1,206 research outputs found

    A Unified Multi-Functional Dynamic Spectrum Access Framework: Tutorial, Theory and Multi-GHz Wideband Testbed

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    Dynamic spectrum access is a must-have ingredient for future sensors that are ideally cognitive. The goal of this paper is a tutorial treatment of wideband cognitive radio and radar—a convergence of (1) algorithms survey, (2) hardware platforms survey, (3) challenges for multi-function (radar/communications) multi-GHz front end, (4) compressed sensing for multi-GHz waveforms—revolutionary A/D, (5) machine learning for cognitive radio/radar, (6) quickest detection, and (7) overlay/underlay cognitive radio waveforms. One focus of this paper is to address the multi-GHz front end, which is the challenge for the next-generation cognitive sensors. The unifying theme of this paper is to spell out the convergence for cognitive radio, radar, and anti-jamming. Moore’s law drives the system functions into digital parts. From a system viewpoint, this paper gives the first comprehensive treatment for the functions and the challenges of this multi-function (wideband) system. This paper brings together the inter-disciplinary knowledge

    Non-Linear Signal Processing methods for UAV detections from a Multi-function X-band Radar

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    This article develops the applicability of non-linear processing techniques such as Compressed Sensing (CS), Principal Component Analysis (PCA), Iterative Adaptive Approach (IAA) and Multiple-input-multiple-output (MIMO) for the purpose of enhanced UAV detections using portable radar systems. The combined scheme has many advantages and the potential for better detection and classification accuracy. Some of the benefits are discussed here with a phased array platform in mind, the novel portable phased array Radar (PWR) by Agile RF Systems (ARS), which offers quadrant outputs. CS and IAA both show promising results when applied to micro-Doppler processing of radar returns owing to the sparse nature of the target Doppler frequencies. This shows promise in reducing the dwell time and increase the rate at which a volume can be interrogated. Real-time processing of target information with iterative and non-linear solutions is possible now with the advent of GPU-based graphics processing hardware. Simulations show promising results

    Experimental Synthetic Aperture Radar with Dynamic Metasurfaces

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    We investigate the use of a dynamic metasurface as the transmitting antenna for a synthetic aperture radar (SAR) imaging system. The dynamic metasurface consists of a one-dimensional microstrip waveguide with complementary electric resonator (cELC) elements patterned into the upper conductor. Integrated into each of the cELCs are two diodes that can be used to shift each cELC resonance out of band with an applied voltage. The aperture is designed to operate at K band frequencies (17.5 to 20.3 GHz), with a bandwidth of 2.8 GHz. We experimentally demonstrate imaging with a fabricated metasurface aperture using existing SAR modalities, showing image quality comparable to traditional antennas. The agility of this aperture allows it to operate in spotlight and stripmap SAR modes, as well as in a third modality inspired by computational imaging strategies. We describe its operation in detail, demonstrate high-quality imaging in both 2D and 3D, and examine various trade-offs governing the integration of dynamic metasurfaces in future SAR imaging platforms

    Bayesian Sparse Fourier Representation of Off-Grid Targets

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    We consider the problem of estimating a finite sum of cisoids via the use of a sparsifying Fourier dictionary (problem that may be of use in many radar applications). Numerous signal sparse representation (SSR) techniques can be found in the literature regarding this problem. However, they are usually very sensitive to grid mismatch. In this paper, we present a new Bayesian model robust towards grid mismatch. Synthetic and experimental radar data are used to assess the ability of the proposed approach to robustify the SSR towards grid mismatch

    Coded access optical sensor (CAOS) imager and applications

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    Starting in 2001, we proposed and extensively demonstrated (using a DMD: Digital Micromirror Device) an agile pixel Spatial Light Modulator (SLM)-based optical imager based on single pixel photo-detection (also called a single pixel camera) that is suited for operations with both coherent and incoherent light across broad spectral bands. This imager design operates with the agile pixels programmed in a limited SNR operations starring time-multiplexed mode where acquisition of image irradiance (i.e., intensity) data is done one agile pixel at a time across the SLM plane where the incident image radiation is present. Motivated by modern day advances in RF wireless, optical wired communications and electronic signal processing technologies and using our prior-art SLM-based optical imager design, described using a surprisingly simple approach is a new imager design called Coded Access Optical Sensor (CAOS) that has the ability to alleviate some of the key prior imager fundamental limitations. The agile pixel in the CAOS imager can operate in different time-frequency coding modes like Frequency Division Multiple Access (FDMA), Code-Division Multiple Access (CDMA), and Time Division Multiple Access (TDMA). Data from a first CAOS camera demonstration is described along with novel designs of CAOS-based optical instruments for various applications
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