A Mobile Localization Method in Smart Indoor Environment Using Polynomial Fitting for Wireless Sensor Network

Algorithm 1

PF-AKF.

1: fordo

2: obtain distance measurement .

3: Calculate curve and by polynomial fitting using Eq. (14) and Eq. (15).

4: Obtain distance prediction using Eq. (16).

5: NLOS detection by hypothesis test using Eq. (18).

6: Adjusted Kalman Filter using Eq. (19) and Eq. (20).

7: Kalman prediction using Eq. (21) and Eq. (22).

8: Kalman update using Eq. (26) and Eq. (27).

9: if NLOS detected then

10:  calculate weighted state estimation by weighting filter using Eq. (29).

11: end if

12: obtain distance estimation by combination using Eq. (28).

13: calculate coordinate estimation by maximum likelihood localization using Eq. (34).

14: end for