Title :
A track-before-detect procedure for sparse data
Author :
Grossi, Emanuele ; Lops, Marco ; Venturino, Luca
Author_Institution :
DIEI, Univ. degli Studi di Cassino e del Lazio Meridionale, Cassino, Italy
Abstract :
In this paper, we consider the problem of detecting the presence of a prospective, moving target from a set of noisy measurements. We propose a two-steps approach: The first step discards unreliable measurements (i.e., those whose likelihood ratio falls below a preassigned threshold); The second step, instead, exploits the correlation among observations taken at different time instants and makes the final decision. A novel, computationally efficient, track-before-detect algorithm which exploits the sparse nature of the measurements is proposed, and experimental results to asses the algorithm performance are provided.
Keywords :
correlation methods; signal detection; target tracking; noisy measurement; observation correlation; preassigned threshold; prospective moving target; sparse data; track-before-detect procedure; unreliable measurements; Abstracts; Conferences; Signal to noise ratio; Silicon compounds;
Conference_Titel :
Statistical Signal Processing Workshop (SSP), 2012 IEEE
Conference_Location :
Ann Arbor, MI
Print_ISBN :
978-1-4673-0182-4
Electronic_ISBN :
pending
DOI :
10.1109/SSP.2012.6319818