Impulse optimization for data association

Matthew Travers*, Todd Murphey, Lucy Pao

*Corresponding author for this work

Research output: Chapter in Book/Report/Conference proceedingConference contribution

4 Scopus citations

Abstract

This paper presents a new method that addresses measurement origin uncertainty. Measurement origin uncertainty occurs when the object a measurement originated from is not clear. The systems considered contain multiple bodies which are dynamically indistinguishable other than initial conditions. Each measurement originates from one of the bodies in the system. In the past, recursive data association methods have been used to address problems of this nature. A new technique is presented which treats the measurement association problem as a batch post-processing problem. Reformulating the problem as such, it is possible to transform the data association problem into a trajectory optimization problem. From this point of view it is then possible to solve the measurement association problem using first- and second-order optimization algorithms that rely on having first- and second-order derivatives for cost functions that depend on impulsive trajectories.

Original languageEnglish (US)
Title of host publication2010 49th IEEE Conference on Decision and Control, CDC 2010
Pages2204-2209
Number of pages6
DOIs
StatePublished - 2010
Event2010 49th IEEE Conference on Decision and Control, CDC 2010 - Atlanta, GA, United States
Duration: Dec 15 2010Dec 17 2010

Publication series

NameProceedings of the IEEE Conference on Decision and Control
ISSN (Print)0191-2216

Other

Other2010 49th IEEE Conference on Decision and Control, CDC 2010
CountryUnited States
CityAtlanta, GA
Period12/15/1012/17/10

ASJC Scopus subject areas

  • Control and Systems Engineering
  • Modeling and Simulation
  • Control and Optimization

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