Next Article in Journal
Towards Autonomous Operation of UAVs Using Data-Driven Target Tracking and Dynamic, Distributed Path Planning Methods
Previous Article in Journal
A New Accurate Aircraft Trajectory Prediction in Terminal Airspace Based on Spatio-Temporal Attention Mechanism
 
 
Font Type:
Arial Georgia Verdana
Font Size:
Aa Aa Aa
Line Spacing:
Column Width:
Background:
Article

A Multimode Fusion-Based Aviation Communication System

1
College of Electronic and Information Engineering, Tongji University, Shanghai 201804, China
2
Shanghai Aerospace Electronics Co., Ltd., Shanghai 201821, China
3
College of Transportation, Tongji University, Shanghai 201804, China
*
Author to whom correspondence should be addressed.
Aerospace 2024, 11(9), 719; https://doi.org/10.3390/aerospace11090719
Submission received: 14 July 2024 / Revised: 20 August 2024 / Accepted: 30 August 2024 / Published: 3 September 2024

Abstract

:
This paper presents a new design for a multimode fusion communication system, aimed at tackling the complexities of modern aeronautical communication. The system integrates multiple communication technologies, such as ad hoc networking, 5G, BeiDou satellite, RTK positioning, and ADS-B broadcasting. This integration effectively solves the problem of increasing the size and weight of aviation communication equipment while also improving the efficiency and security of data communication. The study demonstrates that the implementation of this fusion communication system can lead to the development of more efficient and intelligent avionics equipment in the future, thereby offering robust technical support for flight safety.

1. Introduction

With the rapid development of China’s civil aviation [1] and civil aircraft industry in recent years, aviation electronic equipment [2] has become an important part of modern aircraft, playing a vital role in the performance and safety of aircraft. To accomplish a normal fight, the aircraft should include all necessary communication systems for shortwave communication, ultra-shortwave communication, satellite communication [3], data links, etc. Due to the increasing number of aviation electronic equipment, the volume and total mass of communication systems are highly increased [4], and the electromagnetic interference problems [5,6] between equipment are getting worse, each independent communication device needs to be allocated a certain space in the cabin, which exceeds the limit of cabin space burden.
In this article, a new design and engineering implementation scheme for aviation multimode fusion-based communication systems is proposed to solve the challenges faced by aviation communication. These challenges include numerous communication links, inconsistent communication protocols [7], complex cabin equipment, and a limited working environment, The proposed system contains various functions, such as dedicated ad hoc network communication [8], 5G public network communication [9], BeiDou satellite communication [10], RTK high-precision positioning and navigation [11,12], and ADS-B broadcasting communication [13]. We firstly establish the intelligent fusion platform based on the research of multiple communication links, protocols, and standards, making intelligent decision-making and execution of communication modes, providing insistent interactive information services such as location, voice, image, video, and data for the safe navigation, addressing the current shortcomings of aviation communication, such as low communication rate, long time delay, and poor interconnection capability. Secondly, we build a database, analyze data, and establish a visualization platform through multiple communication links; do the research on algorithms for aircraft trajectory prediction and abnormal behavior analysis; enhance the automation and intelligence level of aviation supervision; reduce the occurrence of flight accidents and illegal activities; and consequently ensure the safety and economy of flight, as well as realize all-weather, all-around, all-time data transmission and remote monitoring guarantee.
Information fusion technology [14,15,16,17,18,19] is intended to combine information obtained from multiple sources into a unified description; it is a multi-level and multifaceted processing engineering that involves detecting, correlating, combining, and estimating multi-source data. With the continuous development of aviation communication technology, new application requirements and target characteristics pose new challenges to the multi-source information fusion technology of aircraft, mainly reflected in subverting traditional communication styles with networked information technology, emphasizing more on the allocation of time and space, and obtaining comprehensive situational information and resource support in the air; increasingly complex characteristics of aircraft targets originated by electromagnetic interference and environmental interference, as well as growing application demand for high-precision tracking flight and electromagnetic anti-interference; and under the condition of the breakthroughs in networked information technology, the integrated collaborative communication makes long-distance air command and control, information transmission, target guidance, and collision warning possible.
The point of aviation information fusion technology is to perceive and analyze the environment in which the target is located to make correct decisions and reactions. 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 provides 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.

2. System Design

In this section, a detailed description of the system design for the aviation multimode fusion communication system is provided. We will outline the overall architecture, including the integration of various communication technologies, and discuss the principles and calculations used for link budget analysis. This comprehensive overview sets the stage for understanding the system’s functionality and performance metrics.

2.1. Overall Architecture

The new aviation multimode fusion communication system integrates various communication links, such as ad hoc network communication, 5G public network communication, BeiDou satellite communication, RTK high-precision positioning and navigation, and ADS-B air broadcasting communication. This system creates a seamlessly integrated aviation communication network that connects aircraft with ground control centers and other aircraft in real time. This network enables precise data exchange during navigation, providing reliable and prompt data information services for aircraft. Please refer to Figure 1 for a visual representation of how the system works.

