Autoencoder-based learning of transmission parameters in fast pulse-echo ultrasound imaging employing sparse recovery. - In: IEEE Xplore digital library, ISSN 2473-2001, (2023), S. 516-520
There is recently a notable rise in the exploration of pulse-echo ultrasound image reconstruction techniques that address the inverse problem employing sparse signal and rely on a single measurement cycle. Nevertheless, these techniques continue to pose significant challenges with regard to accuracy of estimations. Previous studies have endeavored to decrease the correlation between received samples in each transducer array in order to enhance accuracy of sparsely approximated solutions to inverse problems. In this paper, our objective is to learn the transmission parameters within a parametric measurement matrix by employing an autoencoder, which encodes sparse spatial data with a parametric measurement matrix and subsequently decodes it using Fast Iterative Shrinkage-Thresholding Algorithm (FISTA). Outcomes exhibit superior performance in comparison to both state-of-art random selection of the parameters and conventional plane wave imaging (PWI) scenarios in terms of reconstruction accuracy.
https://doi.org/10.1109/CAMSAP58249.2023.10403443
Data-driven subsampling matrices design for phased array ultrasound nondestructive testing. - In: IEEE IUS 2023, International Ultrasonics Symposium, Palais des congrès de Montréal, September 3-8, 2023, (2023), insges. 4 S.
By subsampling optimally in the spatial and temporal domains, ultrasound imaging can achieve high performance, while also accelerating data acquisition and reducing storage requirements. We study the design of experiment problem that attempts to find an optimal choice of the subsampling patterns, leading to a non-convex combinatorial optimization problem. Recently, deep learning was shown to provide a feasible approach for solving such problems efficiently by virtue of the softmax function as a differentiable approximation of the one-hot encoded subsampling vectors. We incorporate softmax neural networks into information theory-based and task-based algorithms, respectively, to design optimal subsampling matrices in Full Matrix Capture (FMC) measurements predicated on compressed sensing theory.
https://doi.org/10.1109/IUS51837.2023.10308257
Deep learning-based optimal spatial subsampling in ultrasound nondestructive testing. - In: 31st European Signal Processing Conference (EUSIPCO 2024), (2023), S. 1863-1867
Traditional ultrasound synthetic aperture imaging relies on closely spaced measurement positions, where the pitch size is smaller than half the ultrasound wavelength. While this approach achieves high-quality images, it necessitates the storage of large data sets and an extended measurement time. To address these issues, there is a burgeoning interest in exploring effective subsampling techniques. Recently, Deep Probabilistic Subsampling (DPS) has emerged as a feasible approach for designing selection matrices for multi-channel systems. In this paper, we address spatial subsampling in single-channel ultrasound imaging for Nondestructive Testing (NDT) applications. To accomplish a model-based data-driven spatial subsampling approach within the DPS framework that allows for the optimal selection of sensing positions on a discretized grid, it is crucial to build an adequate signal model and design an adapted network architecture with a reasonable cost function. The reconstructed image quality is then evaluated through simulations, showing that the presented subsampling pattern approaches the performance of fully sampling and substantially outperforms uniformly spatial subsampling in terms of signal recovery quality.
https://doi.org/10.23919/EUSIPCO58844.2023.10289868
Optimization of transmission parameters in fast pulse-echo ultrasound imaging using sparse recovery. - In: 31st European Signal Processing Conference (EUSIPCO 2024), (2023), S. 441-445
In pulse-echo ultrasound imaging, the goal is to achieve a certain image quality while minimizing the duration of the signal acquisition. In the past, fast ultrasound imaging methods applying sparse signal recovery have been implemented by accepting a single pulse-echo measurement. However, they have experienced a certain amount of reconstruction error. In sparse signal recovery, reducing the correlation between the samples of the measurements observed by the different receivers is beneficial for lowering the reconstruction error. Exploiting the Born approximation and Green's function for the wave equation, the analytical inverse scattering problem can be defined in matrix-vector form. Adopting this setting, it has been suggested in the past to reduce the correlation between the samples of the measurement using Cylindrical Waves (CWs) with randomly selected delays and weights. In a similar setting, we created an optimization problem accepting transmission delays and weights as variables to minimize the correlation between the samples of the measurement in each receiver. We demonstrate via simulations that CWs employing the optimized transmission parameters outperformed the cases with Plane Wave Imaging (PWI) and CWs with random transmission parameters in terms of reconstruction accuracy.
https://doi.org/10.23919/EUSIPCO58844.2023.10290105
Monitoring of joint gap formation in laser beam butt welding using neural network-based acoustic emission analysis. - In: Crystals, ISSN 2073-4352, Bd. 13 (2023), 10, 1451, S. 1-14
This study aimed to explore the feasibility of using airborne acoustic emission in laser beam butt welding for the development of an automated classification system based on neural networks. The focus was on monitoring the formation of joint gaps during the welding process. To simulate various sizes of butt joint gaps, controlled welding experiments were conducted, and the emitted acoustic signals were captured using audible-to-ultrasonic microphones. To implement an automated monitoring system, a method based on short-time Fourier transformation was developed to extract audio features, and a convolutional neural network architecture with data augmentation was utilized. The results demonstrated that this non-destructive and non-invasive approach was highly effective in detecting joint gap formations, achieving an accuracy of 98%. Furthermore, the system exhibited promising potential for the low-latency monitoring of the welding process. The classification accuracy for various gap sizes reached up to 90%, providing valuable insights for characterizing and categorizing joint gaps accurately. Additionally, increasing the quantity of training data with quality annotations could potentially improve the classifier model’s performance further. This suggests that there is room for future enhancements in the study.
https://doi.org/10.3390/cryst13101451
Compressed Sensing: from big data to relevant data. - In: Handbook of Nondestructive Evaluation 4.0, (2022), S. 329-352
Though the ever-increasing availability of digital data in the context of NDE 4.0 is mostly considered a blessing, it can turn to a curse quite rapidly: managing large amounts of data puts a burden on the sensor devices in terms of sampling and transmission, the networks, as well as the server infrastructure in terms of storing, maintaining, and accessing the data. Yet, NDE data can be highly redundant so the storage of massive amounts of data may indeed be wasteful. This is the main reason why focusing on relevant data as early as possible in the NDE process is highly advocated in the context of NDE 4.0. This chapter introduces Compressed Sensing as a potential approach to put this vision to practice. Compressed Sensing theory has shown that sampling signals with sampling rates that are significantly below the Shannon-Nyquist rate is possible without loss of information, provided that prior knowledge about the signals to be acquired is available. In fact, we may sample as low as the actual information rate if our prior knowledge is sufficiently accurate. In the NDE 4.0 context, prior knowledge can stem from the known inspection task and geometry but it can also include previous recordings of the same piece (such as in Structural Health Monitoring), information stored in the digital product memory along the products’ life cycle, or predictions generated through the products’ digital twins. In addition to data reduction, reconstruction algorithms developed in the Compressed Sensing community can be applied for enhanced processing of NDE data, providing added value in terms of accuracy or reliability. The chapter introduces Compressed Sensing basics and gives some concrete examples of its application in the NDE 4.0 context, in particular for ultrasound.
