UAT2数据链状态位图时隙分配与监视性能研究

汤新民; 汤盛家; 文旌宇; 顾俊伟

doi:10.11999/JEIT250251

UAT2数据链状态位图时隙分配与监视性能研究

doi: 10.11999/JEIT250251 cstr: 32379.14.JEIT250251

汤新民^{1, 2, ,},
汤盛家¹,
文旌宇¹,
顾俊伟¹

1.
南京航空航天大学民航学院南京 210016
2.
中国民航大学天津市城市空中交通系统技术与装备重点实验室天津 300300

基金项目: 国家自然科学基金(52072174)，高端外国专家引进计划(G2023202003L)，天津市科技计划项目(24JCZDJC00090)

详细信息

作者简介:
汤新民：男，教授，研究方向为智能网联交通控制工程、空地协同航空监视、先进场面引导与控制、无人机自主感知与避让

汤盛家：男，硕士生，研究方向为无人机通信链路

文旌宇：男，硕士生，研究方向为空管智能化技术

顾俊伟：男，博士生，研究方向为先进场面活动引导与控制系统

通讯作者:
汤新民　tangxinmin@nuaa.edu.cn

中图分类号: V355.1; TN919
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- 被引次数: 0
出版历程
- 收稿日期: 2025-04-09
- 修回日期: 2025-07-30
- 网络出版日期: 2025-08-27

Study on Time Slot Allocation and Monitoring Performance of UAT2 Data Link Status Bitmap

1.
College of Civil Aviation, Nanjing University of Aeronautics and Astronautics, Nanjing 210016, China
2.
Key Laboratory of Urban Air Traffic System Technology and Equipment, Civil Aviation University of China, Tianjin 300300, China

Funds: The National Natural Science Foundation of China (52072174), The High-level Foreign Expert Introduction Program(G2023202003L), Tianjin Science and Technology Plan Project (24JCZDJC00090)

