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Improved Multi-target Tracking Algorithm Based on Gaussian Mixture Particle PHD Filter
| Content Provider | Semantic Scholar |
|---|---|
| Author | Lin, Qing Liao, Dingan Zhan, Yongzhao Yang, Yaping Jiangsu, Zhenjiang Jiangsu, Nanjing |
| Copyright Year | 2015 |
| Abstract | The paper proposes Gaussian mixture particle probability hypothesis density filter(PHD) algorithm ,which can effectively solve the problem that the object number is changing or unknown, based on particle PHD filter. This algorithm calculates the object number and state by recursive procedure, avoiding the uncertainty of target state estimation caused by particle sampling and clustering. Gaussian mixture particle is introduced to effectively maintain the multi-modal distribution of each target,reducing the complexity of calculation. |
| Starting Page | 227 |
| Ending Page | 236 |
| Page Count | 10 |
| File Format | PDF HTM / HTML |
| DOI | 10.14257/ijmue.2015.10.2.21 |
| Volume Number | 10 |
| Alternate Webpage(s) | http://www.sersc.org/journals/IJMUE/vol10_no2_2015/21.pdf |
| Alternate Webpage(s) | https://doi.org/10.14257/ijmue.2015.10.2.21 |
| Journal | MUE 2015 |
| Language | English |
| Access Restriction | Open |
| Content Type | Text |
| Resource Type | Article |