面向远距离高速无人机检测的OFDM通信感知一体化参考信号设计

唐爱民; 王书涵; 曲文泽

doi:10.12000/JR24240

面向远距离高速无人机检测的OFDM通信感知一体化参考信号设计

DOI: 10.12000/JR24240

1.
上海交通大学上海 200240
2.
联发科技股份有限公司北京 100015

详细信息

作者简介:
唐爱民，博士，助理研究员，主要研究方向为B5G/6G网络、通信感知一体化技术、全双工通信

王书涵，硕士生，主要研究方向为通信感知一体化技术

曲文泽，硕士，研究员，主要研究方向为通信感知一体化技术

通讯作者:
唐爱民 tangaiming@sjtu.edu.cn

责任主编：杨杰 Corresponding Editor: YANG Jie
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出版历程
- 收稿日期: 2024-12-03

Reference Signal Design in OFDM ISAC for Long-Range and High-Speed UAV Detection

1.
Shanghai Jiao Tong University, Shanghai 200240, China
2.
MediaTek Inc., Beijing 100015, China

More Information

Corresponding author: TANG Aimin, tangaiming@sjtu.edu.cn

摘要

摘要: 随着低空经济的兴起，无人机的通信和检测问题受到了广泛的关注。该文研究了OFDM通信感知一体化中的感知参考信号设计，用于远距离高速无人机的检测。为了实现无人机在远距离和高速度情况下的不模糊检测，传统的参考信号设计需要较密的感知参考信号布置，从而带来较大的资源开销。此外，基于OFDM波形的远距离检测，还面临码间串扰的挑战。首先，针对远距离检测的问题，该文设计了支持远距离检测且抗码间串扰的感知参考信号模式，可以在较少资源开销下达到系统的最大不模糊检测距离。然后，基于前述参考信号的排布模式，针对高速度检测的问题，该文在基于中国剩余定理消除模糊方法的基础上，引入距离变化率。通过合理的参考信号配置与幽灵目标消除算法，可以在较小的资源开销下，大幅增加不模糊检测速度，且有效避免幽灵目标的产生。上述方法的有效性最后通过仿真进行了验证。仿真结果表明，针对远距离高速目标的检测，相比于传统方法，该文所提的方法可降低72%的参考信号开销。
- 通信感知一体化 /
- 参考信号设计 /
- 无人机 /
- 雷达感知 /
- 正交频分复用
Abstract: With the emergence of the low-altitude economy, the communication and detection issues of unmanned aerial vehicles (UAVs) have gained considerable attention. This paper investigates sensing reference signal design for integrated sensing and communication (ISAC) in orthogonal frequency division multiplexing (OFDM) systems aimed at detecting long-range, high-speed UAVs. To address the ambiguity problem in long-range and high-speed UAV detection, traditional reference signal designs require densely arranged reference signals, leading to significant resource overhead. In addition, long-range detection based on OFDM waveforms faces challenges from inter-symbol interference (ISI). To address these issues, this paper first proposes a reference signal pattern that supports long-range detection and resists ISI, achieving the maximum unambiguous detection range of the system with reduced resource overhead. Then, to address the challenge of high-speed detection, the paper incorporates range-rate into the Chinese Remainder Theorem-based method. Through the proper configuration of sensing reference signals and the cancellation of ghost targets, this approach significantly increases the unambiguous detection velocity while minimizing resource usage and avoiding the generation of ghost targets. The effectiveness of the proposed methods is validated through simulations. Simulation results show that compared with the traditional sensing reference signal design, our proposed scheme can reduce 72% overhead of reference signals for long-range and high-speed UAV detections.
- Integrated sensing and communications /
- Reference signal design /
- Unmanned Aerial Vehicle (UAV) /
- Radar sensing /
- Orthogonal Frequency Division Multiplexing (OFDM)

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图 1 系统模型示意图

Figure 1. Illustration of the system model

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图 2 接收OFDM符号的时间轴

Figure 2. The timeline for received OFDM symbols

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图 3 类型1的RS设计示意

Figure 3. Illustration of RS design for Type 1

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图 4 类型2的RS设计示意

Figure 4. Illustration of RS design for Type 2

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图 5 面向距离模糊问题的RS设计示例

Figure 5. Illustration of RS design resolving ambiguity problem in long distance sensing

