This paper present a Residuals Chi-square Test Method (RCTM) and an Autonomous Integrity monitoring by Extrapolation Method (AIME) for the integrity monitoring of integrated GNSS/SINS system. Firstly the tightly coupled integrated architectures and Kalman filer are designed, then a detailed investigation of the capability of the RCTM and AIME algorithms to deal with the step and ramp failure are carried out, and the realistic simulation platform is established. The simulated GNSS and SINS measurements for the aircraft are used to evaluate the performance of the integrity algorithms. Results show that RCTM can detect step and quickly growing failure effectively, while for slowly growing failure the AIME algorithm can detect earlier than RCTM. Combining the two methods can detect and eliminate both the step failure and ramp failure quickly and accurately.
TerraSAR-X is the first commercially operated high resolution space-borne SAR in the world, which shows good potential in target detection fields. Statistical analysis and modeling are key steps in SAR images based automatic target detection systems. With four typical statistical measures, lognormal distribution is proved well to fit the histograms of TerraSAR-X images over land and ocean regions, and more suitable than Weibull, Gamma, K, G0 and stable distributions to modeling statistics of such images. Additionally, the MLE based parameters estimation and simply analytical expression of detection threshold also indicates the effectiveness and efficiency of lognormal based CFAR for target detection.
The single-stand reversible cold rolling mill is important equipment in the production of steel strips. The rolling schedule is the core technological content in the strip production of the single-stand reversible cold rolling mill. The scientific rolling schedule is the fundamental guarantee for the production capacity of the rolling mill, product quality, accuracy, shape quality, energy saving, and consumption reduction. This paper takes the dynamic rolling process of single-stand cold rolling as the research object, the purposes of increasing production capacity, saving energy, and reducing consumption are achieved by optimizing the rolling schedule. Based on the study of the mechanism model and the analysis of a large number of field measured data, a slice of mathematical models of the rolling process suitable for engineering calculation are proposed, and a few objective functions suitable for the single-stand reversible cold rolling process are designed. On this basis, the artificial fish swarm algorithm is improved into a multiobjective optimization algorithm for the optimization of rolling schedule, and the optimal rolling load distribution scheme is obtained. Finally, the optimization method of rolling schedule proposed in this paper is applied to the actual rolling production. The results show that the proposed method can improve productivity and save energy compared with the empirical rolling schedule, and the feasibility and validity of the proposed algorithm are verified.
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