Tracking correlated, simultaneously evolving target populations

Ronald  Mahler

doi:10.1117/12.2224640

17 May 2016 Tracking correlated, simultaneously evolving target populations

Ronald Mahler

Author Affiliations +

Proceedings Volume 9842, Signal Processing, Sensor/Information Fusion, and Target Recognition XXV; 98420C (2016) https://doi.org/10.1117/12.2224640
Event: SPIE Defense + Security, 2016, Baltimore, Maryland, United States

Abstract

Multisensor-multitarget tracking algorithms are typically based on numerous statistical independence assumptions. This paper is the fifth in a series aimed at weakening such assumptions. It addresses the statistics of correlated, simultaneously evolving multitarget populations. The correlation between two multitarget popula-tions is approximately modeled using bivariate i.i.d.c. (independent, identically distributed cluster) distributions. Based on this, a joint tracking filter for such populations is devised, in analogy with the cardinalized probability hypothesis density (CPHD) filter.

Citation Download Citation

Ronald Mahler, Ronald Mahler, } "Tracking correlated, simultaneously evolving target populations", Proc. SPIE 9842, Signal Processing, Sensor/Information Fusion, and Target Recognition XXV, 98420C (17 May 2016); doi: 10.1117/12.2224640; https://doi.org/10.1117/12.2224640

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