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Payman Arabshahi

Principal Engineer

Associate Professor, Electrical Engineering

Email

payman@apl.washington.edu

Phone

206-221-6990

Research Interests

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

Biosketch

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.

Education

B.S. Engineering, University of Alabama Huntsville, 1988

Ph.D., University of Washington, 1994

Publications

2000-present and while at APL-UW

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.

A smart sensor web for ocean observation: System design, modeling, and optimization

Arabshahi, P., B.M. Howe, Y. Chao, S. Roy, T. McGinnis, and A. Gray, "A smart sensor web for ocean observation: System design, modeling, and optimization," In Proceedings, NASA Earth Science Technology Forum, 22-24 June, Arlington, VA, 17 pp., 2010.

More Info

22 Jun 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 (EOS) 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 the 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 (ROMS) interacting with satellite sensor control.

More Publications

Symbol by symbol Doppler rate estimation for highly mobile underwater OFDM

Parrish, N., S. Roy, and P. Arabshahi, "Symbol by symbol Doppler rate estimation for highly mobile underwater OFDM," In Proceedings, Fourth ACM Workshop on Underwater Networks, 3 November, Berkeley, CA (Association for Computing Machinery, 2009).

3 Nov 2009

Tradeoffs and design choices for a software defined acoustic modem: A case study

Gray, A., P. Arabshahi, S. Roy, N. Jensen, L. Tracy, N. Parrish, and C. Hsieh, "Tradeoffs and design choices for a software defined acoustic modem: A case study," In Proceedings, Fourth ACM Workshop on Underwater Networks, 3 November, Berkeley, CA (Association for Computing Machinery, 2009).

3 Nov 2009

On feature based automatic classification of single and multitone signals

Das, A.K., P. Arabshahi, T. Wen, and W. Su, "On feature based automatic classification of single and multitone signals," In Proceedings, Ninth IASTED International Conference on Wireless and Optical Communications, 6-8 July, Banff, Alberta (Acta Press, 2009).

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6 Jul 2009

We consider the problem of feature based automatic classification of single and multitone signals. Our objective is to extend existing blind demodulation techniques to multitone waveforms such as MIL-STD-188-110B (Appendix B) and OFDM, developing a capability to identify signal types based on short data records, and maintaining robustness to channel effects. In this paper, we report on the first phase of our approach, namely, building a coarse classifier for a range of single tone and multitone signals. Among the features considered by the coarse classifier are those based on trigonometric moments and higher order statistics of the instantaneous frequencies of the received signal. No a priori information is assumed on the part of the received signal. The received signal of interest has not been previously observed; it is not part of a library of known signals; and no automated classifier has been built for it. Extensive simulation results based on real world signals are presented demonstrating the feasibility of the above features for automatic classification purposes of single and multitone signals.

Impact of bottom type on OFDM underwater communications

Parrish, N., S. Roy, and P. Arabshahi, "Impact of bottom type on OFDM underwater communications," J. Acoust. Soc. Am., 125, 2580, 2009.

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1 Apr 2009

The impact of bottom sediment type in relation to acoustic communications via orthogonal frequency division multiplexing (OFDM) is shown via experimental results and simulation. Experimental data from Lake Washington, Seattle with a "silty clay" bottom show that the multipath delay spread is longer at 250 m than at 4 km. This results in better OFDM performance at the longer range. Similar results are shown via simulation using a channel model developed from Bellhop, a Gaussian Ray tracing tool [M. Porter, "Bellhop Gaussian beam/finite element beam code," Available: http://oalib.hlsresearch.com/Rays/index.html (2007)]. Through simulation, results are also shown under similar conditions to the experiment but with varying bottom type. The results show that the performance of OFDM signaling is dependent on the bottom type as well as specific source/receiver geometry.

A smart sensor web for ocean observation: Integrated acoustics, satellite networking, and predictive modeling

Arabshahi, P., Y. Chao, S. Chien, A. Gray, B.M. Howe, and S. Roy, "A smart sensor web for ocean observation: Integrated acoustics, satellite networking, and predictive modeling," Eos, Trans. AGU, 89, Fall Meet. Suppl., Abstract IN23D-02, 2008.

More Info

1 Dec 2008

In many areas of Earth science, including climate change research, 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 sensing assets, 2) higher fidelity information gathering from data sources through integration of complementary data sets, and 3) improved sensor calibration.

The specific purpose of the smart sensor web development presented here is to provide for adaptive sampling and calibration of space-based data via in-situ data. 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 (EOS) satellite sensors providing larger-scale sensing. An acoustic communications network forms a critical link in the web between the in-situ and space-based sensors and facilitates adaptive sampling and calibration.

After an overview of primary design challenges, we report on the development of various elements of the smart sensor web. These include (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) satellite sensor elements; (d) an integrated acoustic navigation and communication network; and (e) a predictive model via the Regional Ocean Modeling System (ROMS). Results from field experiments, including an upcoming one in Monterey Bay (October 2008) using live data from NASA's EO-1 mission in a semi closed-loop system, together with ocean models from ROMS, are described. Plans for future adaptive sampling demonstrations using the smart sensor web are also presented.

