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| Content Provider | IEEE Xplore Digital Library |
|---|---|
| Author | Tong Jun Shan Gan-lin |
| Copyright Year | 2011 |
| Description | Author affiliation: Dept. of Optical and Electronic Engineering, College of Mechanical Engineering, Shijiazhuang 050003, China (Tong Jun; Shan Gan-lin) |
| Abstract | This paper presents a novel sensor selection algorithm for optimal allocation of target tracking resources, based on the interacting multiple model modified kalman filter. The algorithm can be easily calculated and it is possible to include sensors with a probability of detection pd <1. The sensor selection measure function is the minimum trace of covariance matrix. The performance of the sensor selection algorithm is studied for single sensor and sensor collocation. And simulation shows the method is effective and feasible. |
| Starting Page | 532 |
| Ending Page | 535 |
| File Size | 240674 |
| Page Count | 4 |
| File Format | |
| ISBN | 9781424480364 |
| e-ISBN | 9781424480395 |
| DOI | 10.1109/ICEICE.2011.5777375 |
| Language | English |
| Publisher | Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
| Publisher Date | 2011-04-15 |
| Publisher Place | China |
| Access Restriction | Subscribed |
| Rights Holder | Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
| Subject Keyword | Trace Target tracking Radar tracking Covariance matrix Mathematical model Kalman filters Multi-sensor management IMMMKF Optimization Sensor selection Measure function |
| Content Type | Text |
| Resource Type | Article |
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