相关论文: Correlated Non-Coherent Radar Detection for Gamma-…
The general problem of computing the false-alarm rate vs. detection-threshold relationship for a bank of correlators is addressed, in the context of maximum-likelihood detection of gravitational waves, with specific reference to chirps from…
Foreground removal presents a significant obstacle in both current and forthcoming intensity mapping surveys. While numerous techniques have been developed that show promise in simulated datasets, their efficacy often diminishes when…
Data and data sources have become increasingly essential in recent decades. Scientists and researchers require more data to deploy AI approaches as the field continues to improve. In recent years, the rapid technological advancements have…
The Random Coupling Model (RCM) is a statistical approach for studying the scattering properties of linear wave chaotic systems in the semi-classical regime. Its success has been experimentally verified in various over-moded wave settings,…
Inelastic light scattering is an intensively used tool in the study of electronic properties of solids. Triggered by the discovery of high temperature superconductivity in the cuprates and by new developments in instrumentation, light…
Curvature radiation is a natural candidate for the emission mechanism of FRB. However, FRB spectra have structure with $\Delta \nu/\nu \sim \text{0.03--0.2}$, inconsistent with the very smooth spectrum of curvature radiation. Although this…
The range of stimulated Raman scattering (SRS) frequencies covers a domain which at the low end abuts half the laser frequency, omega_0 / 2, according to the simplest SRS theories, corresponding to scatter from electron densities near 1/4…
There are observational facts and theoretical arguments for an origin of gamma-ray bursts in molecular clouds in distant galaxies. If this is true, one could detect a significant flux of GRB prompt and early afterglow X-ray radiation…
Target tracking represents a state estimation problem recurrent in many practical scenarios like air traffic control, autonomous vehicles, marine radar surveillance and so on. In a Bayesian perspective, when phenomena like clutter are…
Since Kelly's pioneering work on GLRT-based adaptive detection, many solutions have been proposed to enhance either selectivity or robustness of radar detectors to mismatched signals. In this paper such a problem is addressed in a different…
Distinguishing between the instantaneous and delayed scatterers in synthetic aperture radar (SAR) images is important for target identification and characterization. To perform this task, one can use the autocorrelation analysis of…
In automotive radar applications, multiple radars are used in all vehicles for improving the imaging quality. However this causes radar-to-radar interference from neighbouring vehicles, thus reducing the imaging quality. One metric to…
Estimating the disturbance or clutter covariance is a centrally important problem in radar space time adaptive processing (STAP). The disturbance covariance matrix should be inferred from training sample observations in practice. Large…
This paper deals with the problem of detecting maritime targets embedded in nonhomogeneous sea clutter, where limited number of secondary data is available due to the heterogeneity of sea clutter. A class of linear discriminant analysis…
Simulation of radar cross-sections (RCS) of pedestrians at automotive radar frequencies forms a key tool for software verification test beds for advanced driver assistance systems. Two commonly used simulation methods are: the…
In the last decade a lot of research activity focused on the use of quantum entanglement as a resource for remote target detection, i.e. on the design of a quantum radar. The literature on this subject uses tools of quantum optics and…
Occlusion is a key factor leading to detection failures. This paper proposes a motion-assisted detection (MAD) method that actively plans an executable path, for the robot to observe the target at a new viewpoint with potentially reduced…
Sparse Bayesian learning (SBL)-aided target localization is conceived for a bistatic mmWave MIMO radar system in the presence of unknown clutter, followed by the development of an angle-Doppler (AD)-domain representation of the…
Detecting ships in synthetic aperture radar (SAR) images is challenging due to strong speckle noise, complex surroundings, and varying scales. This paper proposes MLDet, a multitask learning framework for SAR ship detection, consisting of…
One of the fundamental problems in network analysis is detecting community structure in multi-layer networks, of which each layer represents one type of edge information among the nodes. We propose integrative spectral clustering approaches…