Measurement fusion algorithm based on equivalent sensor in sensor networks

In sensor network, several kinds of information with different characteristics are usually sensed by the sensor nodes, and measurement fusion is performed on sink nodes to reduce the communication cost and improve the whole performance. To reduce calculational cost of measurement fusion of sink nodes, the problem is ascribed to the one of measurement fusion for dissimilar sensors. Defect of typical augmented method which causes high calculational cost is analyzed, and then the conception of equivalent sensor and a measurement fusion method based on it is presented. The equivalent sensors with inconsistent elements sequence in original observation vectors are created by inducting invalid elements, so that equivalent sensors with same dimension could be fused and filtered using combined measurement filtering method. In this way, the restriction of combined measurement filtering method was overcome and the calculational cost of measurement fusion of sink nodes is reduced. To be convenient for numerical calculation, suboptimal measurement fusion algorithm is put forward also. Simulation results show that this method has lower calculational cost than augmented method, and the performance doesn’t vary with the amount of sensor nodes associated to sink node.