A distributed general multi-sensor cardinalized probability hypothesis density (CPHD) filter for sensor networks

S. Datta Gupta; S. Nannuru; M. Coates; M. Rabbat

doi:10.1117/12.2177502

21 May 2015 A distributed general multi-sensor cardinalized probability hypothesis density (CPHD) filter for sensor networks

S. Datta Gupta, S. Nannuru, M. Coates, M. Rabbat

Author Affiliations +

Proceedings Volume 9474, Signal Processing, Sensor/Information Fusion, and Target Recognition XXIV; 94740F (2015) https://doi.org/10.1117/12.2177502
Event: SPIE Defense + Security, 2015, Baltimore, MD, United States

Abstract

We develop a distributed cardinalized probability hypothesis density (CPHD) filter that can be deployed in a sensor network to process the measurements of multiple sensors that make conditionally independent measurements. In contrast to the majority of the related work, which involves performing local filter updates and then exchanging data to fuse the local intensity functions and cardinality distributions, we strive to approximate the update step that a centralized multi-sensor CPHD filter would perform.

Citation Download Citation

S. Datta Gupta, S. Nannuru, M. Coates, and M. Rabbat "A distributed general multi-sensor cardinalized probability hypothesis density (CPHD) filter for sensor networks", Proc. SPIE 9474, Signal Processing, Sensor/Information Fusion, and Target Recognition XXIV, 94740F (21 May 2015); https://doi.org/10.1117/12.2177502

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