Object Detection on Various UWB detection targets
90.71PrecisionFiltering on peak properties, SNR-score, PDoA and clustering
Evaluation results
| Method | Links | ||||
|---|---|---|---|---|---|
| Filtering on peak properties, SNR-score, PDoA and clusteringApproach=Filtering on peak properties, SNR-score, PDoA and clustering, Chip=QM33120WDK1, UWB Mobile robot=true, No Anchor Nodes=true, Angle Estimation of Objects=true, IEEE 802.15.4 Compliant=true, Target Object=metal plate, concrete and plywood box2025.11 | 90.71 | 88.4 | — | — | |
| Signal Entropy UtilisationApproach=Utilises signal’s entropy, Chip=UMAIN HST-D3 directional antenna, UWB Mobile robot=false, No Anchor Nodes=true, Angle Estimation of Objects=false, IEEE 802.15.4 Compliant=false, Target Object=pedestrian, cyclist, vehicle, tram2025.11 | 75.34 | 63.06 | 68.65 | — | |
| Discrete Wavelet Transform and LSTMApproach=Uses Discrete Wavelet Transform to extract features and forward these to the LSTM network, Chip=UMAIN HST-D3 directional antenna, UWB Mobile robot=false, No Anchor Nodes=true, Angle Estimation of Objects=false, IEEE 802.15.4 Compliant=false, Target Object=pedestrian, cyclist, vehicle, tram2025.11 | 72.78 | 71.34 | 72.06 | — | |
| Supervised Machine LearningApproach=Supervised Machine Learning, Chip=P440 from TimeDomain, UWB Mobile robot=false, No Anchor Nodes=true, Angle Estimation of Objects=false, IEEE 802.15.4 Compliant=false, Target Object=humans/obstacles2025.11 | — | — | — | 95 |