Detection and tracking of dim targets in heavy clutter environments is a daunting theoretical and practical problem. Application of the recently developed Background Agnostic Cardinalized Probability Hypothesis Density (BA-CPHD) filter provides a very promising approach that adequately addresses all the complexities and the nonlinear nature of this problem. In this paper, we present analysis, derivation, development, and application of a BA-CPHD implementation for tracking dim ballistic targets in environments with a range of unknown clutter rates, unknown clutter distribution, and unknown target probability of detection. The effectiveness and accuracy of the implemented algorithms are assessed and evaluated. Results that evaluate and also demonstrate the specific merits of the proposed approach are presented.

Date Published: 23 May 2013
PDF: 15 pages
Proc. SPIE 8745, Signal Processing, Sensor Fusion, and Target Recognition XXII, 87450C (23 May 2013); doi: 10.1117/12.2017994

Published in SPIE Proceedings Vol. 8745:
Signal Processing, Sensor Fusion, and Target Recognition XXII
Ivan Kadar, Editor(s)