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图 6 模糊函数

Figure 6. Ambiguity function

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图 7 RD谱和可检测范围

Figure 7. RD map and detection range

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图 8 基于中国剩余定理的RS设计示意

Figure 8. Illustration of RS design based on CRT

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图 9 基于中国剩余定理的多目标模糊速度消除示意

Figure 9. Illustration of resolving velocity ambiguity in multi-target scenarios based on CRT

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图 10 不同RS设计对通信开销的影响

Figure 10. Impact of different RS designs on communication overhead

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图 11 ：不同RS设计对通信数据传输速率的影响

Figure 11. Impact of different RS designs on communication data rate

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图 12 本文提出的速度模糊性消除方法在不同参数下的表现

Figure 12. Performance of our proposed method for addressing velocity ambiguity under different setups

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图 13 幽灵目标的性能

Figure 13. Performance of reducing ghost targets

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1 基于中国剩余定理和距离变化率的目标检测流程

1. Target detection procedure based on CRT and range-rate

输入：两次CPI的RD谱$ {\text{RD}}_{1} $, $ {\text{RD}}_{2} $
输出：估计的距离-速度对$ ({R}^{i},{V}^{i})\text{,}i=1,2,\cdots,I $
1. 从$ {\text{RD}}_{1} $获取峰值，记为$ \left({R}_{1}^{i},{V}_{\mathrm{a}1}^{i}\right)\text{,}i=1,2,\cdots I $，根据$ {V}_{\mathrm{a}1}^{i} $和$ {V}_{\mathrm{u}1} $得到第i个目标在第1个CPI的速度可能取值集合$ {\mathbb{S}}_{1}^{i} $
2. 从$ {\text{RD}}_{2} $获取峰值，记为$ \left({R}_{2}^{j},{V}_{\mathrm{a}2}^{j}\right)\text{,}j=1,2,\cdots,I $，根据$ {V}_{\mathrm{a}2}^{j} $和$ {V}_{\mathrm{u}2} $得到第j个目标在第2个CPI的速度可能取值集合$ {\mathbb{S}}_{2}^{j} $
3. 通过聚合的方式比较两个CPI获得的所有速度可能取值，即比较集合$ \left\{x\right\|x\in {\mathbb{S}}_{1}^{i}\text{,}i=1,2,\cdots I\} $和$ \left\{x\|x\in {\mathbb{S}}_{2}^{j}\text{,}j=1,2,\cdots I\right\} $，如果有一致　或接近的值，记录这个速度和它对应的在两个CPI的距离$ ({V}^{k},{R}_{1}^{k},{R}_{2}^{k})\text{,}k=1,2,\cdots,K(K\ge I) $
4. 如果$ K > I $，根据$ {\hat{V}}^{k}=\dfrac{{R}_{2}^{k}-{R}_{1}^{k}}{{\Delta }t} $计算第k个目标的距离变化率，如果$ {\hat{V}}^{k},{V}^{k} $相差不超过$ \mathrm{m}\mathrm{i}\mathrm{n}({V}_{\mathrm{u}1},{V}_{\mathrm{u}2}) $，保留$ ({V}^{k},{R}_{1}^{k},{R}_{2}^{k}) $数组；否　则，抛弃数组
5. 输出$ ({R}^{k},{V}^{k})=\left(\right({R}_{1}^{k}+{R}_{2}^{k})/2,{V}^{k})\text{,}\;k=1,2,\cdots,I $

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表 1 系统仿真物理层参数

Table 1. Physical layer parameters for system simulation

参数	数值	参数	数值
中心频率 $ {f}_{\mathrm{c}} $	28 GHz	带宽 B	50 MHz
子载波间隔 $ {{\Delta }}_{\mathrm{f}} $	120 kHz	数据持续时长 $ {T}_{\mathrm{d}} $	8.3 μs
CP时长$ {T}_{\mathrm{c}\mathrm{p}} $	0.59 μs	符号持续时长 $ {T}_{\mathrm{s}\mathrm{y}\mathrm{m}} $	8.9 μs
子载波个数 $ {N}_{\mathrm{c}} $	348	OFDM符号个数 $ {N}_{\mathrm{s}} $	112

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