Deep learning aided interpolation of spatio-temporal nonstationary data. - In: 30th European Signal Processing Conference (EUSIPCO 2022), (2022), S. 2221-2225
Despite the growing interest in many fields, spatio-temporal (ST) interpolation remains challenging. Given ST nonstationary data distributed sparsely and irregularly over space, our objective is to obtain an equidistant representation of the region of interest (ROI). For this reason, an equidistant grid is defined within the ROI, where the available time series data are arranged, and the time series of the unobserved points are interpolated. Aiming to maintain the interpretability of the whole process while offering flexibility and fast execution, this work presents a ST interpolation frame-work which combines a statistical technique with deep learning. Our framework is generic and not confined to a specific application, which also provides the prediction confidence. To evaluate its validity, this framework is applied to ultrasound nondestructive testing (UT) data as an example. After the training with synthetic UT data sets, our framework is shown to yield accurate predictions when applied to measured UT data.
https://ieeexplore.ieee.org/document/9909600
Preprocessing of freehand ultrasound synthetic aperture measurements using DNN. - In: 29th European Signal Processing Conference (EUSIPCO 2021), (2021), S. 1401-1405
Manual ultrasonic inspection is a widely used Nondestructive Testing (NDT) technique due to its simplicity and compatibility with complex structures. However, in contrast to the data acquired using a robotic positioner, manual measurements suffer from perturbations caused by a variable coupling and a varying scanning density. Imaging techniques like the synthetic aperture focusing technique rely on an unperturbed dense measurement from an equidistant measurement grid. Consequently, imaging based on freehand measurements leads to artifacts. This work aims at reducing such artifacts by preprocessing the manual measurements using Deep Neural Networks (DNN). The training of a DNN requires a large set of labeled measurements which is difficult to obtain in NDT. In this work, we present a technique to train the DNN using only synthetic data. We show that the resulting DNN generalizes well on real measurements. We present an improvement in Generalized Contrast to Noise Ratio by a factor of 20 and 3 compared to omitting the preprocessing for synthetic and measurement data, respectively.
https://doi.org/10.23919/EUSIPCO54536.2021.9616155
Compressed ultrasound computed tomography in NDT. - In: IEEE IUS 2021, (2021), insges. 4 S.
Ultrasound Computed Tomography (UCT) is challenging due to phenomena such as strong refraction, multiple scattering, and mode conversion. In NDT, large speed of sound contrasts lead to strong artifacts if such phenomena are not modeled correctly; however, enhanced models are computationally expensive. In this work, a two-step framework for Compressed UCT based on the integral approach to the solution of the Helmholtz equation is presented. It comprises a physically motivated forward step and an imaging step that solves a suitable inverse problem. Multiple scattering is accounted for through the use of Neumann series. Convergence problems of Neumann series in high contrast settings are addressed via Padé approximants. Compressed sensing is employed to reduce the computational complexity of the reconstruction procedure by reducing data volumes directly at the measurement step, avoiding redundancy in the data and allowing the ability to steer the admissible computational effort at the expense of reconstruction quality. The proposed method is shown to yield high quality reconstructions under heavy subsampling in the frequency and spatial domains.
https://doi.org/10.1109/IUS52206.2021.9593329
Frequency subsampling of ultrasound nondestructive measurements: acquisition, reconstruction, and performance. - In: IEEE transactions on ultrasonics, ferroelectrics, and frequency control, ISSN 1525-8955, Bd. 68 (2021), 10, S. 3174-3191
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. Based on these measurements, imaging is usually performed using the synthetic aperture focusing technique (SAFT). However, SAFT is suboptimal in terms of resolution and requires oversampling in the time domain to obtain a fine grid for the delay-and-sum (DAS). On the other hand, parametric reconstruction algorithms give better resolution, but their usage for imaging becomes computationally expensive due to the size of the parameter space and a large amount of measurement data in realistic 3-D scenarios when using oversampling. In the literature, the remedies to this are twofold. First, the amount of measurement data can be reduced using state-of-the-art sub-Nyquist sampling approaches to measure Fourier coefficients instead of time-domain samples. Second, parametric reconstruction algorithms mostly rely on matrix-vector operations that can be implemented efficiently by exploiting the underlying structure of the model. In this article, we propose and compare different strategies to choose the Fourier coefficients to be measured. Their asymptotic performance is compared by numerically evaluating the Cramér-Rao bound (CRB) for the localizability of the defect coordinates. These subsampling strategies are then combined with an l1-minimization scheme to compute 3-D reconstructions from the low-rate measurements. Compared to conventional DAS, this allows us to formulate a fully physically motivated forward model matrix. To enable this, the projection operations of the forward model matrix are implemented matrix-free by exploiting the underlying two-level Toeplitz structure. Finally, we show that high-resolution reconstructions from as low as a single Fourier coefficient per A-scan are possible based on simulated data and measurements from a steel specimen.
https://doi.org/10.1109/TUFFC.2021.3085007
Locally optimal subsampling strategies for full matrix capture measurements in pipe inspection. - In: Applied Sciences, ISSN 2076-3417, Bd. 11 (2021), 9, 4291, S. 1-14
In ultrasonic non-destructive testing, array and matrix transducers are being employed for applications that require in-field steerability or which benefit from a higher number of insonification angles. Having many transmit channels, on the other hand, increases the measurement time and renders the use of array transducers unfeasible for many applications. In the literature, methods for reducing the number of required channels compared to the full matrix capture scheme have been proposed. Conventionally, these are based on choosing the aperture that is as wide as possible. In this publication, we investigate a scenario from the field of pipe inspection, where cracks have to be detected in specific areas near the weld. Consequently, the width of the aperture has to be chosen according to the region of interest at hand. On the basis of ray-tracing simulations which incorporate a model of the transducer directivity and beam spread at the interface, we derive application specific measures of the energy distribution over the array configuration for given regions of interest. These are used to determine feasible subsampling schemes. For the given scenario, the validity/quality of the derived subsampling schemes are compared on the basis of reconstructions using the conventional total focusing method as well as sparsity driven-reconstructions using the Fast Iterative Shrinkage-Thresholding Algorithm. The results can be used to effectively improve the measurement time for the given application without notable loss in defect detectability.
https://doi.org/10.3390/app11094291
Subsampling approaches for compressed sensing with ultrasound arrays in non-destructive testing. - In: Sensors, ISSN 1424-8220, Bd. 20 (2020), 23, 6734, insges. 23 S.
Full Matrix Capture is a multi-channel data acquisition method which enables flexible, high resolution imaging using ultrasound arrays. However, the measurement time and data volume are increased considerably. Both of these costs can be circumvented via compressed sensing, which exploits prior knowledge of the underlying model and its sparsity to reduce the amount of data needed to produce a high resolution image. In order to design compression matrices that are physically realizable without sophisticated hardware constraints, structured subsampling patterns are designed and evaluated in this work. The design is based on the analysis of the Cramér–Rao Bound of a single scatterer in a homogeneous, isotropic medium. A numerical comparison of the point spread functions obtained with different compression matrices and the Fast Iterative Shrinkage/Thresholding Algorithm shows that the best performance is achieved when each transmit event can use a different subset of receiving elements and each receiving element uses a different section of the echo signal spectrum. Such a design has the advantage of outperforming other structured patterns to the extent that suboptimal selection matrices provide a good performance and can be efficiently computed with greedy approaches.
https://doi.org/10.3390/s20236734
Hardware architecture for ultra-wideband channel impulse response measurements using compressed sensing. - In: 28th European Signal Processing Conference (EUSIPCO 2020), (2020), S. 1663-1667
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. A channel is excited with a periodic M-sequence and its response signal is observed using a Random Demodulator (RD), which observes pseudo-random linear combinations of the response signal at a rate significantly lower than the measurement bandwidth. The excitation signal and the RD mixing signal are generated from compactly implementable Linear Feedback Shift registers (LFSR) and operated from a common clock. A linear model is derived that allows retrieving an IR from a set of observations using Sparse-Signal-Recovery (SSR). A Matrix-free model implementation is possible due to the choice of synchronous LFSRs as signal generators, resulting in low computational complexity. For validation, real measurement data of a time-variant channel containing multipath components is processed by simulation models of our proposed architecture and the classic M-Sequence method. We show successful IR recovery using our architecture and SSR, outperforming the classic method significantly in terms of IR measurement rate. Compared to the classic method, the proposed architecture allows faster measurements of sparse time-varying channels, resulting in higher Doppler tolerance without increasing hardware or data stream complexity.
https://doi.org/10.23919/Eusipco47968.2020.9287454
Acoustic process monitoring in laser beam welding. - In: 11th CIRP Conference on Photonic Technologies [LANE 2020], (2020), S. 763-768
Structure-borne acoustic emission (AE) measurement shows major advantages regarding quality assurance and process control in industrial applications. In this paper, laser beam welding of steel and aluminum was carried out under varying process parameters (welding speed, focal position) in order to provide data by means of structure-borne AE and simultaneously high-speed video recordings. The analysis is based on conventionally (e.g. filtering, autocorrelation, spectrograms) as well as machine learning methods (convolutional neural nets) and showed promising results with respect to the use of structure-borne AE for process monitoring using the example of spatter formation.
https://doi.org/10.1016/j.procir.2020.09.139
Cramér-Rao bounds for flaw localization in subsampled multistatic multichannel ultrasound NDT data. - In: 2020 IEEE International Conference on Acoustics, Speech, and Signal Processing, (2020), S. 4960-4964
https://doi.org/10.1109/ICASSP40776.2020.9053523
Ein portabler, vielfältig einsetzbarer 3D-Positionierer für Synthetik-Apertur-Ultraschallmessungen in der ZfP. - In: DACH-Jahrestagung 2019, (2019), insges. 2 S.
