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Accurate altitude measurement of UAV is very important for its flight mission. Based on the analysis of the measurement performance of different altitude measurement sensors, this paper designs a multi-altitude measurement sensor fusion filtering structure, and then describes the fusion filtering method. This method mainly provides weighted fusion of data from various altitude measurement sensors to obtain altitude information with higher accuracy than any sensor. Through Kalman filtering of the fusion data, more accurate flight altitude data of UAV can be obtained. The method is validated by a typical example. The results show that the proposed method can solve the problem of precise measurement of altitude data in UAV flight process, and has certain theoretical significance and good application value.

The current assessment of the security of energy transaction data has vague evaluation dimensions, resulting in large errors in the assessment results. To this end, we propose a method for assessing the security of energy transaction data based on big data and the Pagerank algorithm. Determine assessment requirements based on big data and obtain assessment requirements based on six dimensions. Construct a security assessment model and calculate the indicator weights for this model. The assessment results are obtained dynamically based on the Pagerank algorithm. Experiments show that the evaluation results of the method have a small error, with an average error of only 0.22%, which has a high application value.