
- Read more about Coherent long-time integration and Bayesian detection with Bernoulli track-before-detect
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We consider the problem of detecting small and manoeuvring objects with staring array radars. Coherent processing and long-time integration are key to addressing the undesirably low signal-to-noise/background conditions in this scenario and are complicated by the object manoeuvres. We propose a Bayesian solution that builds upon a Bernoulli state space model equipped with the likelihood of the radar data cubes through the radar ambiguity function. Likelihood evaluation in this model corresponds to coherent long-time integration.
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- Read more about Variational Message Passing-based Respiratory Motion Estimation and Detection Using Radar Signals
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We present a variational message passing (VMP)-based approach to detect the presence of a person based on their respiratory chest motion using multistatic ultra-wideband (UWB) radar. In the process, the respiratory motion is estimated for contact-free vital sign monitoring. The received signal is modeled as a backscatter channel and the respiratory motion and propagation channels are estimated using VMP. We use the evidence lower bound (ELBO) to approximate the model evidence for the detection.
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- Read more about EUSIPCO 2020 Tutorial: Four Decades of Array Signal Processing Research: An Optimization Relaxation Technique Perspective
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In our community, we currently witness that sensor array processing, more specifically direction-of- arrival (DoA) estimation, receives new momentum due to the emergence of new applications such as automotive radar, drone localization, parametric channel estimation in Massive MIMO. This development is further inspired by the emergence of new powerful and affordable multiantenna hardware platforms.
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- Read more about IEEE SAM 2022 Tutorial: Four Decades of Array Signal Processing Research: An Optimization Relaxation Technique Perspective
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In our community, we currently witness that sensor array processing, more specifically direction-of-arrival (DoA) estimation, receives new momentum due to the emergence of new applications such as automotive radar, drone localization, parametric channel estimation in Massive MIMO. This development is further inspired by the emergence of new powerful and affordable multiantenna hardware platforms.
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- Read more about Acquisition of Asynchronous Data and Parameter Estimation based on Double-Cross- Correlation Processor with Phase Transform (Demo at WASPAA 2021)
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Coherent processing of signals captured by a wireless acoustic sensor network (WASN) requires an estimation of such parameters as the sampling-rate and sampling-time offset (SRO and STO). The acquired asynchronous signals of such WASN exhibit an accumulating time drift (ATD) linearly growing with time and dependent on SRO and STO values. In our demonstration, we present a real WASN based on Respberry-Pi computers, where SRO and ATD values are estimated by using a double-cross-correlation processor with phase transfrom (DXCP-PhaT) recently proposed.
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- Read more about CRAMÉR-RAO BOUND AND ANTENNA SELECTION OPTIMIZATION FOR DUAL RADAR-COMMUNICATION DESIGN
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- Read more about A NEW COPRIME-ARRAY-BASED CONFIGURATION WITH AUGMENTED DEGREES OF FREEDOM AND REDUCED MUTUAL COUPLING
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In this paper, a new type of coprime-array-based structure, named AtCADiS, is proposed to achieve increased degrees of freedom (DoFs) and reduced mutual coupling. The closed-form expressions for the sensor positions and the number of uniform DoFs (uDoFs) of AtCADiS are provided. Specifically, AtCADiS is constructed via two steps. First, we shift the leftmost sensor of tCADiS to the right by N.
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- Read more about Semidefinite Relaxation Method for Moving Object Localization Using A Stationary Transmitter at Unknown Position
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- Read more about Conjugate Augmented Spatial-Temporal Near-Field Sources Localization with Cross Array
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- Read more about TCLA Array: A New Sparse Array Design with Less Mutual Coupling
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