A framework for developing and evaluating algorithms for estimating multipath propagation parameters from channel sounder measurements. - In: IEEE transactions on wireless communications, Bd. 0 (2023), 0, S. 1-16
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. Sounders equipped with an omni-directional transmitter and a receiver with a uniform planar array (UPA) are considered. An accurate mathematical model is developed for the spatial frequency response of the sounder that incorporates the non-ideal cross-polar beampatterns for the UPA elements. Due to the limited Field-of-View (FoV) of each element, the model is extended to accommodate multi-FoV measurements in distinct azimuth directions. A beamspace representation of the spatial frequency response is leveraged to develop three progressively complex algorithms aimed at solving the single-snapshot maximum likelihood estimation problem: greedy matching pursuit (CLEAN), space-alternative generalized expectation-maximization (SAGE), and RiMAX. The first two are based on purely specular MPCs whereas RiMAX also accommodates diffuse MPCs. Two approaches for performance evaluation are proposed, one with knowledge of ground truth parameters, and one based on reconstruction mean-squared error. The three algorithms are compared through a demanding channel model with hundreds of MPCs and through real measurements. The results demonstrate that CLEAN gives quite reasonable estimates which are improved by SAGE and RiMAX. Lessons learned and directions for future research are discussed.
https://doi.org/10.1109/TWC.2023.3318532
Fingerprints of the automotive radar scattering of passenger cars and vans. - In: Applied Sciences, ISSN 2076-3417, Bd. 13 (2023), 18, 10290, S. 1-12
The radar scattering characteristics of extended objects are an important parameter for perception and tracking algorithms in automated driving tasks. Therefore, high-fidelity sensor models are required to simulate and evaluate typical driving scenarios in virtual testing applications. While the general analysis of typical scattering centers of passenger cars is well studied, there are only a few publicly available reports that analyze specific features of the scattering characteristics of different vehicle types. Hence, this work presents detection distributions derived from systematic measurements for six different vehicle types, conducted with a commercial automotive radar on a proving ground. In particular, the contribution of underbody reflections to the respective radar signatures is analyzed, which are caused by multipath propagation via the road surface. The measurements reveal distinctive differences between the scattering characteristics of different vehicles, which are attributed to the respective underbody geometry.
https://doi.org/10.3390/app131810290
Microwave angiography by ultra-wideband sounding: a preliminary investigation. - In: Diagnostics, ISSN 2075-4418, Bd. 13 (2023), 18, 2950, S. 1-17
Angiography is a very informative method for physicians such as cardiologists, neurologists and neuroscientists. The current modalities experience some shortages, e.g., ultrasound is very operator dependent. The computerized tomography (CT) and magnetic resonance (MR) angiography are very expensive and near infrared spectroscopy cannot capture the deep arteries. Microwave technology has the potential to address some of these issues while compromising between operator dependency, cost, speed, penetration depth and resolution. This paper studies the feasibility of microwave signals for monitoring of arteries. To this aim, a homogenous phantom mimicking body tissue is built. Four elastic tubes simulate arteries and a mechanical system creates pulsations in these arteries. A multiple input multiple output (MIMO) array of ultra-wideband (UWB) transmitters and receivers illuminates the phantom and captures the reflected signals over the desired observation time period. Since we are only interested in the imaging of dynamic parts, i.e., arteries, the static clutters can be suppressed easily by background subtraction method. To obtain a fast image of arteries, which are pulsating with the heartbeat rate, we calculate the Fourier transform of each channel of the MIMO system over the observation time and apply delay and sum (DAS) beamforming method on the heartbeat rate aligned spectral component. The results show that the lateral and longitudinal images and motion mode (M-mode) time series of different points of phantom have the potential to be used for diagnosis.
