You have requested a machine translation of selected content from our databases. This functionality is provided solely for your convenience and is in no way intended to replace human translation. Neither SPIE nor the owners and publishers of the content make, and they explicitly disclaim, any express or implied representations or warranties of any kind, including, without limitation, representations and warranties as to the functionality of the translation feature or the accuracy or completeness of the translations.
Translations are not retained in our system. Your use of this feature and the translations is subject to all use restrictions contained in the Terms and Conditions of Use of the SPIE website.
23 May 2013Sensor selection for target localization in a network of proximity sensors and bearing sensors
The work considers sensor fusion in a heterogeneous network of proximity and bearings-only sensors for multiple target tracking. Specifically, various particle implementations of the probability hypothesis density filter are proposed that consider two different fusion strategies: 1) the traditional iterated-corrector approach, and 2) explicit fusion of the multitarget density. This work also investigates sensor type (proximity or bearings-only) selection via the Renyi entropy criteria. The simulation results demonstrate comparable localization performances for the two fusion methods, and they show that sensor type selection usually outperforms single sensor type performance.
Qiang Le andLance M. Kaplan
"Sensor selection for target localization in a network of proximity sensors and bearing sensors", Proc. SPIE 8745, Signal Processing, Sensor Fusion, and Target Recognition XXII, 874509 (23 May 2013); https://doi.org/10.1117/12.2017907
The alert did not successfully save. Please try again later.
Qiang Le, Lance M. Kaplan, "Sensor selection for target localization in a network of proximity sensors and bearing sensors," Proc. SPIE 8745, Signal Processing, Sensor Fusion, and Target Recognition XXII, 874509 (23 May 2013); https://doi.org/10.1117/12.2017907