Strategies for Co-Existence of Radio Telescope Arrays with Broadcast Stations and Wireless Communication Systems<\/strong><\/span> The project aims at achieving the coexistence strategies by developing interference mitigation techniques that factor in the high-elevation of the look direction of the telescope compared to low-elevation angles of signals emitted by base-stations and wireless systems. A co-existence strategy calls for authorized broadcast stations and wireless transmitters to cooperate with radio telescopes by reporting their locations and providing properties of their signal structures. Prior knowledge of interference location simplifies its nulling and removal by telescope array of multiple units. On the other hand, the distinction in signal characteristics between astronomical events and those of digital communications enables effective cooperative as well as non-cooperative interference identification and suppression. The project has the potential to advance spectrum sharing and utilization and therefore enhance the future capacity for U.S. industry and academic institutions in this area of research and development.<\/p>\n Selected publications:<\/strong><\/span><\/p>\n M. Guo, Y. D. Zhang, and T. Chen, \u201cDOA estimation using compressed sparse array,\u201d IEEE Transactions on Signal Processing<\/em>, vol. 66, no. 15, pp. 4133-4146, Aug. 2018.<\/p>\n S. Liu, Y. D. Zhang, T. Shan, and R. Tao, “Structure-aware Bayesian compressive sensing for frequency-hopping spectrum estimation with missing observations,” IEEE Transactions on Signal Processing<\/em>, vol. 66, no. 8, pp. 2153-2166, April 2018.<\/p>\n S.\u00a0Liu, Y. D. Zhang, and T. Shan, \u201cDetection of weak astronomical signals with frequency-hopping interference suppression,\u201d Digital Signal Processing<\/em>, vol. 72, pp. 1-8, Jan. 2018.<\/p>\n A. Hassanien, M. G. Amin, Y. D. Zhang, and F. Ahmad, \u201cPhase-modulation based dual-function radar-communications,\u201d IET Radar, Sonar, and Navigation<\/em>, vol. 10, no. 8, pp. 1411-1421, Oct. 2016.<\/p>\n A. Hassanien, M. G. Amin, Y. D. Zhang, and F. Ahmad, \u201cSignaling strategies for dual-function radar-communications: An overview,\u201d IEEE Aerospace and Electronic Systems Magazin<\/em>e, vol. 31, no. 10, pp. 36-45, Oct. 2016.<\/p>\n A. Hassanien, M. G. Amin,\u00a0Y. D. Zhang, and F. Ahmad, \u201cDual-function radar-communications: Information embedding using sidelobe control and waveform diversity,\u201d\u00a0IEEE Transactions on Signal Processing<\/em>, vol. 64, no. 8, pp. 2168-2181, April 2016.<\/p>\n A. Hassanien, M. G. Amin, Y. D. Zhang, and F. Ahmad, \u201cA dual function radar-communication system using sidelobe control and waveform diversity,\u201d in Proceedings of IEEE International Radar Conference<\/em>, Arlington, VA, May 2015.<\/p>\n A. Hassanien, M. G. Amin, Y. D. Zhang, and F. Ahmad, \u201cDual-function radar-communications using phase-rotational invariance,\u201d in Proceedings of European Signal Processing Conference<\/em>, Nice, France, Aug.-Sept. 2015.<\/span><\/p>\n Signal Processing for Improved Moving Target Detection, Localization, and Tracking using Multi-Static Passive Radars<\/strong><\/span> The objective of this effort is to investigate: (a) time-frequency analysis for motion parameter estimation, multi-target tracking and ghost detection; (b) robust target localization in the presence of positioning errors of the radar receiver platform; and (c) non-uniform sparse azimuthal data sampling. In recent years, multi-static passive radars (MPRs), which use signals of opportunity, have attracted significant interest, primarily because of their low-cost and covertness. The fact that passive radars do not emit signals also makes them the preferred choice when considering frequency spectrum congestion. MPR systems distinguish themselves from conventional active radars in a number of fronts, e.g., extremely narrow signal bandwidth, low signal power, bistatic operation, and availability of multiple transmitters. In addition, passive radars may operate in a single-frequency network (SFN), where identical waveforms are transmitted from multiple illuminators. Target detection, localization and tracking (DLT) can be applied to ground moving targets, possibly observed through the unmanned aerial vehicles (UAVs), as well as aerial targets, observed from a ground receiver. Both settings can be extended to a set of distributed receivers.