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A ubiquitous and high-performance sensing service is required in the next generation of wireless communication systems.

For applications that require fast evaluations of an antenna’s beampattern, we propose a computationally efficient interpolation technique based on cubic B-Splines.

Peak detection is a fundamental task in radar and has therefore been studied extensively in radar literature.

Switched phased array systems operating at high sample rates generate large amounts of data during measurements of radio channels, but many scenarios contain only few multipath components.

Integrated sensing and communication (ISAC) systems have been investigated by the research and standardization communities in the recent past.

In this work, we investigate the localization of targets in the presence of multiple scattering.

In this work, we investigate the localization of point-like targets in the presence of multiple scattering.

The analysis of wireless communication channels at the mmWave, sub-THz and THz bands gives rise to difficulties in the construction of antenna arrays due to the small maximum inter-element spacing constraints at these frequencies.

Harmonic retrieval techniques are the foundation of radio channel sounding, estimation and modeling.

In this publication, we analyze how the performance of propagation parameter estimation for THz channel sounding can be improved by the power spectrum design of a multicarrier waveform.

The recent advances in Integrated Sensing and Communications (ICAS) essentially transform mobile radio networks into a diverse , dynamic and heterogeneous sensing network.

Estimating the Time Difference of Arrival (TDoA), is a simple yet reliable technique to accurately perform an indoor monostatic localization.

We present our new scalable multi-channel and multi-node sounder , the ILMSound G3.

To efficiently extract estimates about the propagation behavior of electromagnetic waves in a radio environment it is common to invoke the narrowband-assumption.

Multidimensional channel sounding measures the geometrical structure of mobile radio propagation.

This publication proposes a parametric data model and a gradient-based maximum likelihood estimator suitable for the description of delay-dispersive responses of multiple dynamic ultrawideband (UWB)-radar targets.

A framework is proposed for developing and evaluating algorithms for extracting multipath propagation components (MPCs) from measurements collected by channel sounders at millimeter-wave frequencies.

Harmonic retrieval is essential in radio channel sounding, estimation, and modeling.

In the present paper we introduce the empirical results of measurements with an over-the-air based propagation artifact for verification and validation of sub-THz and THz channel sounders and parameter estimation algorithms.

Scientific computing requires handling large linear models, which are often composed of structured matrices.

We present a maximum-likelihood estimation algorithm for radio channel measurements exhibiting a mixture of independent Dense Multipath Components.

Along with the ever increasing number of sensors, which are also generating rapidly growing amounts of data, the traditional paradigm of sampling adhering the Nyquist criterion is facing an equally increasing number of obstacles.

The procedure of estimating the angular dependent delay of an Ultra Wideband (UWB) antenna, directly in frequency domain, is presented.

We propose a compact hardware architecture for measuring sparse channel impulse responses (IR) by extending the M-Sequence ultra-wideband (UWB) measurement principle with the concept of compressed sensing.

In ultrasound nondestructive testing (NDT), a widespread approach is to take synthetic aperture measurements from the surface of a specimen to detect and locate defects within it.

Ultrasound Computed Tomography (UCT) is challenging due to phenomena such as strong refraction, multiple scattering, and mode conversion.

Understanding and analysis of antennas is crucial for the development of modern telecommunication technologies, like 5G or massive MIMO.

The localization of defects is a prevalent task in ultrasound nondestructive testing.

In this paper, we present a compressed sensing model for 2D Full Matrix Capture data from a uniform linear array.

In order to obtain good reconstruction guarantees for typical compressive sensing scenarios, we translate the search for good compression matrices into a ball packing problem in a suitable projective space.

There are disclosed techniques (e.g., apparatus, methods) for estimating an Impulse response (30) of a linear System (4).

In this paper, we propose a compressed sensing scheme for volumetric synthetic aperture measurements in ultrasonic nondestructive testing.

Recently, compressive antenna arrays have been considered for direction of arrival (DoA) estimation with reduced hardware complexity.

This paper is concerned with estimating unknown multidimensional frequencies from linear compressive measurements.

Usually, a large number of patterns are needed in the computational ghost imaging (CGI).

In this paper, the problem of estimating the unknown degree of sparsity from compressive measurements without the need to carry out a sparse recovery step is investigated.

We study the problem of direction of arrival estimation for arbitrary antenna arrays.

In this paper, we propose a matrix-free 3D ultrasonic reconstruction scheme based on the Fast Iterative Shrinkage-Thresholding algorithm (FISTA) implemented on a GPU.

In this paper, we propose an efficient matrix-free algorithm to reconstruct locations and size of flaws in a specimen from volumetric ultrasound data by means of a native 3D Sparse Signal Recovery scheme using Orthogonal Matching Pursuit (OMP).

In this paper we investigate the application of Compressed Sensing (CS) to MIMO channel sounding in the spatial domain.