Autonomous mission design and data fusion: Laying the groundwork for decadal mission swath altimetry and ocean vector winds

Howe, B.M., P. Arabshahi, S. Businger, Y. Chao, S. Chien, and A. Gray, "Autonomous mission design and data fusion: Laying the groundwork for decadal mission swath altimetry and ocean vector winds," Eos Trans. AGU, 89, Fall Meet. Suppl., Abstract IN31A-1122, 2008

More Info

1 Dec 2008

In the coming decade, the autonomous coordinated utilization of space, atmospheric, surface, and ocean assets, sensor webs, and data will assume more importance, as systems become more complex and tightly integrated, and as the need to know our environment with ever greater accuracy and precision becomes more acute. We have begun to address this issue with a prototype virtual ocean observatory that includes present and future NASA satellite missions (Jason-2 and QuikSCAT; and SWOT [swath altimetry] and XOVWM [ocean vector winds], respectively); atmosphere and ocean models (WRF/LAPS and ROMS, respectively); and in-situ sensors and platforms (underwater gliders).

In our prototype system, the goal is to develop the architecture and implementation of the necessary software modules (e.g., automated data fusion/assimilation, and automated planning technology) to achieve adaptive in-situ sampling through feedback from space-based-assets (in this case via the SWOT simulator) thereby contributing to the orbit design during the first, experimental phase (~6-9 months) of the SWOT mission. This work is one step in the process of infusing technology into the development pipeline.

System design considerations for undersea networks: Link and multiple access protocols

Parrish, N., L. Tracy, S. Roy, W.L.J. Fox, and P. Arabshahi, "System design considerations for undersea networks: Link and multiple access protocols," IEEE J. Sel. Areas Commun., 26, 1720-1730, doi:10.1109/JSAC.2008.081211, 2008.

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1 Dec 2008

We address several inter-related aspects of underwater network design within the context of a cross-layer approach. We first highlight the impact of key characteristics of the acoustic propagation medium on the choice of link layer parameters; in turn, the consequences of these choices on design of a suitable MAC protocol and its performance are investigated.

Specifically, the paper makes contributions on the following fronts: a) Based on accepted acoustic channel models, the pointto- point (link) capacity is numerically calculated, quantifying sensitivities to factors such as the sound speed profile, power spectral density of the (colored) additive background noise and the impact of boundary (surface) conditions for the acoustic channel; b) It provides an analysis of the Micromodem-like linklayer based on FH-FSK modulation; and finally c) it undertakes performance evaluation of a simple MAC protocol based on ALOHA with Random Backoff, that is shown to be particularly suitable for small underwater networks.

OFDM in underwater channels

Parish, N., S. Roy, and P. Arabshahi, "OFDM in underwater channels," Proceedings, 3rd ACM Workshop on Underwater Networks, 15 September, San Francisco, CA, 2pp. (2008).

16 Sep 2008

A smart sensor web for ocean observation: Integrated acoustics, satellite networking, and predictive modeling

Howe, B.M., N. Parrish, L. Tracy, A. Gray, Y. Chao, T. McGinnis, P. Arabshahi, and S. Roy, "A smart sensor web for ocean observation: Integrated acoustics, satellite networking, and predictive modeling," Proceedings, NASA Earth Science Technology Conference, 24-26 June, College Park, MD, 10 pp. (2008)

25 Jun 2008

Underwater acoustic communications performance modeling in support of ad hoc network design

Fox, W.L.J., P. Arabshahi, S. Roy, and N. Parrish, "Underwater acoustic communications performance modeling in support of ad hoc network design," Oceans 2007, 29 September - 4 October, Vancouver, BC, 1-5 (IEEE: Piscataway, NJ, 2007).

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29 Oct 2007

This paper discusses a methodology for predicting underwater acoustic communications performance using high fidelity acoustic time series simulation and acoustic modem processing emulation. Multiple source/receiver combinations can be simultaneously simulated, so that aspects of a complete underwater network can be studied. Here, the fundamental modeling and emulation capability will be described, with examples of the propagation modeling, time series simulation, and modem processing over multiple realizations of example communications channels. The results show the dependence of source and receiver location in the water column with respect to the sound speed profile on communications performance. The utility of such simulations for ad hoc network design in the presence of moving communications nodes will be discussed.

A smart sensor web for ocean observation: System design, architecture, and performance

Howe, B.M., P. Arabshahi, W.L.J. Fox, S. Roy, T. McGinnis, M.L. Boyd, A. Gray, and Y. Chao, "A smart sensor web for ocean observation: System design, architecture, and performance," Proc., NASA Science Technology Conference, 19-21 June, College Park, MD (2007).

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19 Jun 2007

Much of the cost and effort of new ocean observatories will be in the infrastructure that directly supports sensors, such as moorings and mobile platforms, which in turn connect to a "backbone" infrastructure. Four elements of this sensor network infrastructure are in various stages of development, presented here: (1) a cable-connected mooring system with a profiler under real-time control with inductive battery charging; (2) a glider with integrated acoustic communications and broadband receiving capability; (3) an integrated acoustic navigation and communication network with tomography on various scales; and (4) a satellite uplink and feedback system. We also present initial results from field experiments, as well as from studies on communication performance of the underwater sensor network system under development.

Wide area ocean networks: Architecture and System Design Considerations

Roy, S., P. Arabshahi, D. Rouseff, and W.L.J. Fox, "Wide area ocean networks: Architecture and System Design Considerations," Proceedings, First ACM International Workshop on Underwater Networks, 25 September, Los Angeles, CA, 25-32 (2006).

25 Sep 2006

Inventions

A Collaborative Networked Expert System for Assistive Robotic Surgery

Record of Invention Number: 46781

Payman Arabshahi

Disclosure

2 Jan 2014

Methods for Underwater Haptic Rendering Using Non-contact Sensors

Record of Invention Number: 46396

Wei-Chih Wang, Fredrik Ryden, Payman Arabshahi, Andy Stewart, Howard Chizeck

Disclosure

7 Feb 2013

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
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