# A Multimode Fusion-Based Aviation Communication System
## 1 Introduction
Classified by fusion objective, the methods include data preprocessing [20], state estimation [21], attribute fusion [22], situation assessment [23], and so on; classified by the fusion mode, the methods include centralized [24], distributed [25], and hybrid fusion [26] methods. A fusion method [27] for air surveillance information based on ensemble learning was proposed in 2020; the position estimation would be more accurate by predicting and fusing multiple aerial surveillance sources. A fusion method [28] for aviation surveillance information based on multiple neural networks was proposed in 2020, to successfully overcome the high requirements of model error and computational accuracy for Kalman filters, ensuring the flight safety of the aircraft. In 2020, the paper [29] proposed a novel joint sensing-communication (JSC) CSUN that can simultaneously conduct downward-looking radar sensing and sensing data fusion communication with the unified spectrum and transceiver by adopting the beam sharing scheme. A multi-source information fusion fault diagnosis method [30] based on the Dempster-Shafer (D-S) evidence theory was proposed in 2021; it helps to improve the high-precision fault diagnosis of aviation hydraulic pumps. The application of non-orthogonal multiple access (NOMA) technologies into satellite-aerial-ground integrated networks in 2022 [31] can meet the requirements of ultra-high rate and massive connectivity for the sixth-generation (6G) communication systems. The paper [32] in 2022 proposed a hierarchical satellite-ground collaborative architecture with three roles: remote cloud center, orbital edge computing server, and data node. A new cooperative interference cancellation strategy [33] is proposed for the multi-beam UAV uplink communication, which aims to eliminate the co-channel interference at each of the occupied ground base stations (GBSs) and, in the meanwhile, maximize the sum rate to the available GBSs with an information fusion strategy to unify communication and visual information. Nevertheless, the literature mainly focuses on theoretical calculations and software simulations, so there is a significant gap in the implementation of the project. In 2023, a mathematical computing technique based on finite state automaton (FSA) was introduced in [34] to expand the range of the ER-ID RF system and reduce the energy required by the drone to use the technology, and a decentralized estimation and tracking of a mobile target performed by a group of unmanned aerial vehicles (UAVs) was studied in [35]. Building on advancements in aviation communication technology, wireless ad hoc networking, differential high-precision positioning and navigation, aviation broadcasting response, and 5G public network communication, we have developed a multimode satellite-aerial-ground integrated fusion communication system model. This model specifically addresses the challenges associated with the increasing quality demands and volume expansion in aviation communication systems. By reducing the physical footprint and enhancing the performance of communication equipment, our system not only pro vides robust data communication but also enables efficient aggregation, sharing, analysis, and display of information. These capabilities are crucial for modern aviation communication, laying the groundwork for a universal, open, interconnected, and comprehensive aviation communication network that meets the demands of current and future aeronautical operations.