Paper P41
3D reconstruction of handheld data by SAFT and the influence of measurement inaccuracies. - In: 2019 IEEE International Ultrasonics Symposium (IUS), (2019), S. 2095-2098
https://doi.org/10.1109/ULTSYM.2019.8926018
Total focusing method with subsampling in space and frequency domain for ultrasound NDT. - In: 2019 IEEE International Ultrasonics Symposium (IUS), (2019), S. 2103-2106
https://doi.org/10.1109/ULTSYM.2019.8926040
SAFT processing for manually acquired ultrasonic measurement data with 3D smartInspect. - In: Insight, ISSN 0007-1137, Bd. 61 (2019), 11, S. 663-669
https://doi.org/10.1784/insi.2019.61.11.663
Defect detection from compressed 3-D ultrasonic frequency measurements. - In: 27th EUSIPCO 2019 - European Signal Processing Conference, (2019), insges. 5 S.
https://doi.org/10.23919/EUSIPCO.2019.8903133
ADMM for ND line spectral estimation using grid-free compressive sensing from multiple measurements with applications to DOA estimation. - In: 2019 IEEE International Conference on Acoustics, Speech, and Signal Processing, (2019), S. 4130-4134
https://doi.org/10.1109/ICASSP.2019.8683697
Combining matrix design for 2D DoA estimation with compressive antenna arrays using stochastic gradient descent. - In: 2019 IEEE International Conference on Acoustics, Speech, and Signal Processing, (2019), S. 5112-5116
https://doi.org/10.1109/ICASSP.2019.8683173
M-estimator based Chinese Remainder Theorem with few remainders using a Kroenecker product based mapping vector. - In: Digital signal processing, ISSN 1051-2004, Bd. 87 (2019), S. 60-74
https://doi.org/10.1016/j.dsp.2019.01.009
Vergleich und Anpassung von 3D-SAFT-Implementierungen im Zeit- und Frequenzbereich für die schnelle Grobblechprüfung. - In: DGZfP-Jahrestagung 2018, (2018), insges. 2 S.
GPU-accelerated matrix-free 3D ultrasound reconstruction for nondestructive testing. - In: 2018 IEEE International Ultrasonics Symposium (IUS), (2018), insges. 4 S.
https://doi.org/10.1109/ULTSYM.2018.8579936
Progressive online 3-D SAFT processing by matrix structure exploitation. - In: 2018 IEEE International Ultrasonics Symposium (IUS), (2018), insges. 4 S.
https://doi.org/10.1109/ULTSYM.2018.8579696
Sensing matrix sensitivity to random Gaussian perturbations in compressed sensing. - In: EUSIPCO 2018, ISBN 978-90-827970-1-5, (2018), S. 583-587
https://doi.org/10.23919/EUSIPCO.2018.8553575
Defect detection from 3D ultrasonic measurements using matrix-free sparse recovery algorithms. - In: EUSIPCO 2018, ISBN 978-90-827970-1-5, (2018), S. 1700-1704
https://doi.org/10.23919/EUSIPCO.2018.8553074
Compressive spatial channel sounding. - In: 12th European Conference on Antennas and Propagation (EuCAP 2018), ISBN 978-1-78561-816-1, (2018), insges. 5 S.
http://dx.doi.org/10.1049/cp.2018.0472
Combining matrix design for 2D DoA estimation with compressive antenna arrays. - In: WSA 2018, (2018), insges. 8 S.
https://ieeexplore.ieee.org/document/8385488
Grid-free Direction-of-Arrival estimation with compressed sensing and arbitrary antenna arrays. - In: 2018 IEEE International Conference on Acoustics, Speech, and Signal Processing, ISBN 978-1-5386-4658-8, (2018), S. 3251-3255
https://doi.org/10.1109/ICASSP.2018.8462501
Sparsity order estimation from a single compressed observation vector. - In: IEEE transactions on signal processing, ISSN 1941-0476, Bd. 66 (2018), 15, S. 3958-3971
https://doi.org/10.1109/TSP.2018.2841867
Multiband TDOA estimation from sub-Nyquist samples with distributed wideband sensing nodes. - In: 2017 IEEE Global Conference on Signal and Information Processing, ISBN 978-1-5090-5990-4, (2017), S. 96-100
https://doi.org/10.1109/GlobalSIP.2017.8308611
Performance analysis of ESPRIT-type algorithms for co-array structures. - In: 2017 IEEE 7th International Workshop on Computational Advances in Multi-Sensor Adaptive Processing (CAMSAP), (2017), insges. 5 S.
https://doi.org/10.1109/CAMSAP.2017.8313207
Broadband beamforming via frequency invariance transformation and PARAFAC decomposition. - In: 2017 IEEE 7th International Workshop on Computational Advances in Multi-Sensor Adaptive Processing (CAMSAP), (2017), insges. 5 S.
https://doi.org/10.1109/CAMSAP.2017.8313096
3D-SAFT auf vorverarbeiteten Ultraschallsignalen - schneller messen bei verbesserter Auflösung. - In: ZfP in Forschung, Entwicklung und Anwendung, (2017), insges. 2 S.
Implementation issues of 3D SAFT in time and frequency domain for the fast inspection of heavy plates. - In: 2017 IEEE International Ultrasonics Symposium (IUS), ISBN 978-1-5386-3383-0, (2017), insges. 4 S.
https://doi.org/10.1109/ULTSYM.2017.8092833
Implementation of sparse signal recovery on FPGA for ultrasonic NDT. - In: 2017 IEEE International Ultrasonics Symposium (IUS), ISBN 978-1-5386-3383-0, (2017), insges. 1 S.
