Title :
Track Detection of Low Observable Targets Using a Motion Model
Author :
Park, J. Daniel ; Doherty, John F.
Author_Institution :
Appl. Res. Lab., Pennsylvania State Univ., State College, PA, USA
fDate :
7/7/1905 12:00:00 AM
Abstract :
A method for detecting a low observable target track using an acceleration-based overall motion model is proposed. Unlike the existing track-before-detect methods that are based on sequential state updates, this method computes integrated echo energy for the entire hypothesized motion. The detection and the estimation of the track are made simultaneously using the batch processing approach. A comparison of track detection probability shows higher performance against low observable targets. Using a motion similarity metric and motion model homogeneity, a performance prediction model is derived and compared with the simulation results.
Keywords :
probability; signal processing; target tracking; batch processing approach; hypothesized motion; integrated echo energy; low observable targets; motion model; sequential state updates; track before detect methods; track detection probability; Batch processing; Hidden Markov models; Marine vehicles; Motion control; Tracking; Batch processing; Detection; Hidden Markov model; Low observable target; Marine vehicle; Motion model; Track before detect; Tracking; Weak target; batch processing; detection; hidden Markov model; low observable target; marine vehicle; motion model; track before detect; weak target;
Journal_Title :
Access, IEEE
DOI :
10.1109/ACCESS.2015.2471935
