DESIGN AND IMPLEMENTATION OF A PHASED ARRAY ANTENNA FOR MULTI-MISSION APPLICATIONS

Multifunction Phased Array Radar (MPAR) was defined to investigate the feasibility of integrating weather observation and air surveillance radars into a single network. Weather radars require dual polarization capability which may be also beneficial to aircraft characterization. Research activities have begun to identify challenges, mitigate risk, and demonstrate polarimetric technologies. Ten-panel, developed by MIT’s Lincoln Laboratory, was the first dual-polarized planar phased array demonstrator. Alternatively, a cylindrical polarimetric phased array radar (CPPAR) was developed at the Advanced Radar Research Center of the University of Oklahoma to resolve the intrinsic limitations of planar arrays in making accurate polarimetric measurements. The current CPPAR employs a frequency scanning patch array antenna. Since the radar’s performance would be the most important driver, the future operational CPPAR, suitable for long-range weather measurement, will utilize a new antenna with higher performance. It is the purpose of this research to propose a new dual-polarized phased array antenna for MPAR application. A crossed dipole antenna with sufficient operational frequency bandwidth is designed. A high polarization purity is achieved by using a group of efficient techniques in element scale. This element was modified to obtain a higher match between copolar beams. The modified element is utilized as an embedded element to form a cylindrical and a planar array antenna. It is demonstrated that suppressed azimuthal surface wave and consequently highly matched copolar beams can be achieved in a cylindrical array of proposed crossed dipole. In order to compensate for the electrical and geometrical asymmetry of the element, an imaged arrangement of the elements with respect to the center of the array is utilized. It is shown that a planar array of the modified crossed dipole, arranged in a specific configuration, proposes zero cross-polarization in the principal planes without increased side lobe problem. The experimental verification demonstrates that the proposed phased array antennas are promising candidates for multi-mission applications

Artificial Intelligence and COVID-19: Deep Learning Approaches for Diagnosis and Treatment

COVID-19 outbreak has put the whole world in an unprecedented difficult situation bringing life around the world to a frightening halt and claiming thousands of lives. Due to COVID-19’s spread in 212 countries and territories and increasing numbers of infected cases and death tolls mounting to 5,212,172 and 334,915 (as of May 22 2020), it remains a real threat to the public health system. This paper renders a response to combat the virus through Artificial Intelligence (AI). Some Deep Learning (DL) methods have been illustrated to reach this goal, including Generative Adversarial Networks (GANs), Extreme Learning Machine (ELM), and Long/Short Term Memory (LSTM). It delineates an integrated bioinformatics approach in which different aspects of information from a continuum of structured and unstructured data sources are put together to form the user-friendly platforms for physicians and researchers. The main advantage of these AI-based platforms is to accelerate the process of diagnosis and treatment of the COVID-19 disease. The most recent related publications and medical reports were investigated with the purpose of choosing inputs and targets of the network that could facilitate reaching a reliable Artificial Neural Network-based tool for challenges associated with COVID-19. Furthermore, there are some specific inputs for each platform, including various forms of the data, such as clinical data and medical imaging which can improve the performance of the introduced approaches toward the best responses in practical applications

Mechanically Reconfigurable, Beam-Scanning Reflectarray and Transmitarray Antennas: A Review

We review mechanically reconfigurable reflectarray (RA) and transmitarray (TA) antennas. We categorize the proposed approaches into three major groups followed by a hybrid category that is made up of a combination of the three major approaches. We discuss the examples in each category and compare their performance metrics including aperture efficiency, gain, bandwidth and scanning range and resolution. We also identify opportunities to build upon or extend these demonstrated approaches to realize further advances in antenna performance