摘要

摘要: 随着城市空中交通(UAM)概念的提出，为应对可预见的未来该场景下飞行器数量激增，迫切需要研究第2代通用接入收发器(UAT2)数据链的时隙分配算法以获得更大的监视容量。该文以UAT2数据链为研究对象，围绕下行报文的时隙分配管理，分析原始时隙分配算法及局限性。根据报文特性，提出基于状态位图并引入随机漂移机制的改进时隙分配算法。此外，研究提出3种时隙数目扩充传输方案并建立监视容量计算模型，最后对各传输方案在不同时隙分配情况下的性能表现进行仿真分析。结果表明所提优化时隙分配算法在各传输方案达到最大监视容量时，较原始算法报文时隙碰撞概率减小16.14%，时隙使用率提升16.13%，较固定时间窗实时动态时隙分配算法报文时隙碰撞概率减小9.36%，时隙使用率提高10.48%，使得监视容量均有显著提升。
- UAT2数据链 /
- 时隙分配 /
- 监视容量 /
- 随机系统建模
Abstract: Objective With the advancement of Urban Air Mobility (UAM), the rapid growth in aircraft numbers under such scenarios requires improved time slot allocation algorithms for the Universal Access Transceiver 2 (UAT2) data link to enhance surveillance capacity. This study analyzes the original time slot allocation algorithm for UAT2, identifying limitations related to downlink message time slot management. An improved allocation algorithm based on a state bitmap with a random drift mechanism is proposed considering message characteristics. Additionally, three transmission schemes to expand the number of time slots are proposed, and a surveillance capacity calculation model is established. The performance of each transmission scheme under different slot allocation strategies is simulated and evaluated. The research addresses the challenge of insufficient surveillance capacity in UAT2 data link under high-density UAM scenarios and provides an optimized approach for time slot allocation and surveillance performance improvement. Methods The study begins with an analysis of the original UAT2 time slot allocation algorithm, which is limited in high-density aircraft environments due to its pseudo-random mechanism based on geographic coordinates. The proposed algorithm introduces a state bitmap, implemented as a bit vector table where each bit indicates whether the corresponding time slot is occupied. When an aircraft selects a time slot, it first generates a pseudo-random number using the algorithm specified in DO-282C MOPS. The state bitmap is then checked: if the corresponding bit is 0, the time slot is selected; if 1, a piecewise random drift mechanism adjusts the slot selection, as shown in Formula (17). The drift mechanism segments the time slots to distribute selections more evenly and reduce collision probability. The algorithm also applies a slot retention period T, allowing an aircraft to occupy the same time slot for T consecutive UAT frames before reselecting, as defined by Formulas (19)–(21). To further expand time slot availability, three transmission schemes are proposed: Multi-ary Continuous Phase Frequency Shift Keying (MCPFSK) with modulation orders M = 4 and 8, constant modulation index with increased symbol rate, and constant carrier frequency difference with reduced modulation index. The available number of time slots for each scheme is calculated using Formula (26). A surveillance capacity model incorporating bit error rate and collision probability is established, as expressed by Formulas (27)–(30). Results and Discussions Simulation results demonstrate that the improved algorithm substantially outperforms both the original algorithm and the fixed time-window dynamic slot allocation algorithm. Under the original transmission scheme, the improved algorithm reduces slot collision probability by 16.78% and increases slot utilization by 16.12% compared to the original algorithm (Fig. 6, Fig. 7). Relative to the algorithm described in [Ref. 19], the collision probability decreases by 10.80%, and slot utilization increases by 10.48%. For the expanded time slot schemes, when maximum surveillance capacity is reached, the improved algorithm reduces collision probability by 16.14% and increases slot utilization by 16.13% relative to the original algorithm (Table 3). Among these schemes, the 8CPFSK expansion achieves the highest surveillance capacity of 3913, with a slot utilization rate of 79.37% (Fig. 13). Real-time performance testing indicates that even in high-density scenarios, the improved algorithm maintains scheduling times within 120 ms, meeting the real-time operational requirements of UAT2 (Fig. 11). Bit Error Rate (BER) simulations reveal that the MCPFSK scheme provides superior anti-interference performance, whereas the constant carrier frequency difference scheme exhibits the highest BER (Fig. 12). Conclusions A slot allocation algorithm for the UAT2 data link based on state bitmaps and a random drift mechanism is proposed in this study. Compared to the original algorithm, the proposed method reduces slot collision probability by 16.78% and improves slot utilization by 16.12% under the original transmission scheme. When compared to the fixed time-window dynamic slot allocation algorithm described in [Ref. 19], collision probability decreases by 10.80%, and slot utilization increases by 10.48%. Three transmission schemes designed to expand slot availability are also proposed. Simulation results show that as the number of available slots increases, the performance advantage of the improved algorithm becomes more pronounced. Across all transmission schemes, when maximum surveillance capacity is reached, the improved algorithm reduces slot collision probability by approximately 16% and increases slot utilization by approximately 17%. In addition, a surveillance capacity calculation model for the UAT2 data link is established. Quantitative simulation results based on slot collision probability and BER performance confirm that the effective surveillance capacity of the improved algorithm is significantly higher than that of both the original algorithm and the fixed time-window dynamic slot allocation algorithm. It is also demonstrated that the proposed algorithm achieves optimal surveillance performance when all aircraft are equipped with both transmission and reception capabilities. Future research will focus on optimizing slot allocation algorithms for scenarios where aircraft possess only transmission capability.
- UAT2 data link /
- Slot allocation /
- Surveillance capacity /
- Stochastic system modeling

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图 1 UAT帧结构图

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图 2 随机算法下飞行器数量与时隙碰撞概率关系曲线

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图 3 基于状态位图的时隙分配算法工作原理示意

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图 4 隐藏站示意图

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图 5 基于状态位图的时隙分配算法仿真流程

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图 6 未扩容时隙分配仿真结果

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图 7 载波频差/调制指数恒定方案时隙分配仿真结果

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图 9 8CPFSK方案时隙分配仿真结果

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图 8 4CPFSK方案时隙分配仿真结果

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图 10 各算法用时对比图

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图 11 各时隙扩充方案误码性能仿真图

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图 12 各传输方案在不同时隙利用情况下的监视容量值

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表 1 3种时隙数量扩充方案参数

方案	MCPFSK扩充	调制指数恒定	载波频差恒定
原理	将码元信号增大为M进制，携带更多信息	调制指数不变的情况下适当增加调制速率	载波频差不变的情况下适当增加调制速率
消息速率(Mbps)	2.08(M=4)/ 3.125(M=8)	1.25	1.25
时隙大小(μs)	140(4)/90(8)	230	230
时隙总数	5714(4)/8880(8)	3478	3478