2.2. Link Calculation

Communication using electromagnetic waves as a medium in wireless communication, electromagnetic wave propagation can be influenced by propagation distance, propagation medium, and its characteristics. It is critical to research electromagnetic wave propagation in aviation wireless communication.
The radio can penetrate the ionosphere with a frequency above 30 MHz, and the ability to bypass the obstacles is weak. The basic mode is direct wave propagation between transmission and reception, and free space propagation is an ideal propagation model. Assuming an omnidirectional radiation source, for the transmission power in all directions, the unit is W. According to the principle of the conservation of energy, the energy radiated by the source per unit of time is always distributed on the sphere (or any necessary sphere) surrounding the source. Therefore, as the radius of the omnidirectional radiation sphere increases, the power or power flux density per unit area is
Φ d = P t 4 π d 2
where 4 π d 2 means the superficial area of the ball, and the typical unit of power flux density is W / m 2 .
The power P r received by the receiving antenna is determined by the size and orientation of the antenna relative to the receiver. In the effective area of the antenna A e f f , the power received by the receiving antenna absorption cross-section is
P r = Φ d A e f f = P t 4 π d 2 A e f f
An omnidirectional transmitting antenna can be regarded as a point source, and according to electromagnetic theory, its effective area in any direction A i s o t r o p i c is
A i s o t r o p i c = λ 2 4 π
where λ is the mean wavelength of the radiation waves.
Bring Equation (3) into Equation (2), and the relationship between the transmission power and reception power of omnidirectional antennas is
P r = P t 4 π d λ 2
Based on Equation (4), the free space path loss can be summarized as
L = P t P r = 4 π d λ 2 .
where L represents the free space path loss between two omnidirectional antennas, also known as diffusion loss.
During signal transmission, the signal intensity difference between the transmitted signal and the received signal can reach more than ten orders of magnitude, and the power of a certain transmitter can reach the kilowatt (kW) level or even the megawatt (MW) level; in contrast, the power of the receiver can reach the picowatt (pW) level. In general, the intensity, gain, and loss values of the signal are usually represented in decibels (dB):
L = 10 l g P t P r = C + 20 l g f + 20 l g d d B .
where f means the transmission signal frequency, the unit is MHz, and d means propagation distance, the unit is km.
As shown in Equation (6), the free space path loss L is only related to the transmission signal frequency f and the propagation distance d . C = 32.45 is the unit conversion factor, and it changes with the units of f and d . For instance, when f is in MHz and d is in miles, the value of C is 36.52. Nevertheless, when f is Hz and d is m, the value should be −147.5.
When using anisotropic antennas, the free space loss related to antenna reception and transmission power is
P r = P t G t G r 4 π d λ 2 = P t G t G r L .
where G t and G r means transmitter antenna gain and receiving antenna gain, respectively.
Equation (7) is called the Friis equation. To simplify the calculation, we will change it to the decibel (dB) expression here:
P r d B m = P t d B m + G t d B + G r d B L d B .
Furthermore, by converting the power unit to mW and comparing it with the participating power of 1 mW, and then taking the logarithmic operation of the comparison value, it can be obtained that
P d B m = 10 l g P mW 1 mW .
The Friis equation is the basic link budget equation, which describes the relationship between received power and transmitted power when considering the transmission characteristics of wireless links.
According to the Friis equation, the budget for the ad hoc network communication, 5G public network communication, BeiDou satellite communication, RTK high-precision positioning and navigation, and ADS-B air broadcast communication link of the new aviation multimode fusion communication system can be calculated, as shown in Table 1.

3. Hardware Design

Based on the design concepts of aviation systems engineering, including comprehensiveness, generalization, and modularity, the hardware of the aviation multimode fusion communication system consists of an ad hoc network communication module, a public network communication module, a BeiDou satellite communication module, an RTK high-precision positioning module, an ADS-B broadcast communication module, a fusion control module, a power module, and an antenna. The composition diagram is shown in Figure 2.

3.1. Ad Hoc Network Communication Module

The ad hoc network communication link uses point-to-point broadband networking data communication technology to support up to 32 nodes. Figure 3 shows that the link is based on the LTE wireless communication standard and adopts OFDM key technology. It also supports multiple bandwidth allocation, which flattens the system architecture design and effectively reduces system delays while improving the data transmission capacity. The ad hoc network communication data link has a long transmission distance, large data throughput, and strong anti-interference ability, which allows it to perform the following communication functions:
The optical lens data collected by the aircraft is transmitted to the ground control center via an ad hoc network link. The optical payload image and video are analyzed and displayed with the ad hoc network communication support 4K HD video transmission, transmission rate up to 20 Mbps.
The aircraft control computer transmits the flight status data to the ground control center through an ad hoc network link for analysis and display.
The aircraft control computer processes ground control command data uploaded via an ad hoc network link through the aviation multimode fusion communication terminal.
The ground control center can communicate bidirectionally with up to 32 aviation multimode fusion communication terminals using an aircraft ground ad hoc network communication function.
The ad hoc network communication module, public network communication module, and BeiDou satellite communication module are integrated on one board, and the block diagram is shown in Figure 4.
This technology relies on the creation of high-performance software radio SoC chips. To ensure secure communication, the SoC chips have implemented encryption protocols to protect data transmitted across the network. The RF chip uses a broadband-integrated chip that has high integration. As a result, the system’s power consumption decreases, and the module size decreases. The module’s power consumption is around 5 W.

