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Linear And Nonlinear Programming

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Spotlight Synthetic Aperture Radar Signal Processing Algorithms

Mode division multiplexing (MDM) using orbital angular momentum (OAM) is a recently developed physical layer transmission technique, which has obtained intensive interest among optics, millimeter-wave, and radio frequency due to its capability to enhance communication capacity while retaining an ultra-low receiver complexity. In this paper, the system model based on OAM-MDM is mathematically analyzed and it is theoretically concluded that such system architecture can bring a vast reduction in receiver complexity without capacity penalty compared with conventional line-of-sight multiple-in-multiple-out systems under the same physical constraint. Furthermore, a $4\times 4$ OAM-MDM communication experiment adopting a pair of easily realized Cassegrain reflector antennas capable of multiplexing/demultiplexing four orthogonal OAM modes of $l = {-3}$ , −2, +2, and +3 is carried out at a microwave frequency of 10 GHz. The experimental results show high spectral efficiency as well as low receiver complexity.

Mode Division Multiplexing Communication Using Microwave Orbital Angular Momentum: An Experimental Study

https://nottingham-repository.worktribe.com/preview/2315217/Multi_Time_Series_Anomaly_Detection_for_Industry_4_0__Neurocomputing_.pdf

Multi-head CNN–RNN for multi-time series anomaly detection: An industrial case study

A system is proposed to generate vortex electromagnetic (EM) beams in the microwave band, which generates high-order vortex beams at the X-frequency band for the first time. First, the orbital angular momentum (OAM)-generating system is designed and the signal model based on the uniform circular array is presented. Subsequently, the mathematical model with array error contributions is established and, comprehensively, numerical simulations are conducted to analyze how amplitude and phase errors affect the radiation field and the EM vortex imaging. The experimental results validate that the proposed system can readily generate vortex beams of high quality, which are in agreement with the simulated results. The work paves the way to applications of OAM-carrying beams as well as a novel information-rich radar paradigm.

Generation of OAM Beams Using Phased Array in the Microwave Band

A novel radar imaging technique based on orbital angular momentum (OAM) modulation is presented. First, the generation of electromagnetic (EM) vortex wave, which carries the OAM, using incrementally phased uniform circular array (UCA) is introduced, and factors that affect the phase-front distribution are analyzed. Subsequently, echo signal models of both multiple-in–multiple-out and multiple-in–single-out modes are established. The target images are obtained using the fast Fourier transform (FFT) and back-projection methods. Simulation results demonstrate that orbital angular momentum has the prospect for acquiring the azimuth information of radar target. The signal of both OAM modulation and frequency modulation can be used to obtain two-dimensional radar target image. The work can benefit the development of novel information-rich radar based on orbital angular momentum, as well as radar target recognition.

Orbital-Angular-Momentum-Based Electromagnetic Vortex Imaging

Convolutional neural networks (CNN) have successfully been employed to tackle several remote sensing tasks such as image classification and show better performance than previous techniques. For the radar imaging community, a natural question is: Can CNN be introduced to radar imaging and enhance its performance? This letter gives an affirmative answer to this question. We first propose a processing framework by which a complex-valued CNN (CV-CNN) is used to enhance radar imaging. Then we introduce two modifications to the CV-CNN to adapt it to radar imaging tasks. Subsequently, the method to generate training data is shown and some implementation details are presented. Finally, simulations and experiments are carried out, and both results show the superiority of the proposed method on imaging quality and computational efficiency.

Enhanced Radar Imaging Using a Complex-Valued Convolutional Neural Network

Motivated by classical coincidence imaging which has been realized in optical systems, an instantaneous microwave-radar imaging technique is proposed to obtain focused high-resolution images of targets without motion limitation. Such a radar coincidence imaging method resolves target scatterers based on measuring the independent waveforms of their echoes, which is quite different from conventional radar imaging techniques where target images are derived depending on time-delay and Doppler analysis. Due to the peculiar features of coincidence imaging, there are two potential advantages of the proposed imaging method over the conventional ones: 1) shortening the imaging time to even a pulse width without resolution deterioration so as to improve the performance of processing noncooperative targets and 2) simplifying the receiver complexity, resulting in a lower cost and platform flexibility in application. The basic principle of radar coincidence imaging is to employ the time-space independent detecting signals, which are produced by a multitransmitter configuration, to make scatterers located at different positions reflect independent waveforms from each other, and then to derive the target image based on the prior knowledge of this detecting signal spatial distribution. By constructing the mathematic model, the necessary conditions of the transmitting waveforms are analyzed for achieving radar coincidence imaging. A parameterized image-reconstruction algorithm is introduced to obtain high resolution for microwave radar systems. The effectiveness of this proposed imaging method is demonstrated via a set of simulations. Furthermore, the impacts of modeling error, noise, and waveform independence on the imaging performance are discussed in the experiments.

Radar Coincidence Imaging: an Instantaneous Imaging Technique With Stochastic Signals

A super-resolution imaging technique based on the vortex electromagnetic (EM) wave, which carries orbital angular momentum (OAM), is reported in this paper. The proof-of-concept experiment for the EM vortex imaging is conducted. An imaging processing method based on the real-world OAM radar data is proposed to obtain the target profile. Experimental results validate the effectiveness of the proposed imaging method and demonstrate that the vortex EM wave can be exploited to image targets with high-resolution beyond the limit of the array aperture. This breakthrough on the Rayleigh limit paves the way for innovative techniques in radar imaging and remote sensing.

/pdf/super-resolution-radar-imaging-based-on-experimental-oam-2assxd4uqq.pdf

Yuliang Qin

Papers

Orbital-Angular-Momentum-Based Electromagnetic Vortex Imaging

Generation of OAM Beams Using Phased Array in the Microwave Band

Enhanced Radar Imaging Using a Complex-Valued Convolutional Neural Network

Radar Coincidence Imaging: an Instantaneous Imaging Technique With Stochastic Signals

Super-resolution radar imaging based on experimental OAM beams