new class of time division multiple access schemes for bi-directional multiuser communications in cooperative amplify-and-forward relay networks. The proposed schemes enable a flexible trade-off between spectral efficiency and suppression of multiuser interference. The relay weights are chosen to maximize the minimum received quality-of-service of all the users under constraints on the individual and the total power at the relays. Simulation results demonstrate that the selection of the scheme has a considerable impact on the achieved throughput of the relay network.
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