{"title":"An improved model for the phase of backscattered electromagnetic fields from a conducting rotating cylinder","authors":"Esmail M. M. Abuhdima, R. Penno","doi":"10.1109/NAECON.2015.7443063","DOIUrl":"https://doi.org/10.1109/NAECON.2015.7443063","url":null,"abstract":"The rotation or vibration of a complex scattering object induces frequency modulations on the scattered signal. This modulation during this rotation or vibration is referred to as the micro-Doppler effect. The Micro-Doppler effect was investigated by many researchers in the past for different types of rotating objects, such as propellers of a fixed wing aircraft and rotors of a helicopter. In this paper, we examine the time-frequency analysis of a rotating, very good conducting cylinder. The scattering of an electromagnetic H-wave by a rotating very good conducting cylinder is investigated using the Franklin transformation. Then, micro-Doppler effects can be extracted by using the short time, fast Fourier transform for scattered fields associated with the rotational motion. The simulated results confirm that the Franklin transformation gives a more accurate analysis for a rotating, very good conducting cylinder than Galilean transformation. Also the results demonstrate the difference between the stationary and rotating very good conducting cylinders in time frequency analysis. Finally, the simulation shows that this approach produces a different result than previous approaches such as the Chen model.","PeriodicalId":133804,"journal":{"name":"2015 National Aerospace and Electronics Conference (NAECON)","volume":"60 ","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2015-06-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"113988427","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Md. Zahangir Alom, Venkataramesh Bontupalli, T. Taha
{"title":"Intrusion detection using deep belief networks","authors":"Md. Zahangir Alom, Venkataramesh Bontupalli, T. Taha","doi":"10.1109/NAECON.2015.7443094","DOIUrl":"https://doi.org/10.1109/NAECON.2015.7443094","url":null,"abstract":"With the advent of digital technology, security threats for computer networks have increased dramatically over the last decade being much bolder and brazen. There is a great need for an effective Intrusion Detection System (IDS) which are intelligent specialized system designed to interpret the intrusion attempts in incoming network traffic. Deep belief neural (DBN) networks proved to be the most influential deep neural nets and generative neural networks that stack Restricted Boltzmann Machines. In this paper, we explore the capabilities of DBN's performing intrusion detection through series of experiments after training it with NSL-KDD dataset. The trained DBN network now identifies any kind of unknown attack in dataset supplied to it and to the best of our knowledge this is first comprehensive paper performing intrusion detection using deep belief nets. The proposed system not only detect attacks but also classify them in five groups with the accuracy of identifying and classifying network activity based on limited, incomplete, and nonlinear data sources. The proposed system achieved detection accuracy about 97.5% for only fifty iterations that is state of art performance compare to the existing system till today for intrusion detection.","PeriodicalId":133804,"journal":{"name":"2015 National Aerospace and Electronics Conference (NAECON)","volume":"92 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2015-06-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121934700","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"Multi-intelligence critical rating assessment of fusion techniques (MiCRAFT) method","authors":"Erik Blasch","doi":"10.1117/12.2177539","DOIUrl":"https://doi.org/10.1117/12.2177539","url":null,"abstract":"Assessment of multi-intelligence fusion techniques includes algorithm performance credibility, mission needs quality assessment, and work-domain usability. Situation awareness (SAW) bridges low-level information fusion (tracking and identification), with high-level information fusion (threat and scenario-based assessment), against user refinement (physical, cognitive, and information tasks). To measure SAW, common techniques include the NASA TLX (Task Load Index), SAGAT (Situational Awareness Global Assessment Technique) probes, SART (Situational Awareness Rating Technique) questionnaires, and CDM (Critical Decision Method) decision points. These SAW tools are combined for a Multi-Intelligence Critical Rating Assessment of Fusion Techniques (MiCRAFT). The focus is to measure user refinement of a situation over the information fusion quality of service (QoS) metrics: timeliness, accuracy, confidence, workload (cost), and attention (throughput). A key component of any user analysis includes correlation, association, and summarization of data; so we also seek measure SAW in the QuEST of information.","PeriodicalId":133804,"journal":{"name":"2015 National Aerospace and Electronics Conference (NAECON)","volume":"11 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2015-06-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126217066","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Dan Shen, B. Jia, Genshe Chen, K. Pham, Erik Blasch
{"title":"Space based sensor management strategies based on informational uncertainty pursuit-evasion games","authors":"Dan Shen, B. Jia, Genshe Chen, K. Pham, Erik Blasch","doi":"10.1109/NAECON.2015.7443045","DOIUrl":"https://doi.org/10.1109/NAECON.2015.7443045","url":null,"abstract":"In this paper, a pursuit-evasion (PE) orbital game approach for space situational awareness (SSA) is presented to deal with imperfect measurements and information with uncertainties. The objective function includes the distance to be minimized by pursuers (observers/sensors) and maximized by evaders (space objects being tracked). The proposed PE approach provides a method to solve the realistic SSA problem with imperfect state information, where the evader will exploit the sensing and tracking model to confuse their opponents by corrupting their tracking estimates, while the pursuer wants to decrease the tracking uncertainties. A numerical simulation scenario with one space based space surveillance (SBSS) satellite as a pursuer and one geosynchronous (GEO) satellite as an evader is simulated to demonstrate the PE orbital game approach. Both SBSS and GEO apply the continuous low-thrust such as the Ion thrust in maneuvers. An add-on module is developed for the NORAD SGP4/SDP4 to propagate the satellites with maneuvers. Worst case maneuvering strategies for SBSS satellites are obtained from the Nash equilibrium of the PE game.","PeriodicalId":133804,"journal":{"name":"2015 National Aerospace and Electronics Conference (NAECON)","volume":"83 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2015-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124309951","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}