<\/p>\n Selected publications:<\/strong><\/span><\/p>\n Y. D. Zhang, M. G. Amin, and B. Himed, \u201cStructure-aware sparse reconstruction and applications to passive multi-static radar,\u201d IEEE Aerospace and Electronic Systems Magazine<\/em>, special issue on Passive and Multi-static Radar for Civil Applications, vol. 32, no. 2, pp. 68-78, Feb. 2017.<\/p>\n S. Subedi, Y. D. Zhang, M. G. Amin, and B. Himed, \u201cGroup sparsity based multi-target tracking in passive multi-static radar systems using Doppler-only measurements,\u201d IEEE Transactions on Signal Processing<\/em>, vol. 64, no. 14, pp. 3619-3634, July 2016.<\/p>\n Q. Wu, Y. D. Zhang, M. G. Amin, and B. Himed, \u201cSpace-time adaptive processing and motion parameter estimation in multi-static passive radar exploiting Bayesian compressive sensing,\u201d IEEE Transactions on Geoscience and Remote Sensing<\/em>,\u00a0<\/em>vol.\u00a054, no. 2, pp. 944-957, Feb. 2016.<\/span><\/p>\n Q. Wu, Y. D. Zhang, M. G. Amin, and B. Himed, \u201cHigh-resolution passive SAR imaging exploiting structured Bayesian compressive sensing,\u201d IEEE Journal of Selected Topics in Signal Processing<\/em>, special issue on Advanced Signal Processing Techniques for Radar Applications, vol. 9, no. 8, pp. 1484-1497, Dec. 2015.<\/p>\n S. Subedi, Y. D. Zhang, M. G. Amin, and B. Himed, \u201cMotion parameters estimation of multiple ground moving targets in multi-static passive radar systems,\u201d EURASIP Journal on Advanced Signal Processing<\/em>, special issue on Sparse Sensing in Radar and Sonar Signal Processing,\u00a0vol. 2014, no. 2014:157, Oct. 2014.<\/span><\/p>\n B. K. Chalise, Y. D. Zhang, M. G. Amin, and B. Himed, \u201cTarget localization in a multi-static passive radar system through convex optimization,\u201d Signal Processing<\/em>, vol. 102, pp. 207-215, Sept. 2014.<\/span><\/p>\n Co-Prime Frequency and Aperture Design for HF Surveillance, Wideband Radar Imaging, and Nonstationary Array Processing The research employs co-prime sampling and arrays to improve radar sensing and surveillance in both narrowband and wideband signal platforms. The main objective is threefold: (1) Increased aperture and improved spatial resolution, enabling separation between individual targets and clutter in both active and passive HF radars; (2) Combating ambiguity and providing unique answers to target location coordinates in active and passive wideband radar sensing under forced coarse sampling in time, frequency, and space. These constraints can be imposed by cost, fast acquisition time, and unavailability of specific frequencies and antenna locations; (3) Improving direction finding of sources of nonstationary signals, as emitters or reflectors of EM waves, by integrating co-prime arrays with joint time-frequency signal representations. In essence, each of these two approaches, though based on a different premise, allows dealing with more sources than sensors. Each objective corresponds to one of the above three research areas.<\/span><\/p>\n Selected publications:<\/strong><\/span><\/p>\n S. Qin, Y. D. Zhang, M. G. Amin, and F. Gini, \u201cFrequency diverse coprime arrays with coprime frequency offsets for multi-target localization,\u201d IEEE Journal of Selected Topics in Signal Processing<\/em>, Special Issue on Advances in Time\/Frequency Modulated Array Signal Processing, vol. 11, no. 2, pp. 321-335, March 2017.