https://doi.org/10.1109/ULTSYM.2017.8092308
Differential SART for sub-Nyquist tomographic reconstruction in presence of misalignments. - In: EUSIPCO 2017, ISBN 978-0-9928626-7-1, (2017), S. 2354-2358
https://doi.org/10.23919/EUSIPCO.2017.8081631
Tensor-based sparsity order estimation for big data applications. - In: EUSIPCO 2017, ISBN 978-0-9928626-7-1, (2017), S. 648-652
https://doi.org/10.23919/EUSIPCO.2017.8081287
Generalized least squares for ESPRIT-type direction of arrival estimation. - In: IEEE signal processing letters, ISSN 1558-2361, Bd. 24 (2017), 11, S. 1681-1685
https://doi.org/10.1109/LSP.2017.2751303
On the SNR variability in noisy compressed sensing. - In: IEEE signal processing letters, ISSN 1558-2361, Bd. 24 (2017), 8, S. 1148-1152
https://doi.org/10.1109/LSP.2017.2689243
Second-order performance analysis of Standard ESPRIT. - In: 2017 IEEE International Conference on Acoustics, Speech, and Signal Processing, ISBN 978-1-5090-4117-6, (2017), S. 3051-3055
https://doi.org/10.1109/ICASSP.2017.7952717
Sparse signal recovery for ultrasonic detection and reconstruction of shadowed flaws. - In: 2017 IEEE International Conference on Acoustics, Speech, and Signal Processing, ISBN 978-1-5090-4117-6, (2017), S. 816-820
https://doi.org/10.1109/ICASSP.2017.7952269
Design and analysis of compressive antenna arrays for direction of arrival estimation. - In: Signal processing, Bd. 138 (2017), S. 35-47
https://doi.org/10.1016/j.sigpro.2017.03.013
Performance analysis of multi-dimensional ESPRIT-type algorithms for arbitrary and strictly non-circular sources with spatial smoothing. - In: IEEE transactions on signal processing, ISSN 1941-0476, Bd. 65 (2017), 9, S. 2262-2276
https://doi.org/10.1109/TSP.2017.2652388
Low complexity performance assessment of a sensor array via unscented transformation. - In: Digital signal processing, ISSN 1051-2004, Bd. 63 (2017), S. 190-198
http://dx.doi.org/10.1016/j.dsp.2017.01.007
On the earth mover's distance as a performance metric for sparse support recovery. - In: 2016 IEEE Global Conference on Signal and Information Processing, ISBN 978-1-5090-4545-7, (2016), S. 1368-1372
https://doi.org/10.1109/GlobalSIP.2016.7906065
Procedures for integrating, testing and operating advanced microsatellites. - In: IFAC-PapersOnLine, ISSN 2405-8963, Bd. 49 (2016), 30, S. 75-79
http://dx.doi.org/10.1016/j.ifacol.2016.11.130
Gridless super-resolution direction finding for strictly non-circular sources based on atomic norm minimization. - In: Conference record of The Fiftieh Asilomar Conference on Signals, Systems & Computers, ISBN 978-1-5386-3954-2, (2016), S. 1518-1522
https://doi.org/10.1109/ACSSC.2016.7869631
Measurement matrix design for compressed sensing based time delay estimation. - In: 2016 24th European Signal Processing Conference (EUSIPCO), ISBN 978-0-9928626-5-7, (2016), S. 458-462
https://doi.org/10.1109/EUSIPCO.2016.7760290
On poisson compressed sensing and parameter estimation in sheet-of-light surface scanning. - In: 2016 24th European Signal Processing Conference (EUSIPCO), ISBN 978-0-9928626-5-7, (2016), S. 453-457
https://doi.org/10.1109/EUSIPCO.2016.7760289
Implementation of improved software defined radio modulation scheme and command and telemetry software interface for small satellites in 5G systems. - In: Proceedings of the 19th International Conference on OFDM and Frequency Domain Techniques (ICOF 2016), ISBN 978-3-8007-4253-0, (2016), S. 77-83
Speeding up 3D SAFT for ultrasonic NDT by sparse deconvolution. - In: 2016 IEEE International Ultrasonics Symposium (IUS), ISBN 978-1-4673-9897-8, (2016), insges. 4 S.
http://dx.doi.org/10.1109/ULTSYM.2016.7728434
Analytical performance evaluation of multi-dimensional Tensor-ESPRIT-based algorithms for strictly non-circular sources. - In: 2016 IEEE Sensor Array and Multichannel Signal Processing Workshop (SAM), ISBN 978-1-5090-2103-1, (2016), insges. 5 S.
http://dx.doi.org/10.1109/SAM.2016.7569659
Spatially resolved sub-Nyquist sensing of multiband signals with arbitrary antenna arrays. - In: 2016 IEEE 17th International Workshop on Signal Processing Advances in Wireless Communications (SPAWC), ISBN 978-1-5090-1749-2, (2016), insges. 5 S.
http://dx.doi.org/10.1109/SPAWC.2016.7536776
Deterministic Cramér-Rao bound for strictly non-circular sources and analytical analysis of the achievable gains. - In: IEEE transactions on signal processing, ISSN 1941-0476, Bd. 64 (2016), 17, S. 4417-4431
http://dx.doi.org/10.1109/TSP.2016.2566603
Antenna array optimization strategies for robust direction finding. - In: 2016 10th European Conference on Antennas and Propagation (EuCAP), ISBN 978-88-907018-6-3, (2016), insges. 5 S.
http://dx.doi.org/10.1109/EuCAP.2016.7481144
Sparsity-based direction-of-arrival estimation for strictly non-circular sources. - In: 2016 IEEE International Conference on Acoustics, Speech, and Signal Processing, ISBN 978-1-4799-9988-0, (2016), S. 3246-3250
http://dx.doi.org/10.1109/ICASSP.2016.7472277
Analytical performance assessment of esprit-type algorithms for coexisting circular and strictly non-circular signals. - In: 2016 IEEE International Conference on Acoustics, Speech, and Signal Processing, ISBN 978-1-4799-9988-0, (2016), S. 2931-2935
http://dx.doi.org/10.1109/ICASSP.2016.7472214
Temporal wireless synchronization with compressed opportunistic signals. - In: 2016 IEEE Topical Conference on Wireless Sensors and Sensor Networks, ISBN 978-1-5090-1691-4, (2016), S. 93-96
https://doi.org/10.1109/WISNET.2016.7444331
Deterministic Cramér-Rao bound for a mixture of circular and strictly non-circular signals. - In: 2015 12th International Symposium on Wireless Communication Systems (ISWCS), ISBN 978-1-4673-6540-6, (2015), S. 661-665
http://dx.doi.org/10.1109/ISWCS.2015.7454431
Compressed temporal synchronization with opportunistic signals. - In: Conference record of the Forty-ninth Asilomar Conference on Signals, Systems & Computers, ISBN 978-1-4673-8576-3, (2015), S. 204-208
https://doi.org/10.1109/ACSSC.2015.7421114
Adaptive measurement matrix design for compressed DoA estimation with sensor arrays. - In: Conference record of the Forty-ninth Asilomar Conference on Signals, Systems & Computers, ISBN 978-1-4673-8576-3, (2015), S. 1769-1773
http://dx.doi.org/10.1109/ACSSC.2015.7421455
Generalized sidelobe cancellers for multidimensional separable arrays. - In: 2015 IEEE 6th International Workshop on Computational Advances in Multi-Sensor Adaptive Processing (CAMSAP), ISBN 978-1-4799-1963-5, (2015), S. 193-196
http://dx.doi.org/10.1109/CAMSAP.2015.7383769
Detection of time-varying support via rank evolution approach for effective joint sparse recovery. - In: 2015 23rd European Signal Processing Conference (EUSIPCO), ISBN 978-0-9928626-3-3, (2015), S. 1716-1720
http://dx.doi.org/10.1109/EUSIPCO.2015.7362677
An adaptively focusing measurement design for compressed sensing based DOA estimation. - In: 2015 23rd European Signal Processing Conference (EUSIPCO), ISBN 978-0-9928626-3-3, (2015), S. 859-863
http://dx.doi.org/10.1109/EUSIPCO.2015.7362505
DoA estimation with reflectarray according to single pixel camera principle. - In: 2015 3rd International Workshop on Compressed Sensing Theory and Its Applications to Radar, Sonar and Remote Sensing (CoSeRa), ISBN 978-1-4799-7420-7, (2015), S. 268-272
http://dx.doi.org/10.1109/CoSeRa.2015.7330306
Sparsity order estimation for sub-Nyquist sampling and recovery of sparse multiband signals. - In: 2015 IEEE International Conference on Communications (ICC), (2015), S. 4907-4912
http://dx.doi.org/10.1109/ICC.2015.7249100
Numerical assessment of reflectarray applicability to CS-based DoA estimation. - In: 2015 16th International Radar Symposium (IRS), ISBN 978-1-4799-7841-0, (2015), S. 404-409
http://dx.doi.org/10.1109/IRS.2015.7226353
On the design of the measurement matrix for Compressed Sensing based DOA estimation. - In: 2015 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP), ISBN 978-1-4673-6998-5, (2015), S. 3631-3635
http://dx.doi.org/10.1109/ICASSP.2015.7178648
Esprit-type algorithms for a received mixture of circular and strictly non-circular signals. - In: 2015 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP), ISBN 978-1-4673-6998-5, (2015), S. 2809-2813
http://dx.doi.org/10.1109/ICASSP.2015.7178483
Polarimetric compressive sensing based DOA estimation. - In: WSA 2014, (2014), insges. 8 S.
