Localization with signal-based signature distance

Abstract

Node localization plays a key and basic role for wireless sensor network. Existing range-free localization approaches suffer from precision limit of positioning, while range-based solutions may obtain good accuracy but pay high costs for ranging hardware. Instead of directly mapping received signal strength values into physical distances, a novel localization scheme with signal-based signature distance estimation is proposed for wireless sensor network. More specifically, we first quantify the near-far relationship between neighbor nodes through received signal strength comparison, and then the distance between non-neighbor nodes is calculated by an improved shortest path algorithm. Based on the obtained node distance, a relative map can be constructed by multidimensional scaling technology. Eventually, the locations of nodes can be acquired by virtue of Procrustes analysis method. For purpose of verifying the effectiveness of our design, several simulations are made in a sensor network with 200 randomly deployed nodes, and two experiments are implemented in real outdoor environments: a linear network and a two-dimensional grid network with 25 nodes. It is remarkable from results that the proposed scheme performs better in positioning and reduces localization errors by as much as 37% compared with state-of-the-art methods.

Sequence-Based Indoor Localization with Channel Status Information

“…Currently, there exist two types of wireless localization methods: range-based localization [ 11 , 12 , 13 , 14 , 15 , 16 , 17 ] and range-free localization [ 18 , 19 , 20 ], according to whether there is actually the distance or angle of measured nodes in the localization process. The range-based localization mechanisms determine the localization of unknown nodes by measuring the actual point-to-point distance or angle information between nodes and using the trilateration, triangulation or maximum likelihood estimation methods, based on the time of arrival (TOA) [ 11 ], time difference of arrival (TDOA) [ 12 , 13 ], angle of arrival (AOA) [ 14 ], signal-based signature distance [ 15 ], received signal strength indicator (RSSI) [ 16 , 17 ], and so on. In the above four algorithms, TOA, TDOA and AOA require additional hardware devices, while RSSI does not because the interface of most nodes has the function of receiving radio frequency (RF) signals [ 21 ] and can test the signal strength.…”