Yuan, Q., Zhuge, S., Lin, Z., Ma, Y., & Zeng, Y. (2025). Kalman Filtering based Target Tracking for Multistatic Sensing in ISAC Systems. 2025 IEEE International Symposium on Circuits and Systems (ISCAS), 1–5. https://doi.org/10.1109/iscas56072.2025.11043835
Abstract:
The advancement of Integrated Sensing and Communication (ISAC) has facilitated the adoption of target tracking technologies, yet most existing research focuses on waveform design rather than specific tracking algorithms within ISAC systems. To address this gap, this paper proposes an effective target tracking method based on Kalman filter (KF) algorithms within the ISAC framework. The method filters noisy radar measurements, such as bistatic range (BR), bistatic range rate (BRR), and direction of arrival (DOA), to enhance tracking accuracy. Performance is assessed by using trajectory maps and root-mean-square
error (RMSE) curves, demonstrating that the proposed method significantly improves estimation
accuracy while increasing robustness to measurement noise, especially in DOA. Compared to our previously
proposed geometric target localization method, this approach delivers superior tracking performance,
making it highly suitable for real-time applications in ISAC systems.
License type:
Publisher Copyright
Funding Info:
This research / project is supported by the National Research Foundation, Singapore and Infocomm Media Development Authority under its Future Communications Research & Development Programme. - Integrated Sensing and Communication in Millimetre-Wave and Terahertz bands for B5G and 6G
Grant Reference no. : FCP-NUS-RG-2022- 018