http://ieeexplore.ieee.org/document/6776890/
Sparsity order estimation for single snapshot compressed sensing. - In: 48th Asilomar Conference on Signals, Systems and Computers, 2014, ISBN 978-1-4799-8298-1, (2014), S. 1220-1224
http://dx.doi.org/10.1109/ACSSC.2014.7094653
On the sensing matrix performance for support recovery of noisy sparse signals. - In: IEEE Global Conference on Signal and Information Processing (GlobalSIP), 2014, ISBN 978-1-4799-7089-6, (2014), S. 679-683
http://dx.doi.org/10.1109/GlobalSIP.2014.7032204
An empirical eigenvalue-threshold test for sparsity level estimation from compressed measurements. - In: Proceedings of the 22nd European Signal Processing Conference (EUSIPCO), 2014, ISBN 978-1-4799-4603-7, (2014), S. 1761-1765
http://ieeexplore.ieee.org/xpl/articleDetails.jsp?tp=&arnumber=6952632
Analytical ESPRIT-based performance study: what can we gain from non-circular sources?. - In: 2014 IEEE 8th Sensor Array and Multichannel Signal Processing Workshop (SAM), ISBN 978-1-4799-1481-4, (2014), S. 17-20
http://dx.doi.org/10.1109/SAM.2014.6882327
R-dimensional ESPRIT-type algorithms for strictly second-order non-circular sources and their performance analysis. - In: IEEE transactions on signal processing, ISSN 1941-0476, Bd. 62 (2014), 18, S. 4824-4838
http://dx.doi.org/10.1109/TSP.2014.2342673
Tensor subspace Tracking via Kronecker structured projections (TeTraKron) for time-varying multidimensional harmonic retrieval. - In: EURASIP journal on advances in signal processing, ISSN 1687-6180, (2014), 123, S. 1-14
https://doi.org/10.1186/1687-6180-2014-123
Tensor-based algorithms for learning multidimensional separable dictionaries. - In: IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP), 2014, ISBN 978-1-4799-2894-1, (2014), S. 2963-2967
http://dx.doi.org/10.1109/ICASSP.2014.6854345
Asymptotic performance analysis of esprit-type algorithms for circular and strictly non-circular sources with spatial smoothing. - In: IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP), 2014, ISBN 978-1-4799-2894-1, (2014), S. 2277-2281
http://dx.doi.org/10.1109/ICASSP.2014.6854005
On the estimation of grid offsets in CS-based direction-of-arrival estimation. - In: IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP), 2014, ISBN 978-1-4799-2894-1, (2014), S. 6776-6780
http://dx.doi.org/10.1109/ICASSP.2014.6854912
Analytical performance assessment of multi-dimensional matrix- and tensor-based ESPRIT-type algorithms. - In: IEEE transactions on signal processing, ISSN 1941-0476, Bd. 62 (2014), 10, S. 2611-2625
http://dx.doi.org/10.1109/TSP.2014.2313530
An efficient and flexible transmission strategy for the multi-carrier multi-user MIMO downlink. - In: IEEE transactions on vehicular technology, ISSN 1939-9359, Bd. 63 (2014), 2, S. 628-642
http://dx.doi.org/10.1109/TVT.2013.2280951
Subspace methods and exploitation of special array structures. - In: Array and statistical signal processing, ISBN 978-0-12-411597-2, (2014), S. 651-717
On the use of order selection rules for accurate parameter estimation in threshold region. - In: Proceedings of the 21st European Signal Processing Conference (EUSIPCO), 2013, ISBN 978-1-4799-3687-8, (2013), insges. 5 S.
http://ieeexplore.ieee.org/xpl/abstractAuthors.jsp?arnumber=6811694
Performance analysis of ESPRIT-type algorithms for strictly non-circular sources using structured least squares. - In: 2013 IEEE 5th International Workshop on Computational Advances in Multi-Sensor Adaptive Processing (CAMSAP), ISBN 978-1-4673-3146-3, (2013), S. 316-319
http://dx.doi.org/10.1109/CAMSAP.2013.6714071
Tensor subspace tracking via Kronecker structured projections (TeTraKron). - In: 2013 IEEE 5th International Workshop on Computational Advances in Multi-Sensor Adaptive Processing (CAMSAP), ISBN 978-1-4673-3146-3, (2013), S. 212-215
http://dx.doi.org/10.1109/CAMSAP.2013.6714045
Performance analysis of ESPRIT-type algorithms for non-circular sources. - In: IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP), 2013, ISBN 978-1-4799-0357-3, (2013), S. 3986-3990
http://dx.doi.org/10.1109/ICASSP.2013.6638407
Robust design of block diagonalization using perturbation analysis. - In: IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP), 2013, ISBN 978-1-4799-0357-3, (2013), S. 4192-4196
http://dx.doi.org/10.1109/ICASSP.2013.6638449
A tensor-based subspace method for blind estimation of MIMO channels. - In: ISWCS 2013, ISBN 978-3-8007-3529-7, (2013), S. 341-345
Efficient source enumeration for accurate direction-of-arrival estimation in threshold region. - In: Digital signal processing, ISSN 1051-2004, Bd. 23 (2013), 5, S. 1668-1677
http://dx.doi.org/10.1016/j.dsp.2013.06.009
Multidimensional prewhitening for enhanced signal reconstruction and parameter estimation in colored noise with Kronecker correlation structure. - In: Signal processing, Bd. 93 (2013), 11, S. 3209-3226
https://doi.org/10.1016/j.sigpro.2013.04.010
A semi-algebraic framework for approximate CP decompositions via simultaneous matrix diagonalizations (SECSI). - In: Signal processing, Bd. 93 (2013), 9, S. 2722-2738
https://doi.org/10.1016/j.sigpro.2013.02.016
Flexible coordinated beamforming (FlexCoBF) for the downlink of multi-user MIMO systems in single and clustered multiple cells. - In: Signal processing, Bd. 93 (2013), 9, S. 2462-2473
https://doi.org/10.1016/j.sigpro.2013.03.012
3-D unitary ESPRIT: accurate attitude estimation for unmanned aerial vehicles with a hexagon-shaped ESPAR array. - In: Digital signal processing, ISSN 1051-2004, Bd. 23 (2013), 3, S. 701-711
http://dx.doi.org/10.1016/j.dsp.2012.12.010
A semi-algebraic framework for approximate CP decompositions via joint matrix diagonalization and generalized unfoldings. - In: Conference record of the Forty Sixth Asilomar Conference on Signals, Systems and Computers (ASILOMAR), 2012, ISBN 978-1-4673-5050-1, (2012), S. 2023-2027
http://dx.doi.org/10.1109/ACSSC.2012.6489396
Distributed beamforming for two-way relaying networks with individual power constraints. - In: Conference record of the Forty Sixth Asilomar Conference on Signals, Systems and Computers (ASILOMAR), 2012, ISBN 978-1-4673-5050-1, (2012), S. 542-546
http://dx.doi.org/10.1109/ACSSC.2012.6489064
Robust source number enumeration for r-dimensional arrays in case of brief sensor failures. - In: IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP), 2012, ISBN 978-1-4673-0045-2, (2012), S. 3709-3712
http://dx.doi.org/10.1109/ICASSP.2012.6288722
Polynomial-time DC (POTDC) for sum-rate maximization in two-way AF MIMO relaying. - In: IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP), 2012, ISBN 978-1-4673-0045-2, (2012), S. 2889-2892
http://dx.doi.org/10.1109/ICASSP.2012.6288520
Efficient spatial scheduling and precoding algorithms for MC MU MIMO systems. - In: International Symposium on Wireless Communication Systems (ISWCS), 2012, ISBN 978-1-4673-0762-8, (2012), S. 731-735
http://dx.doi.org/10.1109/ISWCS.2012.6328464
Satellite ground stations with electronic beam steering . - In: IEEE First AESS European Conference on Satellite Telecommunications (ESTEL), 2012, ISBN 978-1-4673-4687-0, (2012), insges. 7 S.
