DocumentCode :
3117090
Title :
Collaborative Sensor Registration without a Priori Association
Author :
Xi Liu ; Ze-Min Wu ; Hai-Yan Liu
Author_Institution :
Coll. of Commun. Eng., PLA Univ. of Sci. & Technol., Nanjing, China
fYear :
2013
fDate :
11-13 Dec. 2013
Firstpage :
72
Lastpage :
77
Abstract :
Sensor registration is an important prerequisite for successful multi-sensor data fusion. In this paper, we consider a cooperative sensor registration scenario that the Precise Location Messages (PLM) can be received by the tracker periodically from cooperative targets through wireless data link and utilized to estimate sensor systematic biases. A 2-D sensor registration algorithm is presented to jointly estimate the site location bias and the measurement bias without a priori knowledge of track-to-track association. At first, a point set is obtained by mapping all possible pairs of sensor and PLM measurements. Next, a credit function is defined as the arithmetic mean of the likelihood function of these points. Since the registration biases can be estimated by finding the maximum credit point, a two-step searching algorithm is proposed to jointly estimate location and measurement biases. Its statistical performance is compared to the hybrid Cramér-Rao lower bound (HCRLB).
Keywords :
cooperative communication; maximum likelihood estimation; sensor fusion; target tracking; wireless channels; 2D sensor registration; PLM measurements; arithmetic mean; collaborative sensor registration; cooperative sensor registration; cooperative targets; credit function; credit point; likelihood function; measurement bias; multisensor data fusion; precise location messages; registration bias; site location bias; track-to-track association; wireless data link; Algorithm design and analysis; Estimation; Position measurement; Radar tracking; Target tracking; Time measurement; Vectors; HCRLB; bias estimation; data fusion; data link; multi-target tracking; sensor registration;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Mobile Ad-hoc and Sensor Networks (MSN), 2013 IEEE Ninth International Conference on
Conference_Location :
Dalian
Print_ISBN :
978-0-7695-5159-3
Type :
conf
DOI :
10.1109/MSN.2013.42
Filename :
6726311
Link To Document :
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