Title :
Hybrid multi-Bernoulli and CPHD filters for superpositional sensors
Author :
Nannuru, Santosh ; Coates, Mark
Author_Institution :
Dept. of Electr. & Comput. Eng., McGill Univ., Montreal, QC, Canada
Abstract :
In this paper we present an approximate multi-Bernoulli filter and an approximate hybrid multi-Bernoulli cardinalized probability hypothesis density filter for superpositional sensors. The approximate-filter equations are derived by assuming that the predicted and posterior multitarget states have the same form and propagating the probability hypothesis density function for each independent component of the multitarget state. We examine the performance of the filters in a simulated acoustic sensor network and a radio frequency tomography application.
Keywords :
acoustic communication (telecommunication); acoustic transducers; approximation theory; independent component analysis; probability; wireless sensor networks; CPHD filter; approximate-filter equation; cardinalized probability; hybrid multiBernoulli filter; independent component analysis; posterior multitarget state; predicted multitarget state; probability hypothesis density filter function; radiofrequency tomography application; simulated acoustic sensor network; superpositional sensor; Approximation methods; Computational modeling; Density functional theory; Mathematical model; Sensor phenomena and characterization; Target tracking;
Journal_Title :
Aerospace and Electronic Systems, IEEE Transactions on
DOI :
10.1109/TAES.2015.140351