A5063356537- Radar Systems and Signal Processing
- Direction-of-Arrival Estimation Techniques
- Advanced SAR Imaging Techniques
- Wireless Signal Modulation Classification
- Speech and Audio Processing
- Indoor and Outdoor Localization Technologies
- Antenna Design and Optimization
- Random Matrices and Applications
- Distributed Sensor Networks and Detection Algorithms
- Energy Harvesting in Wireless Networks
- Terahertz technology and applications
- Orbital Angular Momentum in Optics
- Underwater Vehicles and Communication Systems
- Microwave Imaging and Scattering Analysis
- Laser Design and Applications
- Spectroscopy and Laser Applications
- Superconducting and THz Device Technology
- Radio Frequency Integrated Circuit Design
- Radio Astronomy Observations and Technology
- Wireless Communication Security Techniques
- Advanced MIMO Systems Optimization
- Structural Health Monitoring Techniques
- Sparse and Compressive Sensing Techniques
- Advanced Wireless Communication Technologies
Ruhr University Bochum
2018-2023
ORCID
2021
This article considers the problem of multitarget detection for massive multiple input output cognitive radar (CR). The concept CR is based on perception-action cycle that senses and intelligently adapts to dynamic environment in order optimally satisfy a specific mission. However, this usually requires priori knowledge environmental model, which not available most cases. We propose reinforcement learning (RL) algorithm presence unknown disturbance statistics. acts as an agent continuously...
Motivated by the growing interest in integrated sensing and communication for 6th generation (6G) networks, this paper presents a cognitive Multiple-Input Multiple-Output (MIMO) radar system enhanced reinforcement learning (RL) robust multitarget detection dynamic environments. The employs planar array configuration adapts its transmitted waveforms beamforming patterns to optimize performance presence of unknown two-dimensional (2D) disturbances. A Wald-type detector is with SARSA-based RL...
In this paper, we propose to utilize a reconfigurable intelligent surface (RIS) aided millimeter wave (mmWave) multiple-input-multiple-output (MIMO) radar system for multi-target localization. The goal is detect multiple targets with sufficient accuracy using an adaptive localization algorithm utilizing the concept of hierarchical codebook design. simulation results show that in case blocked line sight (LOS) between transmitter and targets, receiver can still localize all very good RIS.
We present a MUSIC-based Direction of Arrival (DOA) estimation strategy using small antenna arrays, via employing deep learning for reconstructing the signals virtual large array. Not only does proposed deliver significantly better performance than simply plugging incoming into MUSIC, but surprisingly, is also directly an actual array with MUSIC high angle ranges and low test SNR values. further analyze best choice training as function SNR, observe dramatic changes in behavior this different ranges.
In this paper a robust algorithm for DOA estimation of coherent sources in presence antenna array imperfections is presented. We exploit the current advances deep learning to overcome two most common problems facing state art algorithms (i.e. and imperfections). propose auto encoder (AE) that able correctly resolve without need spatial smoothing, hence avoiding possible processing overhead delays. Moreover, we assumed received signal model such as mutual coupling, gain/ phase mismatches,...
In this paper, we propose a cognitive Massive MIMO integrated communication and sensing (ICAS) system that integrates both functionalities, enabling efficient use of the congested spectrum. To achieve this, introduce reinforcement learning (RL) approach involves adaptability is able to optimize joint waveform for aforementioned multiple objectives. We demonstrate RL can improve state-of-the-art techniques aims at designing from ground-up achieving trade-off. Our results show greatly enhance...
We jointly design an information-theoretic transmit and receive radar beamformers for spatially near multiple extended targets. maximize the mutual information (MI) between received signals targets signatures that allows extraction of unknown features, which may include shape, dimensions, material. However, high interference caused by might obstruct extraction, directing toward steering vector as done in conventional does not solve this problem, especially In letter, iterative algorithm is...
