Sensor management algorithms must be capable of directing sensing resources preferentially to know or potential Targets of Interest (ToIs) having high tactical importance. In principle one could simply wait until accumulated information strongly suggests that particular targets are probable ToIs and then bias the allocation of sensor resources to those targets. However, such ad hoc techniques have inherent limitations. To avoid these limitations target preference must be incorporated into the fundamental statistical description of multisensor-multitarget problems. In this paper we show that finite-set statistics (FISST) has built-in mathematical tools for doing this, thereby allowing target preference to be incorporated into sensor management objective functions.

Date Published: 9 August 2004
PDF: 12 pages
Proc. SPIE 5429, Signal Processing, Sensor Fusion, and Target Recognition XIII, (9 August 2004); doi: 10.1117/12.544019

Published in SPIE Proceedings Vol. 5429:
Signal Processing, Sensor Fusion, and Target Recognition XIII
Ivan Kadar, Editor(s)