DocumentCode
3416601
Title
Probabilistic multi-hypothesis tracking in a multi-sensor, multi-target environment
Author
Giannopoulos, Evangelos ; Streit, Roy ; Swaszek, Peter
Author_Institution
Naval Undersea Warfare Center, Newport, RI, USA
fYear
1996
fDate
21-22 Nov 1996
Firstpage
184
Lastpage
189
Abstract
In this paper the probabilistic multi-hypothesis tracking (PMHT) algorithm, a data fusion algorithm developed by Streit and Luginbuhl (1995), is extended to handle multiple sensors. In addition, performance of multi-target tracking algorithms is discussed in terms of the Cramer-Rao lower bound (CRLB) criterion that is computed from the marginalized measurement PMHT log-likelihood function. Simulation results for one set of scenarios are presented and an initialization procedure for the bearings only measurement case is recommended
Keywords
probability; sensor fusion; target tracking; tracking; Cramer-Rao lower bound criterion; bearings only measurement; log-likelihood function; marginalized measurement; multi-sensor multi-target environment; probabilistic multi-hypothesis tracking; Computational modeling; Density measurement; Least squares methods; Measurement standards; Random variables; Sensor fusion; State estimation; Surveillance; Target tracking; Time measurement;
fLanguage
English
Publisher
ieee
Conference_Titel
Data Fusion Symposium, 1996. ADFS '96., First Australian
Conference_Location
Adelaide, SA
Print_ISBN
0-7803-3601-1
Type
conf
DOI
10.1109/ADFS.1996.581104
Filename
581104
Link To Document