Research Article
RoC: Robust and Low-Complexity Wireless Indoor Positioning Systems for Multifloor Buildings Using Location Fingerprinting Techniques
Table 1
Recent system design approaches for indoor positioning systems.
| Category | Scheme | Localization algorithm | Optimization method | Design objectives | Design limitations | Service areas | Robustness (support in RN-failure situation) |
| Triangulation | [10] | RSS-based | Tabu search | To minimize localization error | The design does not consider minimizing the number of RNs | Single floor | No | [11] | Distance-based | Genetic Algorithm | To maximize signal coverage and minimize number of RNs | The selected fitness evaluation influences the localization results | Single floor | No | [12] | TOA | ā | To minimize localization error | The RN placement has only a uniform angular distribution | Single floor | No |
| Scene analysis | [13] | KNN | Simulated Annealing | To minimize total number of similar fingerprints | The dynamic nature of the indoor environment is not considered in the system design | Single floor | No | [14] | WKNN | ā | To maximize signal RSS and minimize noise | The design does not consider the signal coverage in the physical surroundings | Single floor | No | [15] | KNN | Simulated Annealing | To maximize fingerprint difference | Complicated indoor layouts influence the minimum number of RNs | Single floor | No | [16] | Euclidean distance | Simulated Annealing | To maximize summation of maximum RSS | The RN placement design lacks system reliability | Single-floor and multifloor | No | Proposed design | Active Fusion | Simulated Annealing | To minimize number of RNs and find their optimum locations to be provisioned to support RN-failure situations | The design considers only the discrete candidate sites for installing RNs | Single floor and multifloor | Yes |
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