http://dx.doi.org/10.1109/ESTEL.2012.6400173
Dual-symmetric parallel factor analysis using procrustes estimation and Khatri-Rao factorization. - In: Proceedings of the 20th European Signal Processing Conference (EUSIPCO), 2012, ISBN 978-1-4673-1068-0, (2012), S. 270-274
http://ieeexplore.ieee.org/xpl/articleDetails.jsp?tp=&arnumber=6333983
Impact of synchronization errors on Alamouti-STBC-based cooperative MIMO schemes. - In: IEEE 7th Sensor Array and Multichannel Signal Processing Workshop (SAM), 2012, ISBN 978-1-4673-1070-3, (2012), S. 81-84
http://dx.doi.org/10.1109/SAM.2012.6250567
Advanced algebraic concepts for efficient multi-channel signal processing, 2012. - Online-Ressource (PDF-Datei: XXIII, 383 S., 3,50 MB) : Ilmenau, Techn. Univ., Diss., 2012
Parallel als Druckausg. erschienen
Unsere moderne Gesellschaft ist Zeuge eines fundamentalen Wandels in der Art und Weise wie wir mit Technologie interagieren. Geräte werden zunehmend intelligenter - sie verfügen über mehr und mehr Rechenleistung und häufiger über eigene Kommunikationsschnittstellen. Das beginnt bei einfachen Haushaltsgeräten und reicht über Transportmittel bis zu großen überregionalen Systemen wie etwa dem Stromnetz. Die Erfassung, die Verarbeitung und der Austausch digitaler Informationen gewinnt daher immer mehr an Bedeutung. Die Tatsache, dass ein wachsender Anteil der Geräte heutzutage mobil und deshalb batteriebetrieben ist, begründet den Anspruch, digitale Signalverarbeitungsalgorithmen besonders effizient zu gestalten. Dies kommt auch dem Wunsch nach einer Echtzeitverarbeitung der großen anfallenden Datenmengen zugute. Die vorliegende Arbeit demonstriert Methoden zum Finden effizienter algebraischer Lösungen für eine Vielzahl von Anwendungen mehrkanaliger digitaler Signalverarbeitung. Solche Ansätze liefern nicht immer unbedingt die bestmögliche Lösung, kommen dieser jedoch häufig recht nahe und sind gleichzeitig bedeutend einfacher zu beschreiben und umzusetzen. Die einfache Beschreibungsform ermöglicht eine tiefgehende Analyse ihrer Leistungsfähigkeit, was für den Entwurf eines robusten und zuverlässigen Systems unabdingbar ist. Die Tatsache, dass sie nur gebräuchliche algebraische Hilfsmittel benötigen, erlaubt ihre direkte und zügige Umsetzung und den Test unter realen Bedingungen. Diese Grundidee wird anhand von drei verschiedenen Anwendungsgebieten demonstriert. Zunächst wird ein semi-algebraisches Framework zur Berechnung der kanonisch polyadischen (CP) Zerlegung mehrdimensionaler Signale vorgestellt. Dabei handelt es sich um ein sehr grundlegendes Werkzeug der multilinearen Algebra mit einem breiten Anwendungsspektrum von Mobilkommunikation über Chemie bis zur Bildverarbeitung. Verglichen mit existierenden iterativen Lösungsverfahren bietet das neue Framework die Möglichkeit, den Rechenaufwand und damit die Güte der erzielten Lösung zu steuern. Es ist außerdem weniger anfällig gegen eine schlechte Konditionierung der Ausgangsdaten. Das zweite Gebiet, das in der Arbeit besprochen wird, ist die unterraumbasierte hochauflösende Parameterschätzung für mehrdimensionale Signale, mit Anwendungsgebieten im RADAR, der Modellierung von Wellenausbreitung, oder bildgebenden Verfahren in der Medizin. Es wird gezeigt, dass sich derartige mehrdimensionale Signale mit Tensoren darstellen lassen. Dies erlaubt eine natürlichere Beschreibung und eine bessere Ausnutzung ihrer Struktur als das mit Matrizen möglich ist. Basierend auf dieser Idee entwickeln wir eine tensor-basierte Schätzung des Signalraums, welche genutzt werden kann um beliebige existierende Matrix-basierte Verfahren zu verbessern. Dies wird im Anschluss exemplarisch am Beispiel der ESPRIT-artigen Verfahren gezeigt, für die verbesserte Versionen vorgeschlagen werden, die die mehrdimensionale Struktur der Daten (Tensor-ESPRIT), nichzirkuläre Quellsymbole (NC ESPRIT), sowie beides gleichzeitig (NC Tensor-ESPRIT) ausnutzen. Um die endgültige Schätzgenauigkeit objektiv einschätzen zu können wird dann ein Framework für die analytische Beschreibung der Leistungsfähigkeit beliebiger ESPRIT-artiger Algorithmen diskutiert. Verglichen mit existierenden analytischen Ausdrücken ist unser Ansatz allgemeiner, da keine Annahmen über die statistische Verteilung von Nutzsignal und Rauschen benötigt werden und die Anzahl der zur Verfügung stehenden Schnappschüsse beliebig klein sein kann. Dies führt auf vereinfachte Ausdrücke für den mittleren quadratischen Schätzfehler, die Schlussfolgerungen über die Effizienz der Verfahren unter verschiedenen Bedingungen zulassen. Das dritte Anwendungsgebiet ist der bidirektionale Datenaustausch mit Hilfe von Relay-Stationen. Insbesondere liegt hier der Fokus auf Zwei-Wege-Relaying mit Hilfe von Amplify-and-Forward-Relays mit mehreren Antennen, da dieser Ansatz ein besonders gutes Kosten-Nutzen-Verhältnis verspricht. Es wird gezeigt, dass sich die nötige Kanalkenntnis mit einem einfachen algebraischen Tensor-basierten Schätzverfahren gewinnen lässt. Außerdem werden Verfahren zum Finden einer günstigen Relay-Verstärkungs-Strategie diskutiert. Bestehende Ansätze basieren entweder auf komplexen numerischen Optimierungsverfahren oder auf Ad-Hoc-Ansätzen die keine zufriedenstellende Bitfehlerrate oder Summenrate liefern. Deshalb schlagen wir algebraische Ansätze zum Finden der Relayverstärkungsmatrix vor, die von relevanten Systemmetriken inspiriert sind und doch einfach zu berechnen sind. Wir zeigen das algebraische ANOMAX-Verfahren zum Erreichen einer niedrigen Bitfehlerrate und seine Modifikation RR-ANOMAX zum Erreichen einer hohen Summenrate. Für den Spezialfall, in dem die Endgeräte nur eine Antenne verwenden, leiten wir eine semi-algebraische Lösung zum Finden der Summenraten-optimalen Strategie (RAGES) her. Anhand von numerischen Simulationen wird die Leistungsfähigkeit dieser Verfahren bezüglich Bitfehlerrate und erreichbarer Datenrate bewertet und ihre Effektivität gezeigt.
http://www.db-thueringen.de/servlets/DocumentServlet?id=21627
Linear precoding-based geometric mean decomposition (LP-GMD) for multi-user MIMO systems. - In: International Symposium on Wireless Communication Systems (ISWCS), 2012, ISBN 978-1-4673-0762-8, (2012), S. 1039-1043
http://dx.doi.org/10.1109/ISWCS.2012.6328526
Sum rate maximization for multi-pair two-way relaying with single-antenna amplify and forward relays. - In: IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP), 2012, ISBN 978-1-4673-0045-2, (2012), S. 2477-2480
http://dx.doi.org/10.1109/ICASSP.2012.6288418
Sum-rate maximization in two-way AF MIMO relaying: polynomial time solutions to a class of DC programming problems. - In: IEEE transactions on signal processing, ISSN 1941-0476, Bd. 60 (2012), 10, S. 5478-5493
http://dx.doi.org/10.1109/TSP.2012.2208635
Relay assisted physical resource sharing: projection based separation of multiple operators (ProBaSeMO) for two-way relaying with MIMO amplify and forward relays. - In: IEEE transactions on signal processing, ISSN 1941-0476, Bd. 60 (2012), 9, S. 4834-4848
http://dx.doi.org/10.1109/TSP.2012.2200888
A "sequentially drilled" joint congruence (SeDJoCo) transformation with applications in blind source separation and multiuser MIMO systems. - In: IEEE transactions on signal processing, ISSN 1941-0476, Bd. 60 (2012), 6, S. 2744-2757
http://dx.doi.org/10.1109/TSP.2012.2190728
Optimal and suboptimal beamforming for multi-operator two-way relaying with a MIMO amplify-and-forward relay. - In: International ITG Workshop on Smart Antennas (WSA), 2012, ISBN 978-1-4577-1924-0, (2012), S. 307-311
http://dx.doi.org/10.1109/WSA.2012.6181225
Relay-assisted spectrum and infrastructure sharing between multiple operators. - In: Future Network & Mobile Summit (FutureNetw 2011), ISBN 978-1-905824-23-6, (2011), insges. 8 S.