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表 2 各扩充方案等效时隙数量

方案	4CPFSK	8CPFSK	调制指数恒定	载波频差恒定
“等效时隙”数	3170	4930	1930	1930

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表 3 各方案在两种算法下的监视容量和时隙利用情况

方案	理想监视容量值	基于位置的伪随机原始时隙分配算法			基于固定时间窗和实时动态时隙分配算法			基于状态位图的优化时隙分配算法
方案	理想监视容量值	时隙碰撞概率(%)	监视容量	时隙使用率(%)	时隙碰撞概率(%)	监视容量	时隙使用率(%)	时隙碰撞概率(%)	监视容量	时隙使用率(%)
原始传输方案	1639	35.75	1053	61.88	29.77	1151	67.52	18.97	1328	78.00
调制指数恒定方案 (R_b=1.25 Mbps)	1916	36.53	1216	62.95	29.80	1345	68.59	20.35	1526	79.07
载波频差恒定方案(h=0.5)	1917	36.57	1216	62.95	29.84	1345	68.59	20.34	1527	79.07
4CPFSK扩充方案	3168	36.80	2002	63.22	30.02	2217	68.86	20.61	2515	79.34
8CPFSK扩充方案	4937	36.88	3116	63.24	30.10	3451	68.89	20.74	3913	79.37

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参考文献(21)

