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The recently developed Matched Phase Reassignment (MPR) gives a time-frequency local measure of phase difference between short oscillatory transient signals. However, the resulting phase estimate is not satisfactory as it has poor resolution for high oscillatory frequencies. The MPR is also sensitive to high noise levels and is computationally cumbersome. In this paper, a novel reassignment method
Recent advances in simultaneous estimation of both receiver and sender positions in ad-hoc sensor networks have made it possible to automatically calibrate node positions - a prerequisite for many applications. In man-made environments there are often large planar reflective surfaces that give significant reverberations. In this paper, we study geometric problems of receiver-sender node calibratio
This paper presents the Reassignment Vector Phase Difference Estimator (RVPDE), which gives noise robust relative phase estimates of oscillating transient signals in high noise levels. Estimation of relative phase information between signals is of interest for direction of arrival estimation, source separation and spatio-temporal decoding in neurology as well as for soundscape analysis. The RVPDE
An important issue in simultaneous localisation and mapping is how to match and merge individual local maps into one global map. This is addressed within the field of robotics and is crucial for multi-robot SLAM. There are a number of different ways to solve this task depending on the representation of the map. To take advantage of matching and merging methods that allow for deformations of the lo
Dickcissel (Spiza americana) males occupying territories in cropland sites produced songs that were less similar on average to other Dickcissel songs in their neighborhood than did Dickcissels living in grasslands, where conformity to the local vocal culture was higher. Further, Dickcissel vocal culture changed more quickly over time in cropland sites relative to grassland sites. These differences
Collaborative robots have been designed to perform tasks where human cooperation may occur. Additionally, undesired collisions can happen in the robot’s environment. A contact classifier may be needed if robot trajectory recalculation is to be activated depending on the source of robot–environment contact. For this reason, we have evaluated a fast contact detection and classification method and we
Kinesthetic teaching allows human operators to reprogram part of a robot’s trajectory by manually guiding the robot. To allow kinesthetic teaching, and also to avoid any harm to both the robot and its environment, Cartesian impedance control is here used for trajectory following. In this paper, we present an online method to modify the compliant behavior of a robot toward its environment, so that
This paper discusses challenges, experiences and lessons learned so far while transforming a masonry build system based mostly on manual labour into a robot automated build system. Our motivation for selection of this masonry process is to try out how robot automation could impact the architects in their design work by providing a tool to directly manipulate wall expression down to individual bric
This work is concerned with determining optimal sensor placements that allow for an accurate location estimate of structured signal sources, taking into account the expected location areas and the typical range of the parameters detailing the signals. In the presentation, we illustrate the technique for tonal sound signals, exploiting the expected harmonic structure of such signals. To determine p
Time-domain spectroscopy encompasses a wide range of techniques, such as Fourier-transform infrared, pump-probe, Fourier-transform Raman, and two-dimensional electronic spectroscopies. These methods enable various applications, such as molecule characterization, excited state dynamics studies, or spectral classification. Typically, these techniques rarely use sampling schemes that exploit the prio
Recently, many forms of audio industrial applications, such as sound monitoring and source localization, have begun exploiting smart multi-modal devices equipped with a microphone array. Regrettably, model-based methods are often difficult to employ for such devices due to their high computational complexity, as well as the difficulty of appropriately selecting the user-determined parameters. As a
In this work, we introduce a novel approach for designing the transmit frequency offset scheme based on Cramér-Rao lower bound (CRLB) minimization for a frequency diverse array multiple-input multiple-output (FDA-MIMO) radar. The problem originates in non-uniform FDA radar where each frequency offset scheme derives from a specific mathematical model, but where no optimization is conducted with res
This paper addresses the weak signal detection problem in a massive colocated multiple-input multiple-output (MIMO) radar. To cope with the sheer amount of data produced by the large-scale antennas, a low-bit quantizer is introduced in the sampling process to enable both for hardware limitations and a high detection performance. The generalized likelihood ratio test (GLRT) detector is proposed for
One of the classical multi-view geometry problems is the so called P3P problem, where the absolute pose of a calibrated camera is determined from three 2D-to-3D correspondences. Since these solvers form a critical component of many vision systems (e.g. in localization and Structure-from-Motion), there have been significant effort in developing faster and more stable algorithms. While the current s
Industry 4.0, with its focus on flexibility and customizability, is pushing in the direction of wireless communication in future smart factories, in particular, massive multiple-input-multiple-output (MIMO) and its future evolution of large intelligent surfaces (LIS), which provide more reliable channel quality than previous technologies. At the same time, network slicing in 5G and beyond systems
Acoustic impulse responses (IRs) are widely used to model sound propagation between two points in space. Being a point-to-point description, IRs are generally estimated based on input-output pairs for source and sensor positions of interest. Alternatively, the IR at an arbitrary location in space may be constructed based on interpolation techniques, thus alleviating the need of densely sampling th
The authors propose a computationally efficient approach to estimate the directions of arrival of far-field sources impinging on a sensor array. The proposed estimator is formed using a sparse reconstruction framework, employing a novel adaptive grid selection technique to reduce the dimensionality of the used dictionary matrix. The method further makes use of a SPICE-inspired dictionary to adapti
Industry 4.0, with its focus on flexibility and customizability, is pushing in the direction of wireless communication in future smart factories, in particular massive multiple-input multiple-output (MIMO), and its future evolution Large Intelligent Surfaces (LIS), which provide more reliable channel quality than previous technologies. As such, there arises the need to perform efficient scheduling
In this paper, we considered the real-time modeling of an underwater channel impulse response (CIR), exploiting the inherent structure and sparsity of such channels. Building on the recent development in the modeling of acoustic channels using a Kronecker structure, we approximated the CIR using a structured and sparse model, allowing for a computationally efficient sparse block-updating algorithm
The identification of nonlinear chirp signals has attracted notable attention in the recent literature, including estimators such as the variational mode decomposition and the nonlinear chirp mode estimator. However, most presented methods fail to process signals with close frequency intervals or depend on user-determined parameters that are often non-trivial to select optimally. In this work, we