Tensor-based semi-blind channel estimation for MIMO OSTBC-coded systems. - In: 2011 Conference record of the Forty Fifth Asilomar Conference on Signals, Systems and Computers, ISBN 978-1-4673-0323-1, (2011), S. 449-453
http://dx.doi.org/10.1109/ACSSC.2011.6190039
Efficient spatial processing and resource allocation for amplify and forward two-way relaying. - In: Cross layer designs in WLAN systems, ISBN 978-1-8487-6227-5, (2011), S. 93-131
Spectrum and infrastructure sharing in the MIMO interference relay channels. - In: EUSIPCO 2011, (2011), S. 181-185
Source enumeration using the bootstrap for very few samples. - In: EUSIPCO 2011, (2011), S. 976-979
Efficient relay sharing (EReSH) between multiple operators in amplify-and-forward relaying systems. - In: 4th IEEE International Workshop on Computational Advances in Multi-Sensor Adaptive Processing (CAMSAP), 2011, ISBN 978-1-4577-2104-5, (2011), S. 249-252
http://dx.doi.org/10.1109/CAMSAP.2011.6135995
Subspace based multi-dimensional model order selection in colored noise scenarios. - In: IEEE Information Theory Workshop (ITW), 2011, ISBN 978-1-4577-0438-3, (2011), S. 380-384
http://dx.doi.org/10.1109/ITW.2011.6089484
Multi-dimensional model order selection. - In: EURASIP journal on advances in signal processing, ISSN 1687-6180, (2011), 26, S. 1-13
https://doi.org/10.1186/1687-6180-2011-26
Beamforming design for multi-user two-way relaying with MIMO amplify and forward relays. - In: 2011 IEEE International Conference on Acoustics, Speech and Signal Processing, ISBN 978-1-4577-0539-7, (2011), S. 2824-2827
http://dx.doi.org/10.1109/ICASSP.2011.5947072
Analytical performance assessment of 1-D structured least squares. - In: 2011 IEEE International Conference on Acoustics, Speech and Signal Processing, ISBN 978-1-4577-0539-7, (2011), S. 2464-2467
http://dx.doi.org/10.1109/ICASSP.2011.5946983
Blind estimation of SIMO channels using a tensor-based subspace method. - In: Conference record of the Forty-Fourth Asilomar Conference on Signals, Systems and Computers (ASILOMAR), 2010, ISBN 978-1-4244-9722-5, (2010), S. 8-12
http://dx.doi.org/10.1109/ACSSC.2010.5757455
Temporally resolved multi-way component analysis of dynamic sources in event-related EEG data using PARAFAC2. - In: Proceedings of EUSIPCO 2010, (2010), insges. 5 S.
Sum-rate maximization in two-way relaying systems with MIMO amplify and forward relays via generalized eigenvectors. - In: Proceedings of EUSIPCO 2010, (2010), insges. 5 S.
Spectrum and infrastructure sharing in wireless networks: a case study with relay-assisted communications. - In: Conference proceedings, ISBN 978-1-905824-16-8, (2010), insges. 8 S.
CSI acquisition concepts for advanced antenna schemes in the WINNER+ Project. - In: Conference proceedings, ISBN 978-1-905824-16-8, (2010), insges. 8 S.
Resource sharing in wireless networks: the SAPHYRE approach. - In: Conference proceedings, ISBN 978-1-905824-16-8, (2010), insges. 8 S.
Robust R-D parameter estimation via closed-form PARAFAC. - In: 2010 International ITG Workshop on Smart Antennas (WSA), ISBN 978-1-4244-6070-0, (2010), S. 99-106
http://dx.doi.org/10.1109/WSA.2010.5456382
Robust R-D parameter estimation via closed-form PARAFAC in Kronecker colored environments. - In: 7th International Symposium on Wireless Communication Systems (ISWCS), 2010, ISBN 978-1-4244-6316-9, (2010), S. 115-119
http://dx.doi.org/10.1109/ISWCS.2010.5624278
Multi-dimensional PARAFAC2 component analysis of multi-channel EEG data including temporal tracking. - In: Annual international conference of the IEEE Engineering in Medicine and Biology Society (EMBC), 2010, ISBN 978-1-4244-4123-5, (2010), S. 5375-5378
http://dx.doi.org/10.1109/IEMBS.2010.5626484
Analytical performance assessment for multi-dimensional Tensor-ESPRIT-type parameter estimation algorithms. - In: IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP), 2010, ISBN 978-1-4244-4295-9, (2010), S. 2598-2601
http://dx.doi.org/10.1109/ICASSP.2010.5496266
Iterative Sequential GSVD (I-S-GSVD) based prewhitening for multidimensional HOSVD based subspace estimation without knowledge of the noise covariance information. - In: 2010 International ITG Workshop on Smart Antennas (WSA), ISBN 978-1-4244-6070-0, (2010), S. 151-155
http://dx.doi.org/10.1109/WSA.2010.5456459
Flexible coordinated beamforming (FlexCoBF) algorithm for the downlink of multi-user MIMO systems. - In: 2010 International ITG Workshop on Smart Antennas (WSA), ISBN 978-1-4244-6070-0, (2010), S. 414-420
http://dx.doi.org/10.1109/WSA.2010.5456393
A low-complexity relay transmit strategy for two-way relaying with MIMO amplify and forward relays. - In: IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP), 2010, ISBN 978-1-4244-4295-9, (2010), S. 3254-3257
http://dx.doi.org/10.1109/ICASSP.2010.5496039
Tensor-based channel estimation and Iterative refinements for two-way relaying with multiple antennas and spatial reuse. - In: IEEE transactions on signal processing, ISSN 1941-0476, Bd. 58 (2010), 11, S. 5720-5735
http://dx.doi.org/10.1109/TSP.2010.2062179
Using a new structured joint congruence (STJOCO) transformation of Hermitian matrices for precoding in multi-user MIMO systems. - In: IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP), 2010, ISBN 978-1-4244-4295-9, (2010), S. 3414-3417
http://dx.doi.org/10.1109/ICASSP.2010.5495977
Space-time-frequency component analysis of visual evoked potentials based on the PARAFAC2 model. - In: Crossing borders within the ABC, (2010), S. 484-487
http://www.db-thueringen.de/servlets/DocumentServlet?id=17081
Tensor-based spatial smoothing (TB-SS) using multiple snapshots. - In: IEEE transactions on signal processing, ISSN 1941-0476, Bd. 58 (2010), 5, S. 2715-2728
http://dx.doi.org/10.1109/TSP.2010.2043141
Sequential GSVD based prewhitening for multidimensional HOSVD based subspace estimation. - In: 2009 International ITG Workshop on Smart Antennas, (2009), S. 205-212
Structured least squares (SLS) based enhancements of tensor-based channel estimation (TENCE) for two-way relaying with multiple antennas. - In: 2009 International ITG Workshop on Smart Antennas, (2009), S. 198-204
Deterministic prewhitening to improve subspace based parameter estimation techniques in severely colored noise environments. - In: Information technology and electrical engineering - devices and systems, materials and technologies for the future, (2009), insges. 6 S.
http://www.db-thueringen.de/servlets/DocumentServlet?id=14449
Comparison of model order selection techniques for high-resolution parameter estimation algorithms. - In: Information technology and electrical engineering - devices and systems, materials and technologies for the future, (2009), insges. 6 S.
