In this paper we present a likelihood technique for determining candidate target detections to pass to a tracker over successive temporal intervals. In a representative situation sensor data are available from each interval as matched-filter output sampled at discrete position-velocity state hypotheses. A likelihood ratio for an arbitrary target hypothesis from the continuous state domain can be constructed from the sampled filter output, and we seek local maxima in this likelihood-ratio field as the candidate detections. We obtain a readily implemented algorithm which closely follows this optimal prescription by limiting the sample points in the likelihood construction to the immediate vicinity of a discrete local maximum in the filter output.

Date Published: 6 July 1994
PDF: 12 pages
Proc. SPIE 2235, Signal and Data Processing of Small Targets 1994, (6 July 1994); doi: 10.1117/12.179086

Published in SPIE Proceedings Vol. 2235:
Signal and Data Processing of Small Targets 1994
Oliver E. Drummond, Editor(s)