Censoring distributed nonlinear state estimates in radar networks

Armond S. Conte II; Ruixin Niu

doi:10.1117/12.2228924

13 May 2016 Censoring distributed nonlinear state estimates in radar networks

Armond S. Conte II, Ruixin Niu

Proceedings Volume 9838, Sensors and Systems for Space Applications IX; 98380F (2016) https://doi.org/10.1117/12.2228924
Event: SPIE Defense + Security, 2016, Baltimore, MD, United States

Abstract

In a distributed radar track fusion system, it is desired to limit the communication rate between the sensors and the central node to only the most relevant information available. One way to do this is to use some metric that judges quantity of new information available, in comparison to that which has already been provided. The J-Divergence is a symmetric metric, derived from the Kullback-Liebler divergence, which performs a comparison of the statistical distance between two probability distributions. For the comparison between new and old data, a large J-Divergence can represent the existence of new information, while a small J-Divergence represents the lack of new information. Previous work included an application where the J-Divergence was used to limit data for scenarios in which the primary state estimator was an Extended Kalman Filter and used only Gaussian approximations at the local sensors. This paper expands the range of estimators to particle filters in order to account for situations where censoring is desired to be applied to non-linear/non-Gaussian environments. A derivation of the J-Divergence between probability density functions (PDFs) which are approximated by particles is provided for use in a non-feedback fusion case. An example application is given involving a 2D radar tracking scenario using the J-Divergences of a particle filter with the Gaussian approximation and a particle filter with the approximated discrete prior/posterior PDFs.

Citation Download Citation

Armond S. Conte II and Ruixin Niu "Censoring distributed nonlinear state estimates in radar networks", Proc. SPIE 9838, Sensors and Systems for Space Applications IX, 98380F (13 May 2016); https://doi.org/10.1117/12.2228924

ACCESS THE FULL ARTICLE

INSTITUTIONAL
Select your institution to access the SPIE Digital Library.

SELECT YOUR INSTITUTION

PERSONAL
Sign in with your SPIE account to access your personal subscriptions or to use specific features such as save to my library, sign up for alerts, save searches, etc.

PERSONAL SIGN IN

No SPIE Account? Create one

PURCHASE THIS CONTENT

SUBSCRIBE TO DIGITAL LIBRARY

50 downloads per 1-year subscription

Members: $195

Non-members: $335 ADD TO CART

25 downloads per 1 - year subscription

Members: $145

Non-members: $250 ADD TO CART

PURCHASE SINGLE ARTICLE

Includes PDF, HTML & Video, when available