Particle filtering for range-based localization in Wireless Sensor Networks

The paper proposed a range-based particle filtering localization method for static WSN (Wireless Sensor Network). In the method, every blind node in WSN localizes itself through local distance measurements. So the method is parallel. With the development of hardware, RSSI (Received Signal Strength Indicator) measurements were already hardwired in some chips, and then almost no extra hardware was required when the measurement stratagem was adopted. Firstly, the state-space function of localization in a static WSN was proposed in the paper. And the measurement noise model was particularly studied. Because of the non-linear and non-Gaussian model, particle filter was adopted as a suitable localization algorithm for the application. Static nodes bring some new problems to us. So important steps in a particle filter were specifically illustrated in the paper, including: initialization, prediction, sequential importance sampling and the resampling. Software simulations were done in the paper to demonstrate the effect of the proposed method. A blind node was selected as a sample to illustrate the convergence of the particle filter. And some problems emerged in the simulation were also analyzed. After that, it showed a result about localization in a 100 nodes network by the proposed method.