Robust Adaptive Interference Cancellation with Controlled Leakage Constraint in Non-Stationary Environments

MA Yufeng; HE Fangmin; YANG Kai; LIANG Jiaqi; LIU Hongbo

doi:10.12263/DZXB.20251074

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Robust Adaptive Interference Cancellation with Controlled Leakage Constraint in Non-Stationary Environments

PAPERS | 更新时间：2026-06-16

- Robust Adaptive Interference Cancellation with Controlled Leakage Constraint in Non-Stationary Environments
- ACTA ELECTRONICA SINICA Vol. 54, Issue 3, Pages: 1194-1208(2026)
- 作者机构：
  
  电磁能技术全国重点实验室，湖北武汉 430000
- 作者简介：
- 基金信息：
  
  Stable Support for Scientific Research Projects in National Key Laboratories(614221723030301);National Natural Science Foundation of China Youth Science Fund Project(62301586)
- DOI：10.12263/DZXB.20251074
  CLC： TN975;
- Received：24 December 2025，
  
  Accepted：16 January 2026，
  
  Published：25 March 2026
- 稿件说明：
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马宇峰, 何方敏, 杨凯, 等. 非平稳环境下基于可控泄漏约束的鲁棒自适应干扰对消算法[J]. 电子学报, 2026, 54(03): 1194-1208.

MA Yufeng, HE Fangmin, YANG Kai, et al. Robust Adaptive Interference Cancellation with Controlled Leakage Constraint in Non-Stationary Environments[J]. Acta Electronica Sinica, 2026, 54(03): 1194-1208.
马宇峰, 何方敏, 杨凯, 等. 非平稳环境下基于可控泄漏约束的鲁棒自适应干扰对消算法[J]. 电子学报, 2026, 54(03): 1194-1208. DOI：10.12263/DZXB.20251074

MA Yufeng, HE Fangmin, YANG Kai, et al. Robust Adaptive Interference Cancellation with Controlled Leakage Constraint in Non-Stationary Environments[J]. Acta Electronica Sinica, 2026, 54(03): 1194-1208. DOI：10.12263/DZXB.20251074

摘要

本文提出一种基于可控泄漏约束的鲁棒自适应干扰对消算法（Robust Adaptive Interference Cancellation with Controlled Leakage Constraint，RAIC-CLC），旨在解决阵列误差导致的导向矢量失配问题及非平稳环境下的恶意干扰挑战。针对由期望信号导向矢量失配引起的干扰对消后期望信号增益下降的问题，提出一种可控泄漏约束机制，该机制通过将约束干扰对消后期望信号增益不低于预设阈值，以显式调节信号泄漏水平，实现了期望信号增益保持前提下干扰信号的充分抑制。理论分析表明：引入可控泄漏约束因子可显著降低期望信号增益损失；进一步推导出最优泄漏约束因子的闭式解，实现不同工作条件下干扰抑制能力与期望信号保真度之间的自适应权衡。针对非平稳环境中因干扰源移动、信道变化等因素导致接收的干扰信号统计特性时变、需要低复杂度算法实现干扰信号动态抑制的问题，设计了一种基于梯度投影的迭代优化算法。该算法基于实时输入的数据流快拍，采用瞬时梯度下降法和梯度投影法，完成不等式约束条件下权值矢量的实时更新，显著降低了计算复杂度，达成了算法对非平稳环境下干扰信号的实时跟踪抑制，适用于现场可编程门阵列（Field Programmable Gate Array，FPGA）平台高效实现。仿真结果表明：所提方法在多种典型算法中表现优异，包括传统最小输出功率法（Minimum Output Powe，MOP）、带正则化惩罚项的最小输出功率法（Minimum Output Power with Regularization Penalty，MOP-RP）、最小方差无失真响应（Minimum Variance Distortionless Response，MVDR）算法、广义旁瓣相消法（Generalized Sidelobe Canceller，GSC）及基于特征值替换的协方差矩阵重建（Eigenpair Substitution-based Covariance Matrix Reconstruction，ESCMR）方法，尤其在低快拍数与高信噪比（Signal-to-Noise Ratio，SNR）等具有挑战性条件下展现出更强的鲁棒性。

Abstract

This paper proposes a robust adaptive interference cancellation algorithm based on a controllable leakage constraint

aiming to address the steering vector mismatch caused by array errors and the challenge of malicious interference in non‑stationary environments. To mitigate the degradation of desired signal gain after interference cancellation under steering vector mismatch

a controllable leakage constraint mechanism is introduced. By constraining the post‑cancellation desired signal gain to be no lower than a preset threshold

this mechanism explicitly regulates the signal leakage level

thereby achieving sufficient interference suppression while preserving the desired signal gain. Theoretical analysis indicates that introducing a controllable leakage constraint factor can significantly reduce the loss in desired signal gain. Furthermore

a closed‑form solution for the optimal leakage constraint factor is derived

enabling an adaptive trade‑off between interference suppression capability and desired signal fidelity under various operating conditions. To tackle the problem that time‑varying statistical characteristics of received interference signals due to factors such as moving interference sources and channel variations in non‑stationary environments require low‑complexity algorithms for dynamic interference suppression

an iterative optimization algorithm based on gradient projection is designed. Operating on snapshot data from real‑time input streams

the algorithm employs instantaneous gradient descent combined with gradient projection to update the weight vector in real time under inequality constraints

significantly reducing computational complexity. This approach enables real‑time tracking and suppression of interference in non‑stationary environments and is suitable for efficient implementation on field programmable gate array (FPGA) platforms. Simulation results demonstrate that the proposed method outperforms several representative algorithms

including the traditional minimum output power (MOP)

minimum output power with regularization penalty (MOP‑RP)

minimum variance distortionless response (MVDR)

generalized sidelobe canceller (GSC)

and eigenpair substitution‑based covariance matrix reconstruction (ESCMR). It exhibits stronger robustness

particularly under challenging conditions such as low snapshot counts and high signal‑to‑noise ratio (SNR).

关键词

Keywords

references

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