3.2. Public Network Communication Module

The fifth-generation mobile communication technology, also known as 5G, is a new and advanced broadband mobile communication technology that offers high speed, low latency, and large connectivity. The 5G communication facilities are the network infrastructure that enables the connectivity between humans, machines, and objects, as shown in Figure 5. The 5G public network communication link has become a crucial infrastructure for the digital, networked, and intelligent transformation of aviation communication. The communication functions of the public network communication link include:
The optical data collected by the aircraft is transmitted to the ground control center via a public network communication link, where the images and videos are analyzed and displayed.
The aircraft control computer transmits flight status data to the ground control center via a public network communication link for analysis and display.
Ground control commands are transmitted to the aircraft by sending the command data to the aviation multimode fusion communication terminal via a public network communication link connected to the ground base station. The aircraft control computer processes this data.
In the coverage range of mobile base stations, the ground control center can communicate bidirectionally with thousands of aviation multimode fusion communication terminals.
The circuit diagram of the public network communication module is shown in Figure 6.
The development of the module is based on the 5G module, which is a 5G wireless communication module that supports a diversity reception function. Various network data connection standards are supported in this module, such as 5G NR SA/NSA, LTE-FDD, LTE-TDD, DC-HSDPA, HSPA+, HSDPA, HSUPA, WCDMA, etc. The power consumption of the module is about 5 W.

3.3. BeiDou Satellite Communication Module

The BeiDou satellite communication system is a two-way messaging service that relies on the BeiDou satellite navigation system. It offers communication services through the L-band and S-band links of the GEO satellites in the BeiDou constellation. The system comprises a space segment, a ground control segment, and a user segment. It boasts of a wide communication range and strong anti-interference capabilities, as illustrated in Figure 7. The communication functions of the BeiDou satellite link include:
The aircraft control computer collects flight status data that are transmitted to the ground control center using the BeiDou satellite communication link.
Ground control commands are sent to the aircraft control computer via the BeiDou satellite communication link.
The circuit diagram of the BeiDou satellite communication module is shown in Figure 8.
This module consists of the RDSS module and B1 & L1 positioning module. The RDSS module, with high integration and low power consumption, integrates the BeiDou RDSS RF transceiver chip, RDSS baseband chip, 5 W power amplifier chip, and LNA internally. The BeiDou SIM card and passive antenna can be connected externally to achieve the short message communication function of BeiDou RDSS. The B1 & L1 positioning module is used for auxiliary positioning. The standby power consumption of this module is about 2 W, and the signal transmitting power is about 15 W.

3.4. ADS-B Broadcasting Communication Module

The ADS-B broadcast communication module is an automatic broadcasting system that transmits vital information about the aircraft, including its type, aviation code, position, speed, altitude, and route, in an omnidirectional manner, as depicted in Figure 9. This module has the potential to offer safer and more efficient air traffic monitoring methods; widen the coverage of monitoring; and enhance air traffic safety levels, airspace capacity, and operational efficiency. The primary communication functions of this module are as follows:
The ADS-B communication module receives real-time messages from other aircraft broadcasts. These messages can be of various types, which will then be assembled into mode state (MS) reports following the RTCA/DO-260B standard [36]. The reports will then be sent to the flight control computer for analysis and processing. At the same time, the data will be transmitted down to the ground control center through dedicated ad hoc network links and public network links. The current air situation of the aircraft will be analyzed and displayed based on this data.
The ADS-B broadcast communication module receives navigation information such as longitude, latitude, altitude, and speed from the flight control computer. After inserting ME fields in DF18 format, multiple 1090ES data links are assembled to transmit various types of ADS-B messages. These messages are then broadcast through omnidirectional antennas. At the same time, the data are transmitted to the ground control center through dedicated ad hoc network links and public network links. Finally, the current situation of the aircraft is analyzed and displayed.
The composition diagram of the ADS-B module is shown in Figure 10.
The ADS-B module is a compact design that combines an ARM+FPGA+RF transceiver, saving space and enhancing the system capacity. The digital processing is accomplished using Xilinx’s Z7 series FPGA chip XC7Z020. The RF processing includes a reception channel and a transmission channel. The received signal is converted into a 70 MHz intermediate frequency signal through low-noise amplification, filtering, and mixing and then sent to the digital processing section. The transmission channel generates a 1090 MHz CW signal through VCO. The high-speed RF switch is controlled by FPGA to complete 2ASK modulation of the baseband signal and the local oscillator signal. The standby power consumption of the ADS-B module is approximately 25 W, and the signal transmitting power is about 33 W.