<\/p>\n S. Qin, Y. D. Zhang, and M. G. Amin, \u201cDOA estimation of mixed coherent and uncorrelated signals exploiting a coprime MIMO system,\u201d Digital Signal Processing<\/em>, special issue on Co-prime array and sampling, vol. 61, pp. 26-34, Feb. 2017.<\/p>\n S. Qin, Y. D. Zhang, M. G. Amin, and B. Himed, \u201cDOA estimation exploiting a uniform linear array with multiple co-prime frequencies,\u201d Signal Processing,\u00a0<\/em>vol. 130, pp. 37\u201346, Jan. 2017.<\/p>\n Q. Shen, W. Liu, W. Cui, S. Wu, Y. D. Zhang, and M. G. Amin, \u201cLow-complexity wideband direction-of-arrival estimation based on co-prime arrays,\u201d IEEE\/ACM Transactions on Audio, Speech and Language Processing<\/em>, vol. 23, no. 9, pp. 1445-1456, Sept. 2015.<\/p>\n S. Qin, Y. D. Zhang, and M. G.\u00a0 Amin, \u201cGeneralized coprime array configurations for direction-of-arrival estimation,\u201d IEEE Transactions on Signal Processing<\/em>, vol. 63, no. 6, pp. 1377-1390, March 2015.<\/span><\/p>\n S. Qin, Y. D. Zhang, Q. Wu, and M. G. Amin, \u201cStructure-aware Bayesian compressive sensing for near-field source localization based on sensor-angle distributions,\u201d International Journal on Antennas and Propagation<\/em>,\u00a0vol. 2015, article ID 783467, 15 pages, March 2015.<\/span><\/p>\n S. Qin, Q. Wu, Y. D. Zhang, and M. G. Amin, \u201cDOA estimation of nonparametric spreading spatial spectrum based on Bayesian compressive sensing exploiting intra-task dependency,\u201d in Proceedings of\u00a0IEEE International Conference on Acoustics, Speech, and Signal Processing<\/em>, Brisbane, Australia, April 2015.<\/span><\/p>\n Localization Grid for Accurate Positioning Onboard a Carrier<\/span> The scope of this effort is to develop automatic aircraft tracking algorithms and verify their effectiveness through simulations and proof-of-concept experiments. The objective is (a) to develop effective aircraft tracking algorithms and evaluate their performance through computer simulations; and (b) design and perform proof-of-concept experimental studies to evaluate the aircraft tracking algorithms.<\/p>\n Selected publication:<\/strong><\/p>\n S. Subedi, E. Pauls, and Y. D. Zhang, \u201cAccurate localization and tracking of a passive RFID reader based on RSSI measurements,\u201d IEEE Journal of Radio Frequency Identification<\/em>, vol. 1, no. 2, pp. 144-154, June 2017.<\/p>\n E. Pauls and Y. D. Zhang, \u201cExperimental studies of high-accuracy RFID localization with channel impairments,\u201d in Proceedings of<\/em>\u00a0SPIE Mobile Multimedia\/Image Processing,<\/em> Security, and Applications Conference<\/em>, Baltimore, MD, April 2015.<\/p>\n Advanced Signal Processing and Emerging Sensing Technologies for Assisted Living<\/span> The main objective is to advance the area of Assisted Living by developing and applying signal analysis and processing algorithms aiming at improving radar data monitoring of elderlies in private residences. These algorithms provide enhanced detection and classification of micro and macro human motions which can be markers and barometers of the health status of the elderly.<\/p>\n Selected publications:<\/strong><\/p>\n M. G. Amin, Y. D. Zhang, F. Ahmad, and K. C. Ho, \u201cRadar signal processing for elderly fall detection; The future for in-home monitoring,\u201d IEEE Signal Processing Magazine<\/em>, special issue on Signal Processing for Assisted Living, vol. 33, no. 2, pp. 71-80, March 2016.<\/p>\n Q. Wu, Y. D. Zhang, W. Tao, and M. G. Amin, \u201cRadar-based fall detection based on Doppler time-frequency signatures for assisted living,\u201d IET Radar, Sonar & Navigation<\/em>, special issue on Application of Radar to Remote Patient Monitoring and Eldercare, vol. 9, no. 2, pp. 164-172, Feb. 2015.