State-of-the-art hearing aids (HAs) can connect to a wireless microphone worn by a talker of interest. this ability allows HAs to have access to almost noise-free sound signals of the target talker. In this paper, we ...
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ISBN:
(纸本)9781538647523
State-of-the-art hearing aids (HAs) can connect to a wireless microphone worn by a talker of interest. this ability allows HAs to have access to almost noise-free sound signals of the target talker. In this paper, we aim to estimate the direction of arrival (DoA) of the target signal, given access to the noise-free target signal. Knowing the DoA of the target signal enables HAs to spatialize the wirelessly received target signals. the proposed estimator is based on a maximum likelihood (ML) approach and a database of DoA-dependent relative transfer functions (RTFs), and it supports both monaural and binaural microphone array configurations. For binaural configurations, we propose an information fusion strategy, which decreases the number of parameters required to be wirelessly transferred between the HAs. Further, we show that the proposed method not only has lower computational complexity, but also performs better than recent DoA estimators, which have access to the noise-free target signal.
In recent years, the frequency diverse array (FDA) radar has attracted much attention due to its range-angle dependent beam-pattern. And multiple input multiple output (MIMO) radar has been widely investigated withth...
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ISBN:
(纸本)9781538647523
In recent years, the frequency diverse array (FDA) radar has attracted much attention due to its range-angle dependent beam-pattern. And multiple input multiple output (MIMO) radar has been widely investigated withthe advantage of transmit waveform diversity. In this paper, a FDA-MIMO Inverse Synthetic Aperture Radar (ISAR) is proposed to achieve anti-jamming of ISAR imaging. LFM (Linear Frequency Modulated) and SFCS (Stepped-Frequency Chirp signal) signals are transmitted to jammer and targets respectively, and the received signals are matched filtering by the signal transmitted to the targets. So the jamming signal can't matched withthe reference signal, the well anti-jamming effect can be obtained. the performance of the proposed method is evaluated by the simulation results.
In distributed sensor networks, the posterior Cramer-Rao lower bound (PCRLB) has recently been used [1] as a selection criteria for sensor management decisions, where new sensor nodes are deployed or existing ones rea...
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ISBN:
(纸本)9781467310710
In distributed sensor networks, the posterior Cramer-Rao lower bound (PCRLB) has recently been used [1] as a selection criteria for sensor management decisions, where new sensor nodes are deployed or existing ones reactivated to optimize the network's performance. Previous algorithms to compute the PCRLB are derived for the centralized [2] and hierarchical architectures [3] using a fusion centre that makes them inappropriate for distributed sensor management. Only recently a suboptimal expression [1] for the distributed architecture has been proposed, which can at times lead to large errors especially in systems with highly non-linear dynamics. the paper derives the optimal PCRLB for the distributed architecture. In other words, we derive a recursive procedure to determine the overall Fisher information matrix (FIM), i.e., the inverse of the PCRLB, from local FIMs of the distributed estimators. the proposed distributed PCRLB is independent of the filtering mechanism used and closely follows its centralized counterpart.
We study the problem of sensor fusion in a simplified radar surveillance application. A potentially large number of narrowband radars with isotropic antennas monitor a two-dimensional area for an unknown number of tar...
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ISBN:
(纸本)9781467310710
We study the problem of sensor fusion in a simplified radar surveillance application. A potentially large number of narrowband radars with isotropic antennas monitor a two-dimensional area for an unknown number of targets. We use techniques from compressive sensing to distribute efficient projections of network observations, allowing for reconstruction of the target scene using a single snapshot of sensor data. We avoid the use of a fusion node, allowing all radars to individually estimate target locations after iterative communication with neighboring sensors. We study the robustness of the discretization of continuous target locations, comparing estimation performance of basis pursuit reconstruction methods to a sparse estimator based on a model-robust formulation. We test the approach on simulated scenarios, showing tradeoffs in the resolution of target localization as well as the communication bandwidths required for this inter-radar cooperation scheme.
Performing surgery on the beating heart has significant advantages for the patient compared to traditional heart surgery on the stopped heart. A remote-controlled robot can be used to automatically cancel out the move...
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ISBN:
(纸本)9781479914814
Performing surgery on the beating heart has significant advantages for the patient compared to traditional heart surgery on the stopped heart. A remote-controlled robot can be used to automatically cancel out the movement of the beating heart. this necessitates precise tracking of the heart surface. For this purpose, we track 24 identical artificial markers placed on the heart. this creates a data association problem, because it is not known which measurement was obtained from which marker. To solve this problem, we apply a multiple target tracking method based on a symmetric kernel transformation. this method allows efficient handling of the data association problem even for a reasonably large number of targets. We demonstrate how to implement this method efficiently. the proposed approach is evaluated on in-vivo data of a real beating heart surgery performed on a porcine beating heart.
