Research on Multi-Sensor Data Aggregation Based on Clustering Analysis and Correlation

Abstract

Multi-sensor is deployed for the target-monitoring in complex environment. However, the distribution of sensory data is irregular and inconsistent and the data is also highly redundant. For the purpose of obtaining accurate information, this article proposes a method for data aggregation of multi-sensor based on clustering analysis and correlation. By computing the correlation of the sensory data and the clustering analysis, the overall distribution of the data is analyzed. Finally, the method integrates sensory data by the correlation and uses the joint probability density function to compute the best integrated point. Simulated results show that the method is more effective in data aggregation than traditional methods.