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.
Robert G. Lindgren,
Daniel D. Weston,
"Likelihood interpolation for peak detection", Proc. SPIE 2235, Signal and Data Processing of Small Targets 1994, (6 July 1994); doi: 10.1117/12.179086; https://doi.org/10.1117/12.179086