https://doi.org/10.3390/diagnostics13182950
Intelligent Energy-aware Routing Protocol in Mobile IoT Networks based on SDN. - In: IEEE transactions on green communications and networking, ISSN 2473-2400, Bd. 7 (2023), 4, S. 2093-2103
Intelligent devices and equipment have affected almost all aspects of our life and behavior. The type of connection and the manner of communication between this large volume of devices has caused the emergence of a vast field in the Internet called the Internet of Things, which significantly highlights the issue of energy management and increases the lifetime of networks. Complex communications, especially in mobile networks, have generated many challenges for network designers. To solve these challenges, the Software Defined Networking (SDN) paradigm has reduced the overhead in the devices caused by processing and computing by adding new capabilities to mobile IoT networks. This technique transfers energy-consuming tasks to the central controller, which manages continuous topological changes of the network in dynamic environments. This paper presents a new routing approach called Intelligent Energy-aware Routing Protocol in Mobile IoT Networks based on SDN (IERMIoT), which tries to manage the dynamic changes of topology due to the movement of mobile nodes to increase the network’s lifetime and prevent energy dissipation. For this purpose, it defines clusters of nodes and uses an intelligent evolutionary algorithm to determine the number of clusters required in the network and their balanced distribution in the dynamic environment. Also, this approach considers a mechanism to reduce the overhead of control packets and routing packets, which significantly affects the energy consumption of nodes. The simulation results indicate the proposed solution’s effectiveness compared to other simulated approaches with respect to packet delivery rate, average energy consumption, network lifetime, number of alive nodes, coverage, and routing overhead.
https://doi.org/10.1109/TGCN.2023.3296272
Enhanced solutions for the block-term decomposition in rank-(Lr, Lr, 1) terms. - In: IEEE transactions on signal processing, ISSN 1941-0476, Bd. 71 (2023), S. 2608-2621
The block-term decompositions (BTD) represent tensors as a linear combination of low multilinear rank terms and can be explicitly related to the Canonical Polyadic decomposition (CPD). In this paper, we introduce the SECSI-BTD framework, which exploits the connection between two decompositions to estimate the block-terms of the rank-(Lr, Lr, 1) BTD. The proposed SECSI-BTD algorithm includes the initial calculation of the factor estimates using the SEmi-algebraic framework for approximate Canonical polyadic decompositions via SImultaneous Matrix Diagonalizations (SECSI), followed by clustering and refinement procedures that return the appropriate rank-(Lr, Lr, 1) BTD terms. Moreover, we introduce a new approach to estimate the multilinear rank structure of the tensor based on the HOSVD and $k$-means clustering. Since the proposed SECSI-BTD algorithm does not require a known rank structure but can still take advantage of the known ranks when available, it is more flexible than the existing techniques in the literature. Additionally, our algorithm does not require multiple initializations, and the simulation results show that it provides more accurate results and a better convergence behavior for an extensive range of SNRs.
https://doi.org/10.1109/TSP.2023.3289730
Structured Nyquist correlation reconstruction for DOA estimation with sparse arrays. - In: IEEE transactions on signal processing, ISSN 1941-0476, Bd. 71 (2023), S. 1849-1862
Sparse arrays are known to achieve an increased number of degrees-of-freedom (DOFs) for direction-of-arrival (DOA) estimation, where an augmented virtual uniform array calculated from the correlations of sub-Nyquist spatial samples is processed to retrieve the angles unambiguously. Nevertheless, the geometry of the derived virtual array is dominated by the specific physical array configurations, as well as the deviation caused by the practical unforeseen circumstances such as detection malfunction and missing data, resulting in a quite sensitive model for virtual array signal processing. In this paper, we propose a novel sparse array DOA estimation algorithm via structured correlation reconstruction, where the Nyquist spatial filling is implemented on the physical array with a compressed transformation related to its equivalent filled array to guarantee the general applicability. While the unknown correlations located in the whole rows and columns of the augmented covariance matrix lead to the fact that strong incoherence property is no longer satisfied for matrix completion, the structural information is introduced as a priori to formulate the structured correlation reconstruction problem for matrix reconstruction. As such, the reconstructed covariance matrix can be effectively processed with full utilization of the achievable DOFs from the virtual array, but with a more flexible constraint on the array configuration. The described estimation problem is theoretically analyzed by deriving the corresponding Cramér-Rao bound (CRB). Moreover, we compare the derived CRB with the performance of the virtual array interpolation-based algorithm. Simulation results demonstrate the effectiveness of the proposed algorithm in terms of DOFs, resolution, and estimation accuracy.
