LWMA filtering can help recover the scenario back to no interference situation.
Compared with original fingerprint localization scheme (Figure 1(b)), LWMA filtering, cooperative localization, and OWKNN algorithm are introduced to enhance localization performance.
which is predicted by [N.sub.pre] reference parameters after signature waveform when reference parameters are insufficient before it, where .RSS/[i] is the ith value, cur is current index in list, [N.sub.pre] is the number of prior parameters, [N.sub.att] is number of RSSI signatures attenuated caused by human interference, and RSSI[[cur].sub.predict] is the predicted value computed by LWMA, which works on the D-value of RSSI and its prediction reaches a threshold.
LWMA filtering will replace the RSSI signature values that trigger the capture condition coincidentally without interference.
There are comparisons among 9 cases both for localization accuracy and its standard deviation--Case 0: no interference; other cases, I: RSSI signatures are interfered but not filtering; F: RSSI signatures interfered are filtered by LWMA; C: colocalization recovers accuracy; 1: interfered by single human; 2: interfered by 4 humans semisurrounded; 3: interfered by 8 humans surrounded.