Abstract
In this paper, two proposed Track Before Detect (TBD) algorithms for spawning targets on the basis of raw radar measurements are described. These algorithms are developed by using multi-model particle filter method. To improve the efficiency of particle filter a novel reduced order model is introduced. The algorithms are confirmed by using the simulation results and their performances are analyzed on the basis of the probability of target existence and Root Mean Square (RMS) estimation accuracy for very low Signal-to-Noise Ratio (SNR) targets.
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