3.5. RTK High-Precision Positioning Module

RTK carrier phase difference technology is a real-time differential method used to process carrier phase observations from two measurement stations. The reference station collects the carrier phase, which is then sent to the user receiver for differential calculation of the coordinates. This results in the accurate positioning information are shown in Figure 11. This module provides precise positioning services, achieving centimeter-level accuracy. It can also provide timing, speed measurement, and direction finding for aircraft.
The RTK high-precision positioning module, power module, and fusion control module are integrated on one board, and the circuit composition diagram is shown in Figure 12.
After receiving the RTK signal, it is amplified and smoothed. The RF RFIC then converts this signal down to an intermediate frequency signal, which is sent to the processor for capturing satellite signals, tracking, navigation message demodulation, decoding, raw observation extraction, PVT calculation, and protocol conversion. The module provides support for various differential modes like RTK, DGNSS, and ground enhancement. This allows the module to provide centimeter-level precision positioning services and high-precision orientation services. The module also has anti-multipath, anti-occlusion, and anti-interference technologies, which enable it to achieve continuous and effective localization, even in complex environments. The module has a power consumption of approximately 3 W.

3.6. Fusion Control Module

The fusion control module is integral to the seamless interaction between external devices, such as optical lenses and flight control computers, within the multimode fusion communication system. This module is responsible for the sophisticated processing and distribution of critical data types, including image data, telemetry, and control signals. Additionally, it manages the comprehensive control and orchestration of various communication subsystems, which encompass the ad hoc network communication module, public network communication module, RTK differential high-precision positioning module, BeiDou satellite communication module, and ADS-B broadcast communication module.
As depicted in Figure 13, the architecture of the integrated control module is designed for high efficiency and modularity. The system’s core digital processing is managed by a field-programmable gate array (FPGA), which is responsible for executing tasks related to data manipulation and routing between various interfaces, such as RS232, RS422, SPI, and Ethernet. The FPGA also interfaces with external memory (DDR3) and flash storage to ensure rapid data processing and secure storage of critical information.
A notable component of the system is the RTK high-precision positioning module, which is powered by a secondary power supply ensuring consistent operation at 12 V, with 3.3 V outputs managed by low-voltage TTL (LVTTL) interfaces. This module provides real-time, centimeter-level accuracy in positioning data, which is vital for flight safety and precise navigation. The integration of this module with the FPGA allows for real-time data processing and communication with other subsystems, such as the BeiDou satellite communication and ADS-B modules, thereby enhancing the reliability and precision of the entire system.
The circuit layout also includes essential support systems, such as a power module and interfaces for JTAG and crystal oscillators, ensuring the system’s stability and synchronization. The presence of multiple UART channels, Ethernet, USB 2.0, and LVTTL connections illustrates the system’s versatility and ability to interface with a wide range of external devices, further enhancing its functionality in diverse aeronautical applications.
The digital processing part of the integrated communication module is implemented by Xilinx’s Z7 series FPGA chip XC7Z010. The power consumption of the fusion control module is about 5 W.
The power module mainly converts the input 28 V primary power supply into 12 V to satisfy the power supply needs of other boards. The circuit diagram of the power module is shown in Figure 14. The power board adopts cooling conducting dissipation, with an input of 18–36 V DC for the power supply. After EMI filtering, two isolated DCDCs are generated into two paths of 12 V voltages. One channel has a rated power of 100 W and is in charge of supplying power to the other six modules, and the other channel has a rated power of 3.3 W, to provide power to the two cooling fans.

4. Application Testing

The aviation multimodal fusion communication system is designed to meet the requirements of aviation engineering structures and applications. The system uses a stacked structure with reinforcing bars on three main printed boards to improve the structure and meet the vibration and impact requirements of aviation electronic equipment. To prevent electromagnetic interference, appropriate decoupling capacitors are installed on the module to meet the electromagnetic compatibility requirements. The thermal design transfers heat to the case shell using a conduction method. The aviation multimode fusion communication airborne terminal is shown in Figure 15, with a host size of 160.0 mm × 166.0 mm × 78.4 mm and a weight of ≤2 kg. The average power consumption is 50 W, and the peak power consumption is 90 W. The transmission error rate was found to be 1 × 10−5, and the transmission delay averaged 20 ms. We conducted 20 tests under various conditions, including different heights (e.g., 50 m), speeds (e.g., 80 km/h), and distances (e.g., 45 km). These detailed data are now included to provide a thorough understanding of the system’s performance.
The testing block diagram of the aviation multimode fusion communication system is shown in Figure 16. The system testing environment includes three aviation multimode airborne communication terminals, three network cameras, three regulated power supplies, three sets of upper computer software for airborne terminals, one ground testing equipment, and one set of ground control software.
The verification test results are shown in Table 2.
The aviation multimode fusion communication system is designed to integrate different communication links, such as dedicated ad hoc network communication, 5G public network communication, BeiDou satellite communication, RTK high-precision positioning and navigation, and ADS-B broadcasting. This system offers an extensive satellite–aerial–ground integrated communication network, with various functions such as image and data transmission, remote control, telemetry, high-precision positioning, and aviation situation awareness. Its capabilities make it a valuable asset in the field of aviation communication.

