Browsing by Author "Roemer, Florian"

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An adaptively focusing measurement design for compressed sensing based doa estimation
(IEEE, 2015) Ibrahim, Mohamed; Roemer, Florian; Del Galdo, Giovanni
In this paper we propose an adaptive design strategy for the measurement matrix for applying Compressed Sensing (CS) to Direction Of Arrival (DOA) estimation with antenna arrays. Instead of choosing the coefficients of the compression matrix randomly, we propose a systematic design methodology for constructing a measurement matrix that focuses the array towards a specific area of interest and thereby achieves a superior DOA estimation performance. The focusing is performed in a sequential manner, i.e., we start with a uniform measurement design from which regions of interest can be extracted that the subsequent measurements then focus on. By continuously updating these target regions, gradual movement of the sources can also be tracked over time. Numerical results demonstrate that the focused measurements possess a superior SNR leading to significantly enhanced DOA estimates.
Measurement matrix design for compressed sensing based time delay estimation
(IEEE, 2016) Roemer, Florian; Ibrahim, Mohamed; Franke, Norbert; Hadaschik, Niels; Eidloth, Andreas; Sackenreuter, Benjamin; Del Galdo, Giovanni
In this paper we study the problem of estimating the unknown delay(s) in a system where we receive a linear combination of several delayed copies of a known transmitted waveform. This problem arises in many applications such as timing-based localization or wireless synchronization. Since accurate delay estimation requires wideband signals, traditional systems need high-speed AD converters which poses a significant burden on the hardware implementation. Compressive sensing (CS) based system architectures that take measurements at rates significantly below the Nyquist rate and yet achieve accurate delay estimation have been proposed with the goal to alleviate the hardware complexity. In this paper, we particularly discuss the design of the measurement kernels based on a frequency-domain representation and show numerically that an optimized choice can outperform randomly chosen functionals in terms of the delay estimation accuracy.
On the design of the measurement matrix for compressed sensing based DOA estimation
(IEEE, 2015) Ibrahim, Mohamed; Roemer, Florian; Del Galdo, Giovanni
In this paper we investigate the design of the measurement matrix for applying Compressed Sensing (CS) to the problem of Direction Of Arrival (DOA) estimation with antenna arrays. So far, it has been suggested to choose the coefficients randomly since this choice satisfies the restricted isometry property (RIP) with a high probability. We demonstrate that this choice may be sub-optimal since it can result in an effective array with significant sidelobes and blind spots. The sidelobes are especially problematic when we use correlation-based greedy algorithms for the sparse recovery stage as they can lead to detecting spurious peaks. To address the problem, we introduce a design methodology for constructing a measurement matrix that mitigates these unwanted effects to achieve a better DOA estimation performance. Numerical results demonstrate the usefulness of our design.
Polarimetric compressive sensing based DOA estimation
(VDE, 2014) Roemer, Florian; Ibrahim, Mohamed; Alieiev, Roman; Landmann, Markus; S. Thomae, Reiner; Del Galdo, Giovanni
In this paper, we discuss direction of arrival (DOA) estimation based on the full polarimetric array manifold using a Compressive Sensing (CS)-based formulation. We first show that the existing non-polarimetric CS-based description of the DOA estimation problem can be extended to the polarimetric setting, giving rise to an amplitude vector that possesses a structured sparsity. We explain how DOAs can be estimated from this vector for incoming waves of arbitrary polarization. We then discuss the “gridding” problem, i.e., the effect of DOAs that are not on the sampling grid which was chosen for the discretization of the array manifold. We propose an estimator of these grid offsets which extends earlier work to the polarimetric setting. Numerical results demonstrate that the proposed scheme can achieve a DOA estimation accuracy close to the Cramér-Rao Bound for arbitrarily polarized waves.
Temporal wireless synchronization with compressed opportunistic signals
(IEEE, 2016) Ibrahim, Mohamed; Roemer, Florian; Hadaschik, Niels; Tröger, Hans-Martin; Sackenreuter, Benjamin; Franke, Norbert; Robert, Joerg; Del Galdo, Giovanni
In this paper we introduce a wireless temporal synchronization scheme based on wideband signals of opportunity (SOO) such as DVB-T or LTE signals. Since these signals may not be decodable we show that it is necessary that one (reference) node broadcasts an excerpt of the SOO to all other nodes to provide a reference. However, the transmission of this reference signals requires a high bandwidth. Therefore, we propose to replace this transmission with a lower-bandwidth “compressed” version of this reference signal, using ideas from the field of compressed sensing (CS). We show that the high time resolution of the original wideband SOO can be maintained so that accurate temporal synchronization is possible. On the other hand, the compression leads to higher sidelobes in the correlation function which reduces the effective SNR. Therefore, the compression rate allows to control the trade-off between the required bandwidth and the SNR.