Reducing the strong beam divergence inherent to Orbital Angular Momentum waves (also known as OAM or vortex waves), a tailored lens and reflector are presented in this study. The generation of is accomplished by Uniform Circular Patch Antenna Array (UCA) operating at 10 GHz. Here, set up two correspondingly designed shape functions rotated around antenna's center axis broadside direction (i.e. body revolution approach). Initially, introduced be compared UCA presence absence conventional...
In this paper, we investigate a non-lineof-sight (NLOS) sensing problem at terahertz frequencies. To be able to observe the targets shadowed by blockage, propose method using reconfigurable intelligent surfaces (RIS). We employ bistatic radar system and scan obstructed area with RIS hierarchical codebooks (HCB). Moreover, an iterative maximum likelihood estimation (MLE) scheme yield optimum accuracy, converging Cramer-Rao lower bound (CRLB). take band-specific effects such as diffraction...
In this paper, we address the problem of direction arrival (DOA) estimation for multiple targets in presence sensor failures a sparse array. Generally, arrays are known with very high-resolution capabilities, where N physical sensors can resolve up to ${\mathcal{O}}\left({{N^2}}\right)$ uncorrelated sources. However, among many configurations introduced literature, that provide largest hole-free co-array most susceptible failures. We propose here two machine learning (ML) methods mitigate...
In this paper, we propose a novel algorithm based on supervised learning for antenna array extrapolation the purpose of super resolution DoA estimation. We use multiple signal classification (MUSIC) as estimation technique to estimate DoA. order reduce computational burden, existing approaches focus interpolating missing elements in virtual using sparse (or non-uniform linear arrays) or employ selection within same aperture. contrast, here utilize an uniform (ULA) low number antennas (within...
The two basic performance indices characterizing the multi-target detection task in a radar system are probability of false alarm <tex xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">$(P_{FA})$</tex> and xmlns:xlink="http://www.w3.org/1999/xlink">$P_{D}$</tex> . It is well-known that, when disturbance model (i.e., clutter noise) perfectly known, Neyman-Pearson (NP) detector provides best decision strategy, i.e., that maximizes , while keeping...
Asymptotic analysis is a common tool in statistics aiming at investigating the properties of an inference methodology as number observations grows to infinity. Even if asymptotic regime cannot be achieved real-world scenarios, its practical usefulness has been proved uncountable engineering applications. In contest ISAC, one brightest example Massive Multiple-Input-Multiple-Output (MMIMO) communications framework. The breakthrough brought by MMIMO systems was showing that, antenna elements...
In this paper, we address the problem of direction arrival (DOA) estimation for multiple targets in presence sensor failures a sparse array. Generally, arrays are known with very high-resolution capabilities, where N physical sensors can resolve up to $\mathcal{O}(N^2)$ uncorrelated sources. However, among many configurations introduced literature, that provide largest hole-free co-array most susceptible failures. We propose here two machine learning (ML) methods mitigate effect and maintain...
The impact of spatial correlation on mutual information (MI) is analyzed for MIMO radar. Unlike the work done in literature statistical radar, we consider target matrix elements to study correlated radar performance. There a trade-off between coherent processing gain and diversity scatterers uncorrelated We address how MI received signal channel affected by correlation. Using majorization theory notion Schur-convexity, prove that has changing behavior with respect correlation, where at low...
This paper considers the problem of multi-target detection for massive multiple input output (MMIMO) cognitive radar (CR). The concept CR is based on perception-action cycle that senses and intelligently adapts to dynamic environment in order optimally satisfy a specific mission. However, this usually requires priori knowledge environmental model, which not available most cases. We propose reinforcement learning (RL) algorithm presence unknown disturbance statistics. acts as an agent...
In this paper a robust algorithm for DOA estimation of coherent sources in presence antenna array imperfections is presented. We exploit the current advances deep learning to overcome two most common problems facing state art algorithms (i.e. and imperfections). propose auto encoder (AE) that able correctly resolve without need spatial smoothing, hence avoiding possible processing overhead delays. Moreover, we assumed received signal model such as mutual coupling, gain/ phase mismatches,...