Multi-function wireless systems demand multi-channel transmit/receive (TR) modules, particularly as multiple functions are required to operate simultaneously. In each channel, passive components, including bandpass filters, must be compact, or at least transversely compact; thus, the entire circuitry of the channel will be slender, and consequently multiple channels can be parallel-arranged conveniently. In this work, single-ended and balanced bandpass filters for multi-channel applications are presented. As a unique resonator, the U-shaped stepped impedance resonator (USIR) can achieve size miniaturization compared with its corresponding uniform impedance resonator (UIR) counterpart. Hence, with the utilization of USIRs, the proposed bandpass filters are able to acquire compact transverse sizes. Moreover, by using the source-load coupling scheme, two transmission zeros (TZs) are respectively generated at the lower and upper sides of the passbands, which is useful for improvement of the selectivity performance. In addition, spurlines are introduced at the input and output ports to produce another TZ to further enhance the stopband performance, which cannot be acquired by the UIR or stepped impedance resonator (SIR). To verify the aforementioned idea, one single-ended and one balanced bandpass filter are implemented, with experimental results in good agreement with the corresponding simulations. Meanwhile, as compared with some similar works, the proposed balanced filter achieves compact transverse size, sharp selectivity skirt, and wide stopbands up to the fourth-order harmonic with suppression over 20 dB, which illustrates its suitability for differential signal transmission application in microwave circuits and systems.
System wide information management (SWIM) involves civil aviation system control, intelligence, alarm, traffic, and other data. These data are transmitted in various forms, making SWIM system vulnerable to sensitive information leakage, data tampering, denial, and other security threats. In this article, an attribute-based air traffic management (ATM) information access control scheme is proposed to solve the security threat of SWIM. An improved extensible access control markup language (XACML) authorization model is established, combining linear secret sharing scheme (LSSS) matrix structure and monotone span program (MSP); an attribute association algorithm is designed to establish the attribute association relationship between services and users. Experimental results show that the attribute association algorithm improves the time complexity, but the algorithm can support richer policy representation capability, and the proposed ATM information access control scheme is more efficient and can effectively reduce the space cost. This scheme can achieve more fine-grained and flexible access control.
In wide-area distributed scenarios, it is particularly important to carry out information security situational awareness for the air traffic management (ATM) system with integrated air-ground structure. The operation data of the communication, navigation and surveillance (CNS) equipment of ATM system have the characteristics of multi-dimension, complexity, and strong correlation. In the process of situation awareness feature extraction, there are problems such as poor model accuracy, weak feature expression ability, and low classification performance. A feature association algorithm is designed to solve the above problems. Based on this algorithm, a deep-related sparse autoencoder (DRSAE) model based on improved sparse autoencoder is established. In DRSAE model, L1 regularization and Kullback–Leibler divergence (KLD) sparsity terms are used to penalize the parameters of the encoder network, and the quantity of hidden layers is increased to allow the model to optimize the global encoder network by iteratively training a single encoder. Moreover, the proposed DRSAE model and other feature extraction models such as principal component analysis (PCA), autoencoder (AE), and sparse autoencoder (SAE) are compared and evaluated by using the support vector machine (SVM) classifier. Compared with other feature extraction models, it is found that the proposed DRSAE model has good robustness in feature extraction of ATM system, and the obtained features have strong expression ability, which enhances the classification performance of the model and is convenient for situation awareness.
TSN (Time Sensitive Network) is a real-time Network communication technology being promoted by the international industry. It has the characteristics of more flexibility and high real-time performance. This paper firstly introduces the background of airborne network and real-time network. Then, TSN and the mainstream airborne communication network technology are compared and analyzed from the aspects of synchronization mechanism, scheduling strategy, redundancy and reliability mechanism. Finally, the prospect of TSN in the field of civil aviation is analyzed in general, which makes the application route of TSN in the airborne communication network more clear.
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