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Payman Arabshahi

Principal Engineer

Associate Professor, Electrical Engineering





Research Interests

Sensor Networks, Adaptive Signal Processing, Digital Communications, Wireless Networking, Biological Computing, and Distributed Intelligent Systems


Payman Arabshahi is a senior research scientist with the University of Washington's Applied Physics Laboratory, and Associate Professor of Electrical Engineering at the UW. From 1994-1996 he served on the faculty of the Electrical and Computer Engineering Department at the University of Alabama in Huntsville. From 1997-2006 he was on the senior technical staff of NASA's Jet Propulsion Laboratory, in the Communications Architectures and Research Section. While at JPL he also served as affiliate graduate faculty at the Department of Electrical Engineering at Caltech, where he taught the three-course graduate sequence on digital communications.

He has a strong, 12-year track record of successful design, implementation, and management of large, complex technology projects; building and maintaining R&D relationships with academia, government, and industry; and strategic planning and technology roadmapping. His research interests are in wireless communications and networking, sensor networks, signal processing, data mining and search, and biologically inspired systems.


B.S.E Electrical Engineering, University of Alabama - Huntsville, 1988

M.S. Electrical Engineering, University of Washington - Seattle, 1994

Ph.D. Electrical Engineering, University of Washington - Seattle, 1994


2000-present and while at APL-UW

Puget Sound underwater networking TestBed

Hurst, S., X. Xie, S. Ashrafi, S. Roy, and P. Arabshahi, "Puget Sound underwater networking TestBed," Proc., OCEANS 2014, 14-19 September 2014, St. John's, Newfoundland, doi:10.1109/OCEANS.2014.7003119 (IEEE, 2014).

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14 Sep 2014

Underwater communications is the necessary enabler for several next-generation engineering and scientific applications such as distributed undersea monitoring, persistent surveillance, and long-range high fidelity navigation. Underwater acoustic channels (characterized by long propagation delays and small coherence bandwidths) continue to present significant challenges and reliable networked communications remains a future goal. To this end, a joint collaboration between a number of partner universities (Ocean-TUNE project, funded by the U.S. National Science Foundation), seeks to implement an underwater networking testbed to conduct field tests for better understanding of the underwater acoustic channel characteristics. A key feature of the deployment is a new multicarrier (OFDM) modem - a first for such a testbed to the best of our knowledge - complemented with a software driven protocol stack implementation that allows adaptation to acoustic channel characteristics. In this paper, we first provide an architectural overview of our network testbed, followed by initial results from preliminary testing in Lake Union (Puget Sound), WA. We conclude the paper with a brief description of future plans.

A virtual ocean observatory for climate and ocean science: Synergistic applications from SWOT and XOVWMM

Arabshahi, P., B.M. Howe, Y. Chao, S. Businger, and S. Chien, "A virtual ocean observatory for climate and ocean science: Synergistic applications from SWOT and XOVWMM," 2010 Fall Meeting, AGU, San Francisco, CA, 13-17 December, abstract IN41D-07.

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13 Dec 2010

We present a virtual ocean observatory (VOO) that supports climate and ocean science as addressed in the NRC decadal survey. The VOO is composed of an autonomous software system, in-situ and space-based sensing assets, data sets, and interfaces to ocean and atmosphere models.

The purpose of this observatory and its output data products are: 1) to support SWOT mission planning, 2) to serve as a vanguard for fusing SWOT, XOVWM, and in-situ data sets through fusion of OSTM (SWOT proxy) and QuikSCAT (XOVWM proxy) data with in-situ data, and 3) to serve as a feed-forward platform for high-resolution measurements of ocean surface topography (OST) in island and coastal environments utilizing space-based and in-situ adaptive sampling. The VOO will enable models capable of simulating and estimating realistic oceanic processes and atmospheric forcing of the ocean in these environments. Such measurements are critical in understanding the oceans' effects on global climate.

The information systems innovations of the VOO are: 1. Development of an autonomous software platform for automated mission planning and combining science data products of QuikSCAT and OSTM with complementary in-situ data sets to deliver new data products. This software will present first-step demonstrations of technology that, once matured, will offer increased operational capability to SWOT by providing automated planning, and new science data sets using automated workflows. The future data sets to be integrated include those from SWOT and XOVWM. 2. A capstone demonstration of the effort utilizes the elements developed in (1) above to achieve adaptive in-situ sampling through feedback from space-based-assets via the SWOT simulator. This effort will directly contribute to orbit design during the experimental phase (first 6-9 months) of the SWOT mission by high resolution regional atmospheric and ocean modeling and sampling. It will also contribute to SWOT science via integration of in-situ data, QuikSCAT, and OSTM data sets, and models, thus serving as technology pathfinder for SWOT and XOVWM data fusion; and will contribute to SWOT operations via data fusion and mission planning technology.

The goals of our project are as follows: (a) Develop and test the VOO, including hardware, in-situ science platforms (Seagliders) and instruments, and two autonomous software modules: 1) automated data fusion/assimilation, and 2) automated planning technology; (b) Generate new data sets (OST data in the Hawaiian Islands region) from fusion of in-situ data with QuikSCAT and OSTM data; (c) Integrate data sets derived from the VOO into the SWOT simulator for improved SWOT mission planning; (d) Demonstrate via Hawaiian Islands region field experiments and simulation the operational capability of the VOO to generate improved hydrologic cycle/ocean science, in particular: mesoscale and submesoscale ocean circulation including velocities, vorticity, and stress measurements, that are important to the modeling of ocean currents, eddies and mixing.

A smart sensor web for ocean observation: Fixed and mobile platforms, integrated acoustics, satellites and predictive modeling

Howe, B.M., Y. Chao, P. Arabshahi, S. Roy, T. McGinnis, and A. Gray, "A smart sensor web for ocean observation: Fixed and mobile platforms, integrated acoustics, satellites and predictive modeling," IEEE J. Sel. Top. Appl. Earth Obs. Remote Sens., 3, 507-521, doi:10.1109/JSTARS.2010.2052022, 2010.

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1 Dec 2010

In many areas of Earth science, including climate change research and operational oceanography, there is a need for near real-time integration of data from heterogeneous and spatially distributed sensors, in particular in situ and space-based sensors. The data integration, as provided by a smart sensor web, enables numerous improvements, namely, (1) adaptive sampling for more efficient use of expensive space-based and in situ sensing assets, (2) higher fidelity information gathering from data sources through integration of complementary data sets, and (3) improved sensor calibration. Our ocean-observing smart sensor web presented herein is composed of both mobile and fixed underwater in situ ocean sensing assets and Earth Observing System satellite sensors providing larger-scale sensing.

An acoustic communications network forms a critical link in the web, facilitating adaptive sampling and calibration. We report on the development of various elements of this smart sensor web, including (a) a cable-connected mooring system with a profiler under real-time control with inductive battery charging; (b) a glider with integrated acoustic communications and broadband receiving capability; (c) an integrated acoustic navigation and communication network; (d) satellite sensor elements; and (e) a predictive model via the Regional Ocean Modeling System interacting with satellite sensor control.

More Publications

Acoustics Air-Sea Interaction & Remote Sensing Center for Environmental & Information Systems Center for Industrial & Medical Ultrasound Electronic & Photonic Systems Ocean Engineering Ocean Physics Polar Science Center