Sigma-Point Filter-Based Integrated Navigation System

Case ID:
0786
Web Published:
9/16/2020
Description:

Summary

This technique achieves for the navigational state of the system an estimation accuracy that is greater than that achievable with an extended Kalman filter-based probabilistic inference system.

Technology Overview

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 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 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. 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.

Licensing Opportunity
This technology is available for licensing.

Patent Information:
Category(s):
Software
For Information, Contact:
Arvin Paranjpe
Senior Technology Development Manager
Oregon Health & Science University
(503) 494-8200
paranjpe@ohsu.edu
Inventors:
Rudolph Van Der Merwe
Eric Wan
Simon Julier
Keywords:
Software
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