5. Conclusions

The ongoing evolution of aviation electronics necessitates the development of more integrated, modular, and intelligent systems. This paper presents a multimode fusion communication system designed to enhance aircraft communication capabilities. By incorporating ad hoc networks, 5G public networks, BeiDou satellite communication, RTK high-precision positioning, and ADS-B air broadcasting, the system achieves a balance between communication quality and system volume expansion, providing data communication, aggregation, sharing, analysis, display, and other services for modern aviation communication.
The system’s design emphasizes structural integrity, electromagnetic compatibility, and thermal management, featuring various modules, including ad hoc network, public network, BeiDou, RTK, ADS-B, and a fusion control module. This platform supports a range of functions, from data and image transmission to remote control and emergency communication. With advancements in artificial intelligence and big data, this system could further enhance air traffic control, monitoring, and early warning capabilities, laying the foundation for a comprehensive and interconnected aviation communication network.

Author Contributions

Conceptualization, J.Q. and M.L.; methodology, J.Q.; validation, J.Q. and F.X.; formal analysis, Y.B.; investigation, J.Q.; resources, J.K.; writing—original draft preparation, J.Q.; writing—review and editing, J.Q.; visualization, F.X. and D.O.; supervision, M.L. and J.K.; project administration, J.K. and D.O.; funding acquisition, J.K. All authors have read and agreed to the published version of the manuscript.

Funding

This research was funded by the Fundamental Research Funds for the Central Universities.

Data Availability Statement

Data are contained within the article.

Conflicts of Interest

Authors Jingyi Qian, Feng Xia and Yunfeng Bai were employed by the company Shanghai Aerospace Electronics Co., Ltd. The remaining authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.

Abbreviations

AbbreviationMeaning
Ad hoc networkinfrastructureless network
5Gthe fifth generation of mobile network technology.
RTKreal-time kinematic
ADS-Bautomatic dependent surveillance–broadcast
JSCjoint sensing-communication
CSUNcooperative sensing unmanned aerial vehicle network
D-SDempster–Shafer
NOMAnon-orthogonal multiple access
6Gthe sixth generation of mobile network technology.
UAVunmanned aerial vehicle
GBSsground base stations
LTElong term evolution
OFDMorthogonal frequency division multiplex
SoCsystem on chip
RFradio frequency
5GNR5G new radio
SAstandalone
NSAnon-standalone
FDDfrequency–division duplex
TDDtime–division duplex
DCdual carrier
HSDPAhigh speed downlink packet access
HSPA+evolved high speed packet access
HSUPAhigh-speed uplink packet access
WCDMAwideband code division multiple access
RDSSradio determination satellite system
LNAlow noise amplifier
SIMsubscriber identity module
MSmode state
RTCAradio technical commission for aeronautics
1090ES1090 MHz extended squitter
ARMadvanced risc machines
FPGAfield-programmable gate array
CWcontinuous wave
VCOvoltage-controlled oscillator
RFICradio frequency integrated circuit
PVTposition velocity time
DGNSSdifferential global navigation satellite system
EMIelectromagnetic interference

