DocumentCode
3421684
Title
Multiple target track-before-detect in compound Gaussian clutter
Author
Ebenezer, Samuel P. ; Papandreou-Suppappola, Antonia
Author_Institution
Sch. of Electr., Arizona State Univ., Tempe, AZ, USA
fYear
2015
fDate
19-24 April 2015
Firstpage
2539
Lastpage
2543
Abstract
In this paper, we extend the multiple transition mode track- before-detect (TBD) algorithm to track multiple low observable targets in compound Gaussian sea clutter. The proposed TBD framework uses the un-thresholded fast time radar measurements to track multiple targets in low signal-to-clutter ratios (SCRs). The TBD is implemented using particle filtering (PF), and we derive the generalized likelihood ratio needed to update the particle weights. The maximum likelihood estimate of the texture and the covariance matrix of the speckle are also derived and implemented using a fixed point algorithm. The tracking performance of the proposed algorithm is investigated using three low observable targets that enter and leave the field of view (FOV) at different time steps and under varying environmental conditions.
Keywords
Gaussian processes; covariance matrices; maximum likelihood estimation; object detection; particle filtering (numerical methods); radar clutter; radar detection; radar signal processing; radar tracking; target tracking; TBD algorithm; compound Gaussian sea clutter; field-of-view; fixed point algorithm; generalized likelihood ratio; low signal-to-clutter ratios; maximum likelihood texture estimate; multiple low observable target tracking; multiple target track-before-detect; multiple transition mode track-before-detect algorithm; particle filtering; speckle covariance matrix; unthresholded fast time radar measurements; Maximum likelihood estimation; Propagation delay; Scattering; Tracking;
fLanguage
English
Publisher
ieee
Conference_Titel
Acoustics, Speech and Signal Processing (ICASSP), 2015 IEEE International Conference on
Conference_Location
South Brisbane, QLD
Type
conf
DOI
10.1109/ICASSP.2015.7178429
Filename
7178429
Link To Document