Self localization of nodes in wireless sensor networks (WSN) attracts wide interest in the past few years. the main challenge is to adopt calibration algorithms to the low-power/low-bandwidth/low-cost constrains on ea...
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ISBN:
(纸本)9781479914814
Self localization of nodes in wireless sensor networks (WSN) attracts wide interest in the past few years. the main challenge is to adopt calibration algorithms to the low-power/low-bandwidth/low-cost constrains on each sensor in the network. In this paper we present a novel approach, in which position-known anchors transmit special calibration signals simultaneously. Each node measures only the received signal strength (RSSI), i.e. envelope of the sum of received signals, and estimates time difference of arrivals (TDOA) of the signals. Two or more TDOA measurements allow the node to estimate its own position in the WSN. Based on an analysis of the appropriate Cramer Rao Lower Bound (CRLB) on the TDOA estimates, we suggest the choice of calibrating signals which provide optimal performance. the theoretical results are supported by simulations of the Maximum Likelihood (ML) estimators and numerical evaluation of the CRLB for a specific scenario of interest.
this paper critically examines the potential performance benefits offered by motion of sparse arrays for direction-of-arrival (DOA) estimation. the motivation behind utilizing array motion is to increase the number of...
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ISBN:
(纸本)9781728119465
this paper critically examines the potential performance benefits offered by motion of sparse arrays for direction-of-arrival (DOA) estimation. the motivation behind utilizing array motion is to increase the number of consecutive difference lags. However, creating a synthetic array also requires more temporal measurements compared to the static (non-synthetic) array. For the first time, we rigorously analyze the trade-off between the required number of temporal samples and the length of the difference co-array to understand when synthetic arrays offer distinct advantages. As a concrete result, we show that if the ratio of the number of consecutive lags of the difference coarray of sparse arrays with and without motion is above a universal threshold, the synthetic array outperforms its non-synthetic counterpart and has a smaller estimation error. Our claims are demonstrated boththeoretically and through numerical experiments(1).
To reduce the consumption of spectrum and hardware resource, two methods are proposed to design the integrated waveform that can satisfy the requirements for both radar and communication. First, a linear superposition...
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ISBN:
(纸本)9781728119465
To reduce the consumption of spectrum and hardware resource, two methods are proposed to design the integrated waveform that can satisfy the requirements for both radar and communication. First, a linear superposition (LS) method is proposed to design the transmit waveforms of a uniform linear array (ULA). In the far field of the ULA, the designed transmit waveforms can simultaneously synthesize the desired radar and communication waveforms in different directions. However, the designed waveforms usually have high peak-to-average power ratio (PAPR). then, an alternative projection (AP) method is proposed to reduce the PAPR of the transmit waveforms. the AP method can devise the waveforms with constant modulus. Boththe proposed methods can perform radar and communication function in different directions. Finally, several simulation results are given to verify the effectiveness of the proposed methods.
Many threats in the form of human actions (terrorist attacks, military actions, etc.) can be stochastically modeled by someone with relevant expert knowledge. In this work, a threat is taken to be a sequence of action...
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ISBN:
(纸本)9781538647523
Many threats in the form of human actions (terrorist attacks, military actions, etc.) can be stochastically modeled by someone with relevant expert knowledge. In this work, a threat is taken to be a sequence of actions that evolve over time and culminate at some ultimate goal. A model would be a hypothesis as to how a threat would develop, and what kind of observable evidence it would produce along the way. this modeling method allows us to attempt detection using the preliminary evidence of a threat. this would theoretically allow the user to take preemptive action;i.e. the user can interfere withthe threat before its culmination. this work presents a method of stochastically modeling these types of processes using Hidden Markov Models (HMMs). We then present a detection scheme based on random finite set (RFS) filters (Bernoulli filters) that allows for detection of multiple threat processes using a single cluttered stream of observed data.
this paper address the problem of direction-of-arrival (DOA) estimation of quasi-stationary signals based on uniform linear array with malfunctioning sensors. By utilizing the subspace structures of the local second-o...
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ISBN:
(数字)9781728119465
ISBN:
(纸本)9781728119465
this paper address the problem of direction-of-arrival (DOA) estimation of quasi-stationary signals based on uniform linear array with malfunctioning sensors. By utilizing the subspace structures of the local second-order statistics of quasi-stationary signals, a Khatri-Rao subspace approach is developed. Our scheme first collects the local covariance matrices of the source signals and then transfers them into a new virtual linear array which can identify at least twice as much DOAs as to the original physical one. It is also shown that the coprime configuration is a special case of the proposed model therefore the same techniques can be applied directly. Simulations are also carried out for the comparison of the proposed algorithm and state-of-the-art approaches.
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