Multi-Sensor Information Fusion Algorithm Design under N-P Criterion
Sensors are the key components for realizing a high degree of automation in environmental sensing.To realize a high level of anti-interference and robustness of multi-sensor systems,a multi-sensor information fusion algorithm based on statistical judgment is innovatively proposed to address the problems of poor stability and insufficient accuracy of local sensors.Firstly,the basic modeling of multi-sensor fusion is completed,and the calculation method of single-value probability characteristics of single sensors is designed.Then,the Kalman filtering method in traditional single sensing is optimally designed and the effect of cumulative error is eliminated.Finally,the design of multi-sensor information fusion algorithm for multi-dimensional evaluation is accomplished by introducing the Neyman-Pearson(N-P)criterion.The receiver operating characteristic(ROC)curve evaluation test proves the theoretical correctness and rationality of the proposed algorithm.Compared with other algorithms,the proposed algorithm has significant advantages in the performance of anti-interference and fault tolerance.The actual unmanned aerial vehicle test proves that the algorithm has some practicality.
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