Abstract
The multiple hypothesis tracking (MHT) algorithm is considered as the optimal data association algorithm in condition of low detection probability, high clutter density, and dense target distribution. Because of the data independent process between detector and tracker in conventional, the performance of radar signal processing system will be decreased. In order to solve this problem, a joint detection and MHT for multi-target tracking model is proposed. Firstly, MHT filter provides the location distribution information to the Bayesian detector. Then, the detector utilizes the information to calculate the prior information to adjust the detection threshold. Simulation results illustrate that the proposed algorithm has significant improvement in tracking accuracy compared with the traditional MHT algorithm.
| Translated title of the contribution | Joint Detection and MHT for Multiple Target Tracking |
|---|---|
| Original language | Chinese (Traditional) |
| Pages (from-to) | 195-199 |
| Number of pages | 5 |
| Journal | Beijing Ligong Daxue Xuebao/Transaction of Beijing Institute of Technology |
| Volume | 39 |
| State | Published - Oct 2019 |
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