Tracking correlated, simultaneously evolving target populations

Ronald Mahler

doi:10.1117/12.2224640

17 May 2016 Tracking correlated, simultaneously evolving target populations

Ronald Mahler

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

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