[1]	FAA. Concept of operations v2.0[R]. Washington DC, USA: FAA, 2023.
[2]	李诚龙, 屈文秋, 李彦冬, 等. 面向eVTOL航空器的城市空中运输交通管理综述[J]. 交通运输工程学报, 2020, 20(4): 35–54. doi: 10.19818/j.cnki.1671-1637.2020.04.003. LI Chenglong, QU Wenqiu, LI Yandong, et al. Overview of traffic management of urban air mobility (UAM) with eVTOL aircraft[J]. Journal of Traffic and Transportation Engineering, 2020, 20(4): 35–54. doi: 10.19818/j.cnki.1671-1637.2020.04.003.
[3]	WANG Leilei, DENG Xiaoheng, GUI Jinsong, et al. A review of urban air mobility-enabled intelligent transportation systems: Mechanisms, applications and challenges[J]. Journal of Systems Architecture, 2023, 141: 102902. doi: 10.1016/j.sysarc.2023.102902.
[4]	廖小罕, 屈文秋, 徐晨晨, 等. 城市空中交通及其新型基础设施低空公共航路研究综述[J]. 航空学报, 2023, 44(24): 028521. doi: 10.7527/S1000-6893.2023.28521. LIAO Xiaohan, QU Wenqiu, XU Chenchen, et al. A review of urban air mobility and its new infrastructure low-altitude public routes[J]. Acta Aeronautica et Astronautica Sinica, 2023, 44(24): 028521. doi: 10.7527/S1000-6893.2023.28521.
[5]	汤新民, 顾俊伟, 刘冰, 等. 低空监视技术及其发展趋势综述[J]. 南京航空航天大学学报, 2024, 56(6): 973–993. doi: 10.16356/j.1005-2615.2024.06.001. TANG Xinmin, GU Junwei, LIU Bing, et al. Review on low-altitude surveillance technology and its development trend[J]. Journal of Nanjing University of Aeronautics & Astronautics, 2024, 56(6): 973–993. doi: 10.16356/j.1005-2615.2024.06.001.
[6]	中国民航局. IB-TM-2024-01 民用微轻小型无人驾驶航空器运行识别最低性能要求(试行)[S]. 北京: 中国民航局. CAAC. IB-TM-2024-01 Civil micro and light small UAS operation identification minimum operational performance standards (provisional)[S]. Beijing: CAAC.
[7]	FAA, Department of Transportation. FAA-2019-1100 Policy statement for the reported geometric altitude of the control station of a standard remote identification unmanned aircraft[S]. Washington: FAA, DOT, 2019.
[8]	NASA. Reliable, secure, and scalable communications, Navigation, and Surveillance (CNS) options for urban air mobility (UAM)[R]. Cleveland, USA: NASA, 2020.
[9]	STOUFFER V L, COTTON W, IRVINE T, et al. Enabling urban air mobility through communications and cooperative surveillance[C]. AIAA Aviation 2021 Forum, Reston, USA, 2021: 2–16. doi: 10.2514/6.2021-3172.
[10]	FAA. Unmanned aircraft systems (UAS) traffic management (UTM)[R]. Washington: FAA, 2020.
[11]	RTCA. RTCA-DO-282C Minimum Operational Performance Standards (MOPS) for universal access transceiver (UAT) automatic dependent surveillance-broadcast (ADS-B)[S]. Washington: RTCA Inc, 2022.
[12]	孙伟杰. 数据链网络动态时隙分配与优化研究[D]. [硕士论文], 国防科技大学, 2019. doi: 10.27052/d.cnki.gzjgu.2019.000681. SUN Weijie. Research on dynamic slot allocation and optimization of data link network[D]. [Master dissertation], National University of Defense Technology, 2019. doi: 10.27052/d.cnki.gzjgu.2019.000681.
[13]	LIU Lei, LIU Yiming, WANG Zhaowei, et al. Design of dynamic TDMA protocols for tactical data link[C]. The 12th International Conference on Communications and Networking, Xi’an, China, 2017: 166–175. doi: 10.1007/978-3-319-78130-3_18.
[14]	王自强. 低轨卫星数据链动态时隙分配与网络规划研究[D]. [硕士论文], 西安电子科技大学, 2022. doi: 10.27389/d.cnki.gxadu.2022.001624. WANG Ziqiang. Research on dynamic time slot allocation and network planning for low-orbit satellite data link[D]. [Master dissertation], Xidian University, 2022. doi: 10.27389/d.cnki.gxadu.2022.001624.
[15]	YU Xueyong. 5G wireless networking connection and playback technology assist the low-latency propagation of new media[J]. Journal of Sensors, 2021, 2021(1): 3082280. doi: 10.1155/2021/3082280.
[16]	LEE J S, YOO Y S, CHOI H, et al. Group connectivity-based UAV positioning and data slot allocation for tactical MANET[J]. IEEE Access, 2020, 8: 220570–220584. doi: 10.1109/ACCESS.2020.3042795.
[17]	朱宇挺, 苏焕坤, 冯小东, 等. 基于改进差分算法的数据链时隙分配方法[J]. 系统仿真学报, 2024, 36(5): 1242–1250. doi: 10.16182/j.issn1004731x.joss.23-0095. ZHU Yuting, SU Huankun, FENG Xiaodong, et al. Time slot allocation method of data link based on improved difference algorithm[J]. Journal of System Simulation, 2024, 36(5): 1242–1250. doi: 10.16182/j.issn1004731x.joss.23-0095.
[18]	苗帅. 基于NS2的UAT数据链仿真设计与实现[D]. [硕士论文], 北京邮电大学, 2012. MIAO Shuai. The simulation of UAT data link design and implementation[D]. [Master dissertation], Beijing University of Posts and Telecommunications, 2012.
[19]	黄裕文, 张炼, 刘元春. UAT数据链上行报文时隙实时动态分配算法研究[J]. 现代雷达, 2017, 39(5): 25–29. doi: 10.16592/j.cnki.1004-7859.2017.05.006. HUANG Yuwen, ZHANG Lian, and LIU Yuanchun. A study on real time dynamic allocation algorithm for uplink messages of UAT data link[J]. Modern Radar, 2017, 39(5): 25–29. doi: 10.16592/j.cnki.1004-7859.2017.05.006.
[20]	樊昌信, 曹丽娜. 通信原理[M]. 7版. 北京: 国防工业出版社, 2012: 182–241. FAN Changxin and CAO Lina. Principles of Communications[M]. The 7th ed. Beijing: National Defense Industry Press, 2012: 182–241.
[21]	文旌宇, 汤新民, 汤盛家, 等. UAT2数据链监视容量扩充研究[J]. 北京航空航天大学学报, 2024, 1–15. doi: 10.13700/j.bh.1001-5965.2024.0534. WEN Jingyu, TANG Xinmin, TANG Shengjia, et al. Research on the expansion of surveillance capacity for UAT2 data link[J]. Journal of Beijing University of Aeronautics and Astronautics, 2024, 1–15. doi: 10.13700/j.bh.1001-5965.2024.0534.