References

  1. Zhu, Y.; Jia, M.; Shi, Y. Analysis on current development situations, the key issues and countermeasures of China’s general aviation industry. Procedia Eng. 2017, 174, 871–877. [Google Scholar] [CrossRef]
  2. Ryapukhin, A. Trends in the Development of Standardization and Certification of Aviation Equipment. Transp. Res. Procedia 2023, 68, 183–190. [Google Scholar] [CrossRef]
  3. Kodheli, O.; Lagunas, E.; Maturo, N.; Sharma, S.K.; Shankar, B.; Montoya, J.F.M.; Duncan, J.C.M.; Spano, D.; Chatzinotas, S.; Kisseleff, S.; et al. Satellite communications in the new space era: A survey and future challenges. IEEE Commun. Surv. Tutor. 2020, 23, 70–109. [Google Scholar] [CrossRef]
  4. Kantimirov, S.; Serebryansky, S. On the Issue of Weight Design of Aircraft on a Digital Platform in a Single Information Space of the Product Life Cycle. In Proceedings of the 2021 14th International Conference Management of Large-Scale System Development (MLSD), Moscow, Russian, 27–29 September 2021. [Google Scholar]
  5. Liu, Z.; Ling, M.; Zhu, T.; Xu, D.; He, Y.; Liu, Z. Research on the Influence and Countermeasure of Radio Interference on Maritime Generation Aviation. J. Coast. Res. 2020, 36, 252–255. [Google Scholar] [CrossRef]
  6. Saraloğlu Güler, E.; Irgin, D. Maximizing Electromagnetic Interference Shielding Through Carbon Fiber Plating with Nickel: A Parameter-Based Approach. Trans. Indian Inst. Met. 2024, 77, 1553–1562. [Google Scholar] [CrossRef]
  7. Elmarady, A.A.; Rahouma, K. Studying Cybersecurity in Civil Aviation, Including Developing and Applying Aviation Cybersecurity Risk Assessment. IEEE Access 2021, 9, 143997–144016. [Google Scholar] [CrossRef]
  8. Lakew, D.S.; Sa’Ad, U.; Dao, N.-N.; Na, W.; Cho, S. Routing in Flying Ad Hoc Networks: A Comprehensive Survey. IEEE Commun. Surv. Tutor. 2020, 22, 1071–1120. [Google Scholar] [CrossRef]
  9. Bonati, L.; Polese, M.; D’oro, S.; Basagni, S.; Melodia, T. Open, Programmable, and Virtualized 5G Networks: State-of-the-Art and the Road Ahead. Comput. Netw. 2020, 182, 107516. [Google Scholar] [CrossRef]
  10. Li, G.; Guo, S.; Lv, J.; Zhao, K.; He, Z. Introduction to global short message communication service of BeiDou-3 navigation satellite system. Adv. Space Res. 2021, 67, 1701–1708. [Google Scholar] [CrossRef]
  11. Shi, J.; Ouyang, C.; Huang, Y.; Peng, W. Assessment of BDS-3 global positioning service: Ephemeris, SPP, PPP, RTK, and new signal. GPS Solut. 2020, 24, 81. [Google Scholar] [CrossRef]
  12. An, X.; Ziebold, R.; Lass, C. From RTK to PPP-RTK: Towards real-time kinematic precise point positioning to support autonomous driving of inland waterway vessels. GPS Solut. 2023, 27, 86. [Google Scholar] [CrossRef]
  13. Wu, Z.; Shang, T.; Guo, A. Security Issues in Automatic Dependent Surveillance—Broadcast (ADS-B): A Survey. IEEE Access 2020, 8, 122147–122167. [Google Scholar] [CrossRef]
  14. Padhi, D.K.; Padhy, N.; Bhoi, A.K.; Shafi, J.; Yesuf, S.H. An Intelligent Fusion Model with Portfolio Selection and Machine Learning for Stock Market Prediction. Comput. Intell. Neurosci. 2022, 2022, 7588303. [Google Scholar] [CrossRef]
  15. Ahmad, K.; Khan, K.; Al-Fuqaha, A. Intelligent Fusion of Deep Features for Improved Waste Classification. IEEE Access 2020, 8, 96495–96504. [Google Scholar] [CrossRef]
  16. Zhao, J.; Li, Q. Big Data-Artificial Intelligence Fusion Technology in Education in the Context of the New Crown Epidemic. Big Data 2022, 10, 262–276. [Google Scholar] [CrossRef]
  17. Hao, G.; Sun, Q.; Han, P. Research on Optimization Path of Intelligent Pension Industry Based on Intelligent Fusion Algorithm of Multisource Information. Sci. Program. 2021, 2021, 6193743. [Google Scholar] [CrossRef]
  18. Noh, S. Intelligent Data Fusion and Multi-Agent Coordination for Target Allocation. Electronics 2020, 9, 1563. [Google Scholar] [CrossRef]
  19. Xiao, M.; Feng, Z.; Fan, X.; Zeng, B.; Li, J. A Structure Design of Virtual and Real Fusion Intelligent Equipment and Multimodal Navigational Interaction Algorithm. IEEE Access 2020, 8, 125982–125997. [Google Scholar] [CrossRef]
  20. Wang, S.; Celebi, M.E.; Zhang, Y.D.; Yu, X.; Lu, S.; Yao, X.; Zhou, Q.; Miguel, M.G.; Tian, Y.; Gorriz, J.M.; et al. Advances in data preprocessing for bio-medical data fusion: An overview of the methods, challenges, and prospects. Inf. Fusion 2021, 76, 376–421. [Google Scholar] [CrossRef]
  21. Chen, Y.; Xie, X.; Yu, B.; Li, Y.; Lin, K. Multitarget Vehicle Tracking and Motion State Estimation Using a Novel Driving Environment Perception System of Intelligent Vehicles. J. Adv. Transp. 2021, 2021, 6251399. [Google Scholar] [CrossRef]
  22. Zhang, P.; Li, T.; Yuan, Z.; Luo, C.; Wang, G.; Liu, J.; Du, S. A data-level fusion model for unsupervised attribute selection in multi-source homogeneous data. Inf. Fusion 2022, 80, 87–103. [Google Scholar] [CrossRef]
  23. Yang, C.; Wang, D.; Zeng, Y.; Yue, Y.; Siritanawan, P. Knowledge-based multimodal information fusion for role recognition and situation assessment by using mobile robot. Inf. Fusion 2019, 50, 126–138. [Google Scholar] [CrossRef]
  24. Lai, J.W.; Chang, J.; Ang, L.K.; Cheong, K.H. Multi-level information fusion to alleviate network congestion. Inf. Fusion 2020, 63, 248–255. [Google Scholar] [CrossRef]
