Sensors positioning in outdoor environment with signal strength

Log-distance path loss model have been using as a simple positioning method because of its simplicity which is mainly depends on Received Signal Strength (RSS) along with path loss exponent and random Gaussian noise variable with zero-mean. This model can be extensively used in urban and remote area because it is related to energy representation. On the other hand, fingerprint positioning is also an alternative solution in positioning due to it reliable performance. It is noticed that antenna gain and background thermal noise should be included into the model such that the accuracy could be improved. In this investigation, a sub-urban route was selected as testing area and carried the Particle Swarm Optimization (PSO) for an optimal coordinate. Experimental results show that the new scheme was implemented successfully in RSS positioning resulting in about averaged 100 meters and 84 meters in daytime and evening time respectively in same experiment scene. This new scheme provides a more reliable way in calculating a sensors position.