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The centralized Kalman filter is always applied in the velocity and attitude matching of Transfer Alignment (TA). But the centralized Kalman has many disadvantages, such as large amount of calculation, poor real-time performance, and low reliability. In the paper, the federal Kalman filter (FKF) based on neural networks is used in the velocity and attitude matching of TA, the Kalman filter is adjusted by the neural networks in the two subfilters, the federal filter is used to fuse the information of the two subfilters, and the global suboptimal state estimation is obtained. The result of simulation shows that the federal Kalman filter based on neural networks is better in estimating the initial attitude misalignment angle of inertial navigation system (INS) when the system dynamic model and noise statistics characteristics of inertial navigation system are unclear, and the estimation error is smaller and the accuracy is higher.

For the rapid response of the aircraft, it is required that the aircraft is not only quick but also chooses the shortest flight routes. The great circle track is the shortest flight route on the earth between any two points, but the great circle track needs to cross the polar region when the aircraft flies over the hemispheres of East and West. Because the polar region has some particularity, such as the landform characteristics, the climatic conditions, and the vast territory, the transpolar aircraft is the key technology of global navigation. This article researched on the algorithm of SINS/GPS integrated navigation system and analyzed the result of simulation when the SINS/GPS integrated navigation system works in the middle-and low-latitude region and the polar region. The result of simulation shows that the working performance of SINS/ GPS integrated navigation system is improved and makes use of their respective advantages to overcome the shortcomings. By comparing the result of simulation, the navigation precision is consistent when the SINS/GPS integrated navigation system works in the middle-and low-latitude region and the polar region.

Because the accuracy of the existing airborne navigation is lacking in the polar region, it is difficult to ensure the safety and reliability of the aircraft when it is flying over the polar region. The integrated navigation system based on the inertial navigation technology uses multi-information fusion to assist collaborative navigation and obtain an indirect grid navigation algorithm that combines the azimuth navigation algorithm and the grid navigation algorithm to solve the existing problems. This paper analyzes the principle of the inertial navigation system in the polar region, the semiphysical simulation experiments are carried out by using the navigation theory and the background engineering, and the accuracies of the integrated navigation system of the indirect grid frame in the polar region and the integrated navigation system in the middle and low latitudes are consistent, which verifies the feasibility and effectiveness of the SINS/CNS/GPS integrated navigation system in the polar region. In addition, the paper provides the theoretical basis and the application of engineering to achieve the SINS/CNS/GPS integrated navigation system in the polar region.

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This paper analyses the bit error rate (BER) of the spatial modulation orthogonal frequency division multiplex (SM-OFDM) system and derives the optimal power allocation between the data and the pilot symbols by minimizing the upper bound for the BER operating with imperfect channel estimation. Furthermore, we prove the proposed optimal power allocation scheme applies to all generalized linear interpolation techniques with the minimum mean square error (MMSE) channel estimation. Simulation results show that employing the proposed optimal power allocation provides a substantial gain in terms of the average BER performance for the SM-OFDM system compared to its equalpower-allocation counterpart.

SummaryIn the big data era, information security is becoming more and more important. The recent scandal of the data privacy on Facebook sounded the warning bell for us. Based on the utility theory, this paper proposes that the disclosure behavior of consumer personal information is mainly influenced by two factors, which are perceived risk and perceived benefit, respectively. When consumers make decisions, they weigh the risks and benefits. If the income is greater than the risk, the consumer is willing to provide the information on the website and vice versa. This paper analyzes the serious threats to the safety and privacy of commercial big data and proposes a multi‐level security protection theoretical model for business information security and privacy protection from the perspective of business big data security. The security functions and core technologies of each layer are described in detail, which provide a useful and in‐depth theoretical exploration for practical engineering. Finally, based on the privacy protection of large data and the principle of RBAC, a model of user privacy information security system is proposed.