It is well known that parameter estimation algorithms designed to exploit the prior knowledge of the strict second-order (SO) non-circularity (NC) of incident signals can estimate the parameters of twice as many sourc...
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It is well known that parameter estimation algorithms designed to exploit the prior knowledge of the strict second-order (SO) non-circularity (NC) of incident signals can estimate the parameters of twice as many sources and achieve significant gains in reducing the estimation error. So far, the magnitude of the NC gain could only be quantified through simulations and finding a generic analytical expression for arbitrary scenarios is an intricate task. In this paper, we adopt a first-order performance analysis framework to analytically compute the asymptotic NC gain of NC Standard ESPRIT for the case of two uncorrelated strictly SO non-circular (rectilinear) sources captured by a uniform linear array (ULA). We assume a maximum phase separation of the sources, which yields the largest NC gain. For this scenario, we derive simplified asymptotic mean squared error (MSE) expressions of NC Standard ESPRIT and Standard ESPRIT, which are subsequently used to compute the NC gain. While the simplified MSE expression of Standard ESPRIT depends on the source separation, we show that if NC Standard ESPRIT is applied in this case, the two non-circular sources entirely decouple. Thus, the NC gain can theoretically approach infinity if the separation of the two sources tends to zero. Our derived expressions are verified by simulation results.
The following topics are dealt with: arrayprocessing for communications; DOA estimation and localization; radar; sensor networks and distributed estimation; beamforming; speech/audio/acoustic arrayprocessing; detect...
The following topics are dealt with: arrayprocessing for communications; DOA estimation and localization; radar; sensor networks and distributed estimation; beamforming; speech/audio/acoustic arrayprocessing; detection and estimation; blind source separation.
The performance of the multi-channel Wiener filter (MWF), which is often used for noise reduction in speech enhancement applications, depends on the noise field and on the acoustic transfer functions (ATFs) between th...
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The performance of the multi-channel Wiener filter (MWF), which is often used for noise reduction in speech enhancement applications, depends on the noise field and on the acoustic transfer functions (ATFs) between the desired source and the microphone array. Recently, using statistical room acoustics an analytical expression for the spatially averaged output SNR, given the relative distance between the source and the microphone array, has been derived for the MWF in a diffuse noise field, requiring only the room properties to be known. In this paper, we show that this analytical expression can be extended to compute the average output SNR of the MWF for a specific microphone configuration, enabling to compare the performance of different microphone configurations, e.g. in an acoustic sensor network. Simulation results show that the average output SNR obtained using the statistical properties of ATFs is similar to the average output SNR obtained using simulated ATFs, therefore providing an efficient way to compare different microphone configurations.
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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ISBN:
(纸本)9781467310710
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.
This paper investigates an adaptive beamforming technique that is robust against imperfect knowledge of signal and interference arrival directions, antenna calibration errors and other similar imperfections. The propo...
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ISBN:
(纸本)9781467310710
This paper investigates an adaptive beamforming technique that is robust against imperfect knowledge of signal and interference arrival directions, antenna calibration errors and other similar imperfections. The proposed technique is based on Generalized Sidelobe Canceller but uses Slepian sequences in both the steering and blocking lobes of the algorithm. Only Slepians corresponding to large spectral concentrations are used in the branches. The theoretical results are verified in a simulation study.
In this paper we derive a generic signalprocessing model for oversampled linear antenna arrays based on network theory and Nyquist sampling theory. The theoretical model is verified with experimental data collected o...
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ISBN:
(纸本)9781467310710
In this paper we derive a generic signalprocessing model for oversampled linear antenna arrays based on network theory and Nyquist sampling theory. The theoretical model is verified with experimental data collected on an HF OTHR receive array.
PATENT PENDING. Time-of-arrival (TOA) localization is tightly coupled with sensor time synchronization. Synchronization can be obtained by GPS, atomic clocks or message exchange protocols. All methods affect the energ...
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ISBN:
(纸本)9781467310710
PATENT PENDING. Time-of-arrival (TOA) localization is tightly coupled with sensor time synchronization. Synchronization can be obtained by GPS, atomic clocks or message exchange protocols. All methods affect the energy sources and the synchronization protocols use valuable bandwidth. We present self-synchronized localization algorithms that rely exclusively on TOA measurements performed by the sensor network on passing sources rendering it completely passive. Localization performance is close to that provided by a perfectly synchronized network. Such algorithms can also be used for sensor network synchronization and communication networks in general.
In this work, we propose a distributed power control algorithm able to capture the tradeoff between detection capabilities and power consumption for a radar sensor network. This is achieved by modeling the radar senso...
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ISBN:
(纸本)9781467310710
In this work, we propose a distributed power control algorithm able to capture the tradeoff between detection capabilities and power consumption for a radar sensor network. This is achieved by modeling the radar sensors as rational agents engaging in a noncooperative game in which the detection threshold and the transmit power are properly designed according to the Nash equilibrium solution. An iterative algorithm based on a best-response dynamics is proposed to achieve the equilibrium point and its performance is compared to that achieved by a uniform power allocation.
An adaptive algorithm for azimuth-angle estimation of moving sources in the presence of array nonidealities is proposed. The method, termed unitary element-space Capon (UES-Capon) beamformer, is robust in the face of ...
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ISBN:
(纸本)9781467310710
An adaptive algorithm for azimuth-angle estimation of moving sources in the presence of array nonidealities is proposed. The method, termed unitary element-space Capon (UES-Capon) beamformer, is robust in the face of small number of snapshots and fully takes into account effects such as mutual coupling, mounting platform reflections, and sensor's misplacement errors. Unlike most of the robust beamformers available in the literature, the proposed method is based on QR-decomposition and real-valued polynomial root tracking. Furthermore, it is applicable to sensorarrays of arbitrary configuration. Numerical results using a real-world antenna array are included, illustrating the excellent performance of the proposed method, both in terms of SINR and fast adaptivity to moving sources.
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