https://doi.org/10.1109/TSP.2023.3251110
Twenty-five years of sensor array and multichannel signal processing: a review of progress to date and potential research directions. - In: IEEE signal processing magazine, ISSN 1558-0792, Bd. 40 (2023), 4, S. 80-91
In this article, a general introduction to the area of sensor array and multichannel signal processing is provided, including associated activities of the IEEE Signal Processing Society (SPS) Sensor Array and Multichannel (SAM) Technical Committee (TC). The main technological advances in five SAM subareas made in the past 25 years are then presented in detail, including beamforming, direction-of-arrival (DOA) estimation, sensor location optimization, target/source localization based on sensor arrays, and multiple-input multiple-output (MIMO) arrays. Six recent developments are also provided at the end to indicate possible promising directions for future SAM research, which are graph signal processing (GSP) for sensor networks; tensor-based array signal processing, quaternion-valued array signal processing, 1-bit and noncoherent sensor array signal processing, machine learning and artificial intelligence (AI) for sensor arrays; and array signal processing for next-generation communication systems.
https://doi.org/10.1109/MSP.2023.3258060
Space-time adaptive processing as a solution for mitigating interference using spatially-distributed antenna arrays. - In: Navigation, ISSN 2161-4296, Bd. 70 (2023), 3, navi.592, insges. 23 S.
Antenna arrays and spatial processing techniques are among the most effective countermeasures against interference. Here, we demonstrate a new array concept consisting of spatially-distributed subarrays that are small enough to fit inside the non-metallic parts of an automobile. This will facilitate concealed installation of these devices in bumpers or side mirrors, which is a strict requirement of the industry and preferred by the customers. Using beamforming algorithms, this array was proven to be robust against jammers in the L1 band. The large distances between the individual antenna elements resulted in a non-negligible baseband delay that violated the narrowband assumption and increased with bandwidth. Hence, this paper demonstrates the influence of a jammer in the L5 band. Space-time adaptive processing that allows for compensation of the delays was introduced and analyzed. Improvements in interference mitigation capabilities were assessed and compared to those of pure spatial state-of-the-art implementation. Real-life measurement data was used to ensure realistic results.
https://doi.org/10.33012/navi.592
An efficient modeling approach of 1D-planar metamaterials in the high-frequency regime. - In: Compel, ISSN 2054-5606, Bd. 42 (2023), 3, S. 776-786
Purpose The purpose of this paper is to present an alternative modeling approach in terms of the determination of a physically equivalent circuit model for one-dimensional (1D) planar metamaterials in the high-frequency regime, without a postprocessing optimization procedure. Thereby, an efficient implementation of physical relationships is aimed. Design/methodology/approach In this paper, a method based on quasi-stationary simulations and mathematical conversions to derive the values for a physically equivalent circuit model is proposed. Because the electromagnetic coupling mechanisms are investigated in detail, a simplification for the considered multiconductor transmission line structure is achieved. Findings The results show that the proposed modeling approach is an efficient and physically meaningful alternative to classical full-wave simulation techniques for the investigated inhomogeneous transmission line structure in both the time domain as well as in the frequency domain. In the course of this, the effort is reduced while a comparable accuracy is maintained, whereby specific coupling mechanisms are considered in circuit simulations. Originality/value The process to obtain information about physically interpretable lumped element values for a given structure or to determine a layout for known ones is simplified with the aid of the proposed approach. An advantageous adaption of the presented procedure to other areas of application is well conceivable.
https://doi.org/10.1108/COMPEL-09-2022-0313
Configurable pseudo noise radar imaging system enabling synchronous MIMO channel extension. - In: Sensors, ISSN 1424-8220, Bd. 23 (2023), 5, 2454, insges. 27 S.
In this article, we propose an evolved system design approach to ultra-wideband (UWB) radar based on pseudo-random noise (PRN) sequences, the key features of which are its user-adaptability to meet the demands provided by desired microwave imaging applications and its multichannel scalability. In light of providing a fully synchronized multichannel radar imaging system for short-range imaging as mine detection, non-destructive testing (NDT) or medical imaging, the advanced system architecture is presented with a special focus put on the implemented synchronization mechanism and clocking scheme. The core of the targeted adaptivity is provided by means of hardware, such as variable clock generators and dividers as well as programmable PRN generators. In addition to adaptive hardware, the customization of signal processing is feasible within an extensive open-source framework using the Red Pitaya® data acquisition platform. A system benchmark in terms of signal-to-noise ratio (SNR), jitter, and synchronization stability is conducted to determine the achievable performance of the prototype system put into practice. Furthermore, an outlook on the planned future development and performance improvement is provided.
https://doi.org/10.3390/s23052454