<\/p>\n B. Jokanovic, M. G. Amin, Y. D. Zhang, and F. Ahmad, \u201cMulti-window time-frequency signature reconstruction from undersampled continuous wave radar measurements for fall detection,\u201d IET Radar, Sonar & Navigation<\/em>, special issue on Application of Radar to Remote Patient Monitoring and Eldercare, vol. 9, no. 2, pp. 173-183, Feb. 2015.<\/p>\n L. Ramirez Rivera, E. Ulmer, Y. D. Zhang, W. Tao, and M. G. Amin, \u201cRadar-based fall detection exploiting time-frequency features,\u201d in\u00a0Proceedings of IEEE China Summit and International Conference on Signal and Information Processing<\/em>, Xi\u2019an, China, July 2014.<\/p>\n M. Wu, X. Dai, Y. D. Zhang, B. Davidson, J. Zhang, and M. G. Amin, \u201cFall detection based on sequential modeling of radar signal time-frequency features,\u201d in Proceedings of<\/em>\u00a0IEEE International Conference on Healthcare Informatics<\/em>, Philadelphia, PA, Sept. 2013.<\/p>\n Selected Past Projects<\/strong><\/p>\n Partnerships for Innovation in Acoustic and Ultrasound Technologies for Medical and Industrial Applications<\/strong><\/span> Next-Generation Over-the-Horizon HF Radar (NGOTHR) Moving Target Indicator (MTI) and Clutter Mitigation Development<\/strong><\/span> Intelligent Remote Sensing for Urban Warfare Operations<\/strong><\/span> Through-the-Wall Target Detection and Classification for Achieving Transparent Urban Structures<\/strong><\/span> High-Rate Multiuser Cooperative Diversity Systems<\/strong><\/span> Technologies for Future Naval Capabilities Radar-based Signal Processing for Assisted Living<\/strong><\/span> Development of Orphan Meter Detection Techniques<\/strong><\/span> Strategies for Co-Existence of Radio Telescope Arrays with Broadcast Stations and Wireless Communication Systems Funded by National Science Foundation (NSF) …<\/p>\n","protected":false},"author":7519,"featured_media":0,"parent":0,"menu_order":50,"comment_status":"closed","ping_status":"closed","template":"","meta":{"footnotes":""},"class_list":["post-19","page","type-page","status-publish","hentry"],"_links":{"self":[{"href":"https:\/\/sites.temple.edu\/aspl\/wp-json\/wp\/v2\/pages\/19","targetHints":{"allow":["GET"]}}],"collection":[{"href":"https:\/\/sites.temple.edu\/aspl\/wp-json\/wp\/v2\/pages"}],"about":[{"href":"https:\/\/sites.temple.edu\/aspl\/wp-json\/wp\/v2\/types\/page"}],"author":[{"embeddable":true,"href":"https:\/\/sites.temple.edu\/aspl\/wp-json\/wp\/v2\/users\/7519"}],"replies":[{"embeddable":true,"href":"https:\/\/sites.temple.edu\/aspl\/wp-json\/wp\/v2\/comments?post=19"}],"version-history":[{"count":0,"href":"https:\/\/sites.temple.edu\/aspl\/wp-json\/wp\/v2\/pages\/19\/revisions"}],"wp:attachment":[{"href":"https:\/\/sites.temple.edu\/aspl\/wp-json\/wp\/v2\/media?parent=19"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}
\nFunded by National Science Foundation (NSF)<\/span><\/p>\n
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\nFunded by\u00a0Air Force Research Laboratory (AFRL)<\/span><\/p>\n
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\n<\/strong>Funded by Office of Naval Research (ONR)<\/span><\/span><\/p>\n
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\n<\/strong>Funded by Office of Naval Research (ONR)<\/p>\n
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\n<\/strong>Funded by Qatar National Research Fund (QNRF)<\/p>\n
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\nFunded by National Science Foundation<\/span><\/p>\n
\nFunded by Air Force Research Laboratory<\/span><\/p>\n
\nFunded by Defense Advanced Research Projects Agency<\/span><\/p>\n
\nFunded by Office of Naval Research<\/span><\/p>\n
\nFunded by Office of Naval Research<\/span><\/p>\n
\n<\/strong>Funded by Naval Surface Warfare Center<\/span><\/span><\/p>\n
\nFunded by Ben Franklin Technology Partners<\/span><\/p>\n
\nFunded by Cellnet+Hunt<\/span><\/p>\n","protected":false},"excerpt":{"rendered":"