DocumentCode :
1053777
Title :
Bearings-only target motion analysis with acoustic propagation models of uncertain fidelity
Author :
Streit, Roy L. ; Walsh, Michael J.
Author_Institution :
Naval Undersea Warfare Center, Newport, RI, USA
Volume :
38
Issue :
4
fYear :
2002
fDate :
10/1/2002 12:00:00 AM
Firstpage :
1122
Lastpage :
1137
Abstract :
The augmented bearings-only target motion analysis (TMA) problem arises when the bearing measurements of the classical bearings-only TMA problem are augmented with received signal-to-noise ratio (SNR) measurements. A combined acoustic propagation and sensor (CAPS) performance prediction model specifying the conditional density of the SNR measurements is assumed given; however, mismatch may exist between the CAPS model and the real world. We present a novel "missing data" formulation of the augmented bearings-only TMA problem using an empirical maximum a posteriori (EMAP) method for target parameter estimation, and show that it provides a natural and straightforward technique for mitigating CAPS model mismatch. The EMAP approach leads to an iteratively reweighted, linear least-squares algorithm for solving both the augmented bearings-only TMA problem and the classical (nonaugmented) bearings-only TMA problem. Examples are provided.
Keywords :
interference (signal); observability; parameter estimation; prediction theory; probability; sonar signal processing; state estimation; underwater acoustic propagation; CAPS model mismatch; CAPS performance prediction model; EMAP method; augmented bearings-only TMA problem; bearings-only target motion analysis; combined acoustic propagation/sensor model; empirical maximum a posteriori method; iteratively reweighted linear LS algorithm; linear least-squares algorithm; passive sonar target motion analysis problem; probability density function; received SNR measurements; signal-to-noise ratio measurements; target parameter estimation; Acoustic measurements; Acoustic propagation; Acoustic sensors; Density measurement; Iterative algorithms; Motion analysis; Motion measurement; Parameter estimation; Predictive models; Signal to noise ratio;
fLanguage :
English
Journal_Title :
Aerospace and Electronic Systems, IEEE Transactions on
Publisher :
ieee
ISSN :
0018-9251
Type :
jour
DOI :
10.1109/TAES.2002.1145738
Filename :
1145738
Link To Document :
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