24 accepted papers
Joint sensing and communication (JSAC) has emerged as a promising technology in autonomous driving, as it allows simultaneous road sensing and two-way communication using a single shared platform. Meanwhile, intelligent reflective surface (IRS) enables sensing enhancement and communication with targ…
Deep learning has been shown to be a powerful tool in array processing. Sparse array reconfigurability can be an integral part of cognitive sensing in dynamic radio frequency (RF) environments. In this respect, fast-switching that avoids hardware complexity, insertion loss, and crosstalk distortion…
Radio frequency signal modulation classifications find broad applications in cognitive sensing and RF spectrum coexistence. Recently, deep neural networks have been shown to be a powerful tool for automatic modulation classification (AMC). Accounting for different signal variations is paramount towa…
The paper considers phase-only reconfigurable sparse arrays (RSAs) for receive beamforming to maximize signal-to-interference plus noise ratio (MaxSINR). We develop a design approach based on supervised deep neural network (DNN) to learn and mimic a phase-only sparse MaxSINR beamformer. The proposed…
Recent performance analysis of dual-function radar communications (DFRC) systems, which embed information using phase shift keying (PSK) into multiple-input multiple-output (MIMO) frequency hopping (FH) radar pulses, shows promising results for addressing spectrum sharing issues between radar and co…
Sparse array design aided by emerging fast sensor switching technologies can lower the overall system overhead by reducing the number of expensive transceiver chains. In this paper, we examine the active sparse array design enabling the maximum signal to interference plus noise ratio (MaxSINR) beamf…
We consider a multiple-input multiple-output (MIMO) dual function radar communication (DFRC) system employing frequency hopping (FH) radar waveforms. The DFRC system embeds communication symbols using code-shift keying (CSK) strategy. Each symbol is represented by a phase modulated pulse code sequen…
Moving platforms enable sparse arrays to assume higher degrees of freedom and lead to increased number of lags. In essence, array motion can fill the holes in the spatial auto-correlation lags associated with a fixed platform and, therefore, increase the number of sources detectable by the same phys…
Sparse arrays are typically configured considering either the environmental dependent or independent design objectives. In this paper, we investigate hybrid sparse array design satisfying dual design objectives. We consider enhancing the source identifiability and maximizing the Signal-to-Interferen…
The problem of optimum distribution of the available spatial degrees of freedom among two sparse antenna subarray beamfomers in shared aperture receiver is investigated. The two subarrays, forming a full array, co-exist on the same platform and could perform separate RF sensing and communications ta…
Optimum sparse array design for maximum output signal-to-noise ratio (MaxSNR) and signal-to-interference ratio (MaxSINR) have been shown to yield significant performance improvement compared to random or environmental-independent structured arrays, with the same number of antennas. We examine the Ma…
The problem of optimum sparse array beamformer design to maximize output signal-to-interference-plus-noise ratio (SINR) in the case of multiple narrowband sources was recently investigated. This was based on seeking both optimum sensor placement as well as optimum a single beamformer for all sources…
In recent years, radar has been employed as a fall detector, due to its superior sensing capabilities and penetration through walls. In this paper, we introduce a multi-linear subspace fall detection scheme that exploits the three radar signal variables: slow-time, fast-time, and Doppler frequency.…
Radar for indoor monitoring has recently attracted much attention that is driven by its safety, privacy-preserving, and non-wearable sensing mode. Micro-Doppler signatures offered by radars operating in the K-band can disclose intricate details and characteristics of human gait. This paper reveals k…
In this paper, we consider optimum array configurations for multiple satellite signals in interference-free environment. The two measures of maximum output signal-to-noise ratio (SNR) and equal gains towards all sources incident on the array are considered for the array design. As it is computationa…
In this paper, we consider robust direction-of-arrival (DOA) estimation for an array that contains mis-calibrated sensors with unknown gain and phase uncertainties. We develop two robust DOA estimation algorithms based on the maximum correntropy criterion (MCC). In the first algorithm, adaptively op…
Increased demand on spectrum sensing over a broad frequency band requires a high sampling rate and thus leads to a prohibitive volume of data samples. In some applications, e.g., spectrum estimation, only the second-order statistics are required. In this case, we may use a reduced data sampling rate…
In this paper, we address the suppression of frequency modulated jammers in a multi-sensor Global Navigation Satellite System (GNSS) receiver. In particular, we consider the case of sparsely sampled signals and compressed observations. In this case, applying conventional time-frequency (TF) analysis…
In this paper, we utilize Bayesian Compressive Sensing (BCS) for direction-of-arrival (DOA) estimation based on the coarray. This enables estimation of more sources than the number of physical antennas. We adopt the covariance vectorization technique to construct the received signal vectors of coarr…
For spatially distributed targets encountered in radar and sonar applications, direct application of subspace-based methods usually do not lead to an accurate estimation of the direction and angular extent of the signal arrivals. If the spatial distribution of the targets can be parameterized with a…
In this paper, we consider antenna selection and array reconfiguration in the presence of multiple interferences based on the spatial correlation coefficient (SCC) which characterizes the spatial separation between the desired signal and interference subspace. Minimizing the SCC increases the separa…
In this paper, we consider multipath exploitation and sparse reconstruction in a network of distributed multistatic radar units for stationary target localization behind walls. Multipath exploitation leverages prior information of the indoor scattering environment to eliminate ghosts targets. Howeve…
Hermite functions are an effective tool for improving the resolution of the single-window spectrogram. In this paper, we analyze the Hermite functions in the ambiguity domain and show that the higher order terms can introduce undesirable cross-terms in the multiwindow spectrogram. The optimal number…
In this paper, we propose a novel structured compressive sensing algorithm based on non-parametric Bayesian framework for the reconstruction of sparse entries with a continuous structure. A paired spike-and-slab prior is first employed to impose signal sparsity. A logistic Gaussian kernel model, whi…