Sigma-Point Filter-Based Integrated Navigation System
OHSU # 0786
The Wan-Merwe Sigma-Point Kalman Filter (SPKF) is an integrated navigational system that uses nonlinear recursive Bayesian Interference to improve navigational capablities. While improving software for unmanned vehicles, Eric Wan and Rudolph van der Merwe at Oregon Graduate Institute School of Science & Engineering at OHSU developed an improved method for navigation, feedback control, and fault detection applicable to unmanned and manned vehicles. The potential applications include the navigational software in aircraft, helicopters, missiles, cars, trucks, underwater vehicles, and more. This software could also be used to track people or objects.
USA Today reports that the U.S. military, encouraged by the success of satellite-guided bombs and unmanned spy planes, plans to spend $10 billion between now and 2010 on unmanned vehicles. Small, unmanned aerial vehicles represent one such application. Currently, the internal monitoring unit and software for small unmanned aerial vehicles cost approximately $10,000-$15,000, and usually is the most expensive piece on the vehicle. With the thousands of unmanned vehicles to be built in the next decade for the military, the market for this technology will continue to grow. Military aircraft search and navigation instruments are also a large but steadily growing market with projected 2005 revenues of $39.7 billion, up 14.7% from 2004 revenues of $34.6 billion. Missiles are also a substantial source of revenue for defense contractors at $14.8 billion, with variable growth depending upon the current world political situation. The market for navigation systems is rapidly growing driven by a diversity of applications. Allied Business Intelligence predicts that the global GPS market will rise above $21.5 billion by 2008. Consumer applications are the fastest growing segment.
The invention consistently outperforms the current standard, Extended Kalman Filter (EKF) by offering more accurate accounts for nonlinearities, providing exact modeling of asynchronous and lagged sensor updates, and handling the same computational load while using less expensive, less sensitive filters to get the same result. This translates into a 25% reduction in production costs.
Potential opportunities for this technology include companies engaged in navigational software for aircraft, helicopters, missiles, cars, trucks and underwater vehicles. According to the December 2002 DOD UAV Roadmap, the development cycles of major planned unmanned aerial vehicles are set to begin early stage development in 2005 through 2010. Therefore, the SPKF has a critical market window to convince the developers to use the SPKF in the products currently in development which will be manufactured for years to come.
Dr. Wan received his BS, MS, and Ph.D. in Electrical Engineering from Stanford University. His research is in algorithms and architecture for adaptive signal processing and machine learning. He has ongoing projects in autonomous unmanned aerial vehicles, estimation and probabilistic interference, integrated navigation systems, time series prediction and modeling, and speech enhancement. He holds several patents in adaptive signal processing and has authored over 50 technical papers in the field.
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