Alternating EKF tracking and prediction assisted beamforming design of air-to-air integrated sensing and communications

ZHAO Tiegang; YU Qiyue

doi:10.13471/j.cnki.acta.snus.ZR20240292

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Alternating EKF tracking and prediction assisted beamforming design of air-to-air integrated sensing and communications

Column of integrated sensing and communication | 更新时间：2025-11-14

- Alternating EKF tracking and prediction assisted beamforming design of air-to-air integrated sensing and communications
- Acta Scientiarum Naturalium Universitatis Sunyatseni Vol. 64, Issue 4, Pages: 12-21(2025)
- 作者机构：
  
  哈尔滨工业大学电子与信息工程学院，黑龙江哈尔滨 150001
- 作者简介：
- 基金信息：
- DOI：10.13471/j.cnki.acta.snus.ZR20240292
  CLC： TN929.5
- Received：30 September 2024，
  
  Accepted：16 December 2024，
  
  Published Online：07 April 2025，
  
  Published：25 July 2025
- 稿件说明：
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赵铁刚,于启月.交替EKF跟踪预测辅助的机间通信感知一体化波束形成设计[J].中山大学学报(自然科学版)(中英文),2025,64(04):12-21.

ZHAO Tiegang,YU Qiyue.Alternating EKF tracking and prediction assisted beamforming design of air-to-air integrated sensing and communications[J].Acta Scientiarum Naturalium Universitatis Sunyatseni,2025,64(04):12-21.
赵铁刚,于启月.交替EKF跟踪预测辅助的机间通信感知一体化波束形成设计[J].中山大学学报(自然科学版)(中英文),2025,64(04):12-21. DOI： 10.13471/j.cnki.acta.snus.ZR20240292.

ZHAO Tiegang,YU Qiyue.Alternating EKF tracking and prediction assisted beamforming design of air-to-air integrated sensing and communications[J].Acta Scientiarum Naturalium Universitatis Sunyatseni,2025,64(04):12-21. DOI： 10.13471/j.cnki.acta.snus.ZR20240292.

摘要

针对高空机间通信感知一体化场景，首先构建了多机之间的通信感知系统模型，并基于双机之间的空间几何关系，推导了可用于跟踪的状态预测模型与量测模型。对模型进行了线性化处理，并将传统的扩展卡尔曼滤波（EKF）算法改进为交替EKF多波束跟踪预测算法，以实现对多个目标的独立跟踪与预测。并通过降低模型中转换矩阵的阶数，进一步减少计算复杂度。通过交替EKF跟踪预测算法实时提供的状态信息，在功率受限条件下，利用数字波束形成技术实现了多机通信的速率最大化，并得到了设计的闭合解形式。最后，仿真结果验证了所提出的交替EKF多波束跟踪预测算法的优越性。

Abstract

This paper investigates the signal tracking and prediction in the high-altitude air-to-air（A2A） ISAC scenario. First of all， an A2A ISAC system model is established， and state prediction and measurement models suitable for tracking are derived based on the spatial geometric relationship between two aircraft. Then， the model is linearized， and the traditional EKF algorithm is improved to an alternating EKF multi-beam tracking and prediction algorithm， which enables independent tracking and prediction of multiple targets. Furthermore， by reducing the order of the transformation matrix within the model， we further decrease the computational complexity. Utilizing the real-time state information provided by the alternating EKF tracking and prediction algorithm， we maximize the communication rate among multiple aircraft under power-constrained conditions through digital beamforming design， and we present a closed-form solution for the design. Simulation results demonstrate that the proposed algorithm significantly improves tracking accuracy while extending the time span of multi-target tracking and predictions.

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references

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ZHAO Tiegang

YU Qiyue

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LI Xinrui

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Southeast University / National Mobile Communications Research Laboratory

Purple Mountain Laboratories

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