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Near-far robustness and optimal power allocation for two-way relaying with MIMO amplify and forward relays. - In: 3rd IEEE International Workshop on Computational Advances in Multi-Sensor Adaptive Processing (CAMSAP), 2009, ISBN 978-1-4244-5180-7, (2009), S. 281-284
http://dx.doi.org/10.1109/CAMSAP.2009.5413278
Analytical performance evaluation for HOSVD-based parameter estimation schemes. - In: 3rd IEEE International Workshop on Computational Advances in Multi-Sensor Adaptive Processing (CAMSAP), 2009, ISBN 978-1-4244-5180-7, (2009), S. 77-80
http://dx.doi.org/10.1109/CAMSAP.2009.5413232
Tensor-based channel estimation (TENCE) for two-way relaying with multiple antennas and spatial reuse. - In: IEEE International Conference on Acoustics, Speech and Signal Processing, 2009, ISBN 978-1-4244-2353-8, (2009), S. 3641-3644
http://dx.doi.org/10.1109/ICASSP.2009.4960415
Multidimensional unitary tensor-ESPRIT for non-circular sources. - In: IEEE International Conference on Acoustics, Speech and Signal Processing, 2009, ISBN 978-1-4244-2353-8, (2009), S. 3577-3580
http://dx.doi.org/10.1109/ICASSP.2009.4960399
Algebraic norm-maximizing (ANOMAX) transmit strategy for two-way relaying with MIMO amplify and forward relays. - In: IEEE signal processing letters, ISSN 1558-2361, Bd. 16 (2009), 10, S. 909-912
https://doi.org/10.1109/LSP.2009.2026453
Multi-dimensional space-time-frequency component analysis of event related EEG data using closed-form PARAFAC. - In: IEEE International Conference on Acoustics, Speech and Signal Processing, 2009, ISBN 978-1-4244-2353-8, (2009), S. 349-352
http://dx.doi.org/10.1109/ICASSP.2009.4959592
Identification of signal components in multi-channel EEG signals via closed-form PARAFAC analysis and appropriate preprocessing. - In: 4th European Conference of the International Federation for Medical and Biological Engineering, (2009), S. 1226-1230
Multi-antenna processing in the WINNER air interface. - In: XXIX General Assembly, 7 - 16 August 2008, Chicago, USA, (2008), insges. 4 S.
A closed-form solution for multilinear PARAFAC decompositions. - In: The fifth IEEE Sensor Array and Multichannel Signal Processing Workshop, ISBN 978-1-424-42241-8, (2008), S. 487-491
Robust methods based on the HOSVD for estimating the model order in PARAFAC models. - In: The fifth IEEE Sensor Array and Multichannel Signal Processing Workshop, ISBN 978-1-424-42241-8, (2008), S. 510-514
Multi-user MIMO systems. - In: Technologies for the wireless future, ISBN 978-0-470-99387-3, (2008), S. 234-242
Higher-order SVD-based subspace estimation to improve the parameter estimation accuracy in multidimensional harmonic retrieval problems. - In: IEEE transactions on signal processing, ISSN 1941-0476, Bd. 56.2008, 7, Pt. 2, S. 3198-3213
http://dx.doi.org/10.1109/TSP.2008.917929
A closed-form solution for parallel factor (PARAFAC) analysis. - In: IEEE International Conference on Acoustics, Speech and Signal Processing, 2008, ISBN 978-1-4244-1483-3, (2008), S. 2365-2368
http://dx.doi.org/10.1109/ICASSP.2008.4518122
Efficient channel quantization scheme for multi-user MIMO broadcast channels with RBD precoding. - In: IEEE International Conference on Acoustics, Speech and Signal Processing, 2008, ISBN 978-1-4244-1483-3, (2008), S. 2389-2392
http://dx.doi.org/10.1109/ICASSP.2008.4518128
Enhanced model order estimation using higher-order arrays. - In: Conference record of the Forty-First Asilomar Conference on Signals, Systems and Computers, 2007, ISBN 978-1-4244-2109-1, (2007), S. 412-416
https://doi.org/10.1109/ACSSC.2007.4487242
Tensor-structure structured least squares (TS-SLS) to improve the performance of multi-dimensional Esprit-type algorithms. - In: IEEE International Conference on Acoustics, Speech and Signal Processing, 2007, 2007, S. II-893-II-896
http://dx.doi.org/10.1109/ICASSP.2007.366380
Deterministic Cramér-Rao bounds for strict sense non-circular sources. - In: International ITG/IEEE Workshop on Smart Antennas, (2007), insges. 5 S.
Higher order SVD based subspace estimation to improve multi-dimensional parameter estimation algorithms. - In: Fortieth Asilomar Conference on Signals, Systems and Computers, 2006, (2006), S. 961-965
http://dx.doi.org/10.1109/ACSSC.2006.354894
Efficient 1-D and 2-D DOA estimation for non-circular sources with hexagonal shaped ESPAR arrays. - In: 2006 IEEE International Conference on Acoustics, Speech and Signal Processing, 2006, ICASSP 2006, (2006), S. IV-881-IV-884
https://doi.org/10.1109/ICASSP.2006.1661110
Advances in subspace-based parameter estimation: Tensor-ESPRIT-type methods and non-circular sources. - 160 S Ilmenau : Techn. Univ., Diplomarbeit, 2006
Hochauflösende Parameterschätzverfahren stellen ein Forschungsgebiet dar, welches bereits seit Jahrzehnten weltweit merkliche Beachtung findet. Die entsprechenden Methoden lassen sich zur Lösung einer Vielzahl von praktischen Problemen verwenden, wie etwa der Radarsignalverarbeitung, bildgebenden Verfahren in der Medizin, Audiokodierung, Mobilkommunikationoder Kanalmodellierung aus Kanalmessdaten. Die hohe Bandbreite an möglichen Anwendungen erklärt auch, warum auf diesem Gebiet nach wie vor sehr aktiv geforscht wird. In dieser Arbeit werden zwei grundsätzliche Fortschritte in diesem Feld diskutiert. Im ersten Teil werden die mehrdimensionalen Signale, die dem Problem zu Grunde liegen, näher beleuchtet. In den meisten bisherigen Verfahren werden diese Signale mit Hilfe von Matrizen dargestellt. Da diese aber nur zweidimensional sind, geben sie die höherdimensionale Struktur der Signale nicht gut wieder. Eine sehr viel geeignetere Repräsentation ist mit Tensoren möglich, die beliebig viele Dimensionen haben können. Diese offensichtliche Feststellung ist Ausgangspunkt dafür, bestehende Verfahren mit Hilfe von Tensoren neu zu entwickeln. Im Ergebnis entstehen neuartige tensor-basierte Methoden, welche in diesem Teil der Arbeit entwickelt und evaluiert werden. Der zweite Teil befasst sich mit einer Klasse von Signalen, die als nicht-zirkuläre Signale bezeichnet werden. Hier wird gezeigt, wie bestehende hochauflösende Parameterschätzverfahren verbessert werden können, wenn die Quellsignale nicht-zirkulär sind. Es werden dann zwei Algorithmen gezeigt, die diese Verbesserungen enthalten und in ihrer Leistungsfähigkeit bewertet. Im letzten Kapitel wird schließlich die Cramér-Rao Schranke für diese Art der Signale hergeleitet, welche eine untere Schranke für den Schätzfehler einer großen Klasse von Schätzverfahren darstellt. Für das hier verwendete Datenmodell wurde diese Schranke in der bisher existierenden Literatur noch nirgends angegeben. Der Anspruch dieser Arbeit ist, die mathematischen Grundlagen für die genannten Fortschritte zu legen und Algorithmen abzuleiten, die diese Erweiterungen beinhalten. Das Hauptaugenmerk liegt also auf den theoretischen Aspekten und weniger auf den Problemen einer praktischen Anwendung dieser Verfahren.
Using 3-D unitary ESPRIT on a hexagonal shaped ESPAR antenna for 1-D and 2-D doa estimation. - In: Proceedings, (2005), insges. 8 S.
Enhancements of unitary ESPRIT for non-circular sources. - In: 2004 IEEE International Conference on Acoustics, Speech, and Signal Processing, (2004), S. II-101-II-104
https://doi.org/10.1109/ICASSP.2004.1326204