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| Content Provider | IEEE Xplore Digital Library | 
|---|---|
| Author | Rong Yang Gee Wah Ng Bar-Shalom, Y. | 
| Copyright Year | 2013 | 
| Description | Author affiliation: Dept. of ECE, Univ. of Connecticut, Storrs, CT, USA (Bar-Shalom, Y.) || DSO Nat. Labs., Singapore, Singapore (Rong Yang; Gee Wah Ng) | 
| Abstract | It is known that using two passive sensors that provide bearings-only information cannot eliminate false intersections in a multi-target environment, and results in ghost tracks. In this paper, we propose a tracking/fusion and deghosting method using two stationary acoustic sensors. The existing approaches for bearings-only information require the number of sensors to be greater than or equal to three. The method proposed in this paper makes target tracking possible in a two-sensor system through making use of frequency information. This method generates tentative tracks from all possible bearing track combinations, and distinguishes target tracks from ghost tracks using a 2-D assignment algorithm. Tentative tracks are initiated using an iterated Least Squares (LS) algorithm, and updated by an Unscented Kalman Filter (UKF) based on Doppler-Bearing Tracking (DBT) approach. The likelihood ratios of tentative tracks, which are computed based on track innovation probability density functions, are assigned as costs in the 2-D assignment algorithm. Simulation tests have been conducted to validate the effectiveness of the proposed method. | 
| Starting Page | 1784 | 
| Ending Page | 1790 | 
| File Size | 1436436 | 
| Page Count | 7 | 
| File Format | |
| ISBN | 9786058631113 | 
| e-ISBN | 9781479902842 | 
| Language | English | 
| Publisher | Institute of Electrical and Electronics Engineers, Inc. (IEEE) | 
| Publisher Date | 2013-07-09 | 
| Publisher Place | Turkey | 
| Access Restriction | Subscribed | 
| Rights Holder | ISIF ( Intl Society of Information Fusi | 
| Subject Keyword | Kalman filters Measurement Dopplier-bearing tracking Deghosting passive tracking | 
| Content Type | Text | 
| Resource Type | Article | 
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