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| Content Provider | IEEE Xplore Digital Library |
|---|---|
| Author | Deyun Zhou Hao Zhang Qian Pan Kun Zhang |
| Copyright Year | 2015 |
| Description | Author affiliation: Sch. of Electron. & Inf., Northwestern Polytech. Univ., Xi'an, China (Deyun Zhou; Hao Zhang; Qian Pan; Kun Zhang) |
| Abstract | In order to improve the deficiency of range information unmeasurable in passive location and high computational complexity in distributed fusion estimation, an improved range parameterized square root cubature information filter (RP-SRCIF) algorithm is proposed. The proposed algorithm adopts fully distributed fusion estimation structure, integrates square root cubature Kalman filter (SRCKF) algorithm, range parameterized method and information filter (IF) algorithm. SRCKF can ensure better numerical stability and higher estimation accuracy; the improved range parameterized method can provide good robustness for initial estimation range and better real-time performance than traditional range parameterized method; IF with fully distributed fusion estimation structure makes fusion estimation computation more simple and convenient. Simulation results indicate the RP-SRCIF algorithm is feasible and more effective when compared with other algorithms for multi-UAV cooperative passive location. |
| Starting Page | 1079 |
| Ending Page | 1084 |
| File Size | 300498 |
| Page Count | 6 |
| File Format | |
| e-ISBN | 9781467391047 |
| DOI | 10.1109/ICInfA.2015.7279447 |
| Language | English |
| Publisher | Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
| Publisher Date | 2015-08-08 |
| Publisher Place | China |
| Access Restriction | Subscribed |
| Rights Holder | Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
| Subject Keyword | square root cubature information filter Accuracy Filtering algorithms Information filters distributed fusion estimation Kalman filters range parameterized Covariance matrices State estimation passive location |
| Content Type | Text |
| Resource Type | Article |
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