Adaptive Suppression Algorithm for Communication Signal Clutter Interference under Integrated Sensing and Communication System

DOI: https://doi.org/10.62517/jbdc.202601324

Author(s)

Pengzhou Huang

Affiliation(s)

School of Electronic Information and Communications, Huazhong University of Science and Technology, Wuhan, Hubei, China

Abstract

Integrated sensing and communication (ISAC) systems integrate communication and sensing functionalities by sharing spectrum and hardware resources. Nevertheless, strong clutter components generated by ground object reflection of communication signals will submerge weak target echoes, severely degrading sensing performance. To address the failure of fixed-coefficient suppression methods in non-stationary clutter environments, this paper first analyzes the distribution discrepancies between clutter and target echoes in the range-Doppler domain, and then proposes an adaptive clutter suppression algorithm combining subspace projection and recursive least squares (RLS) estimation. Leveraging the structural property that clutter concentrates in the zero-Doppler region, the algorithm constructs a clutter subspace. It updates projection coefficients online via a variable forgetting factor to track environmental variations, and reduces iterative computational complexity to nearly quadratic order by exploiting the low-rank characteristic of the covariance matrix. Simulation results reveal that under an urban macro-cell non-stationary clutter scenario with a signal-to-clutter ratio (SCR) of -15 dB, the proposed algorithm improves the signal-to-interference-plus-noise ratio (SINR) by approximately 8 dB compared with classical cancellation methods. With a false alarm probability constraint of 10⁻⁶, the target detection probability reaches 0.92, and the processing latency is less than 0.5 ms. The algorithm balances suppression performance and real-time requirements, providing a feasible scheme for the engineering implementation of the sensing link in ISAC systems.

Keywords

Integrated Sensing and Communication; Clutter Suppression; Subspace Projection; Recursive Least Squares; Interference Cancellation

References

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