Research Article
Digital Twin-Enabled Online Battlefield Learning with Random Finite Sets
Algorithm 1
RFS-based online battlefield learning algorithm.
| Input: | | Output: | (1) | for to do | (2) | Generate the particles for the UGV state, ; | (3) | Get predicted battlefield PHD through the predict step of PHD filter; | (4) | Get updated battlefield PHD through the update step of PHD filter; | (5) | Get predicted PHD mass ; | (6) | Get updated PHD mass ; | (7) | Select a given battlefield state ; | (8) | ; | (9) | ; | (10) | Get updated UGV state weight ; | (11) | end for | (12) | Initialize the learned battlefield state , ; | (13) | Determine the maximum weight component ; | (14) | Update UGV state with ; | (15) | Update battlefield state according to the related PHD: | (16) | for to do | (17) | if , here is the landmark existence threshold | (18) | Generate new battlefield state by ; | (19) | end if | (20) | end for | (21) | Return . |
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