  25. Yang, Y.; Qin, Y.; Pan, Q.; Yang, Y.; Li, Z. Distributed fusion for nonlinear uncertain systems with multiplicative parameters and random delay. Signal Process. 2019, 157, 198–212. [Google Scholar] [CrossRef]
  26. Wen, P.; Li, Y.; Chen, S.; Zhao, S. Remaining useful life prediction of IIoT-enabled complex industrial systems with hybrid fusion of multiple information sources. IEEE Internet Things J. 2021, 8, 9045–9058. [Google Scholar] [CrossRef]
  27. Gao, Z.; Meng, Z. Aviation Surveillance Information Fusion Based on Ensemble Learning. In Proceedings of the 2020 IEEE International Conference on Information Technology, Big Data and Artificial Intelligence (ICIBA), Chongqing, China, 6–8 November 2020. [Google Scholar]
  28. Gao, Z.; Meng, Z. Aviation Surveillance Information Fusion Based on Multi Neural Network. In Proceedings of the 2020 IEEE 6th International Conference on Computer and Communications (ICCC), Chengdu, China, 11–14 December 2020. [Google Scholar]
  29. Chen, X.; Feng, Z.; Wei, Z.; Gao, F.; Yuan, X. Performance of Joint Sensing-Communication Cooperative Sensing UAV Network. IEEE Trans. Veh. Technol. 2020, 69, 15545–15556. [Google Scholar] [CrossRef]
  30. Lu, C.; Wang, S.; Wang, X. A multi-source information fusion fault diagnosis for aviation hydraulic pump based on the new evidence similarity distance. Aerosp. Sci. Technol. 2017, 71, 392–401. [Google Scholar] [CrossRef]
  31. Kong, H.; Lin, M.; Zhang, J.; Ouyang, J.; Wang, J.-B.; Upadhyay, P.K. Ergodic sum rate for uplink NOMA transmission in satellite-aerial-ground integrated networks. Chin. J. Aeronaut. 2022, 35, 58–70. [Google Scholar] [CrossRef]
  32. Zhou, D.; Sheng, M.; Li, J.; Han, Z. Aerospace Integrated Networks Innovation for Empowering 6G: A Survey and Future Challenges. IEEE Commun. Surv. Tutor. 2023, 25, 1. [Google Scholar] [CrossRef]
  33. Liu, L.; Zhang, S.; Zhang, R. Multi-Beam UAV Communication in Cellular Uplink: Cooperative Interference Cancellation and Sum-Rate Maximization. IEEE Trans. Wirel. Commun. 2019, 18, 4679–4691. [Google Scholar] [CrossRef]
  34. Koulouris, C.; Dimitrios, P.; Al-Darraji, I.; Tsaramirsis, G.; Musa, M.J.; Papageorgas, P. A Preliminary Study and Implementing Algorithm Using Finite State Automaton for Remote Identification of Drones. Appl. Sci. 2023, 13, 2345. [Google Scholar] [CrossRef]
  35. Lizzio, F.F.; Bugaj, M.; Rostáš, J.; Primatesta, S. Comparison of Multiple Models in Decentralized Target Estimation by a UAV Swarm. Drones 2024, 8, 5. [Google Scholar] [CrossRef]
  36. RTCA. Minimum Operational Performance Standards for 1090 MHz Extended Squitter Automatic Dependent Surveillance-Broadcast (ADS-B) and Traffic Information Services-Broadcast (TIS-B); DO-260B; RTCA Inc.: Washington, DC, USA, 2009. [Google Scholar]
Figure 1. Architecture diagram of an aviation multimode fusion communication system.
Figure 1. Architecture diagram of an aviation multimode fusion communication system.
Aerospace 11 00719 g001
Figure 2. Aviation multimode fusion-based communication composition diagram.
Figure 2. Aviation multimode fusion-based communication composition diagram.
Aerospace 11 00719 g002
Figure 3. Dedicated ad hoc link schematic diagram.
Figure 3. Dedicated ad hoc link schematic diagram.
Aerospace 11 00719 g003
Figure 4. Data transmission networking module composition block diagram.
Figure 4. Data transmission networking module composition block diagram.
Aerospace 11 00719 g004
Figure 5. The 5G public network communication link diagram.
Figure 5. The 5G public network communication link diagram.
Aerospace 11 00719 g005
Figure 6. The 5G public network module composition block diagram.
Figure 6. The 5G public network module composition block diagram.
Aerospace 11 00719 g006
Figure 7. Schematic diagram of the BeiDou satellite communication link.
Figure 7. Schematic diagram of the BeiDou satellite communication link.
Aerospace 11 00719 g007
Figure 8. RDSS module composition block diagram.
Figure 8. RDSS module composition block diagram.
Aerospace 11 00719 g008
Figure 9. ADS-B broadcast communication diagram.
Figure 9. ADS-B broadcast communication diagram.
Aerospace 11 00719 g009
Figure 10. ADS-B module composition block diagram.
Figure 10. ADS-B module composition block diagram.
Aerospace 11 00719 g010
Figure 11. RTK high-precision positioning navigation schematic diagram.
Figure 11. RTK high-precision positioning navigation schematic diagram.
Aerospace 11 00719 g011
Figure 12. RNSS module composition diagram.
Figure 12. RNSS module composition diagram.
Aerospace 11 00719 g012
Figure 13. Block diagram of an integrated communication module composition diagram.
Figure 13. Block diagram of an integrated communication module composition diagram.
Aerospace 11 00719 g013
Figure 14. Block diagram of the power module composition.
Figure 14. Block diagram of the power module composition.
Aerospace 11 00719 g014
Figure 15. Aviation multimode communication airborne terminal prototype.
Figure 15. Aviation multimode communication airborne terminal prototype.
Aerospace 11 00719 g015
Figure 16. Aviation multimode fusion communication system testing block diagram.
Figure 16. Aviation multimode fusion communication system testing block diagram.
Aerospace 11 00719 g016
Table 1. Aviation multimode fusion communication link budget.
Table 1. Aviation multimode fusion communication link budget.
Communication ParametersAd Hoc Network Communication5G Public Network CommunicationBeiDou Satellite CommunicationRTK High-Precision Positioning and NavigationADS-B Air Broadcast Communication
Working Frequency1.4 GHz3.5 GHz1.6 GHz1.5 GHz1 GHz
Transmission Power33 dBm23 dBm76 dBm45 dBm37 dBm
Transmitter Antenna Gain3 dBi1 dBi1 dBi3 dBi1 dBi
Transmission Line Loss1 dB1 dB1 dB1 dB1 dB
Communication Distance50 km0.5 km36,000 km20,183 km15 km
Space
Loss
129 dB97.25 dB191.5 dB182.4 dB116.67 dB
Atmospheric
Loss
2 dB2 dB2 dB2 dB2 dB
Receiving Antenna Gain3 dBi1 dBi1 dBi3 dBi1 dBi
Receiving Terminal
Line Loss
1 dB1 dB1 dB1 dB1 dB
Receiver Sensitivity−102 dBm−90 dBm−127 dBm−140 dBm−89 dBm
Link
Margin
8 dB13.75 dB9.5 dB4.6 dB7.33 dB
Table 2. Aviation multimodal fusion communication system status testing.
Table 2. Aviation multimodal fusion communication system status testing.
RequirementsCommunication LinkImplemented Functions
Image TransmissionAd hoc Network Communication LinkOptical payload images and videos are collected from multiple aircraft lenses and transmitted to the ground control center via an ad hoc network link for analysis and display.
Public Network Communication LinkThe data collected from all aircraft optical lenses within the coverage range of the base station is transmitted to the ground control center via the public network communication link through the ground public network base station, and the optical payload images and videos are analyzed and displayed.
Data TransmissionAd hoc Network Communication LinkFlight status data is collected from aircraft control computers and transmitted to the ground control center via an ad hoc network link for analysis and display.
Public Network Communication LinkThe flight status data from all aircraft control computers that fall within the coverage range of the base station is transmitted to the ground control center via a public network communication link through the ground public network base station. The ground control center then analyzes and displays the flight status data.
BeiDou Satellite Communication LinkThe flight status data collected by the aircraft control computer is transmitted to the ground control center via the BeiDou satellite communication link and analyzed and displayed.
Command and Remote ControlAd hoc Network Communication LinkUpload command data from ground control aircraft to multiple aviation multimode fusion communication terminals through ad hoc network links, and send it to the aircraft control computer for processing.
Public Network Communication LinkThe data from the ground control aircraft command is transmitted to the aviation multimode fusion communication terminal through a public network link. This is done via a ground base station and then sent to the aircraft control computer within the base station’s coverage range for processing.
BeiDou Satellite Communication LinkTransmit the aircraft command data to the aviation multimode fusion communication terminal via the BeiDou satellite communication link, and send it to the aircraft control computer for processing.
Aviation Situational AwarenessADS-B Link
The aircraft’s flight control computer receives ADS-B messages in real-time from other aircraft, which are analyzed and processed to determine the current air situation. These messages are also simultaneously transmitted to the ground control center through dedicated ad hoc network links and public network links.
ADS-B messages from aircraft are transmitted simultaneously to the ground control center through dedicated ad hoc and public network links. This allows for analysis and display of the current air situation.
High-precision Positioning NavigationRTK LinkProviding high-precision timing, speed measurement, direction finding, and precise positioning services for aircraft.
Disclaimer/Publisher’s Note: The statements, opinions and data contained in all publications are solely those of the individual author(s) and contributor(s) and not of MDPI and/or the editor(s). MDPI and/or the editor(s) disclaim responsibility for any injury to people or property resulting from any ideas, methods, instructions or products referred to in the content.

Share and Cite

MDPI and ACS Style

Qian, J.; Liu, M.; Xia, F.; Bai, Y.; Ou, D.; Kang, J. A Multimode Fusion-Based Aviation Communication System. Aerospace 2024, 11, 719. https://doi.org/10.3390/aerospace11090719

AMA Style

Qian J, Liu M, Xia F, Bai Y, Ou D, Kang J. A Multimode Fusion-Based Aviation Communication System. Aerospace. 2024; 11(9):719. https://doi.org/10.3390/aerospace11090719

Chicago/Turabian Style

Qian, Jingyi, Min Liu, Feng Xia, Yunfeng Bai, Dongxiu Ou, and Jinsong Kang. 2024. "A Multimode Fusion-Based Aviation Communication System" Aerospace 11, no. 9: 719. https://doi.org/10.3390/aerospace11090719

Note that from the first issue of 2016, this journal uses article numbers instead of page numbers. See further details here.

Article Metrics

Back to TopTop