针对自适应滤波的组网雷达欺骗干扰优化策略

针对组网雷达系统在跟踪目标发生机动时采用自适应滤波来估计目标状态的特点，在点迹融合数据处理结构的组网雷达基础上提出了一种欺骗干扰优化策略。根据状态和量测方程描述了组网雷达跟踪目标的模型，同时建立了跟踪机动目标的自适应滤波模型。在此基础上，建立了欺骗干扰模型，并在目标机动检测约束下，推导了虚假目标欺骗干扰对于组网雷达融合中心的自适应滤波估计误差协方差的影响关系式。用误差协方差矩阵的迹来量化欺骗干扰效果，并以此为优化的目标函数。使用矩阵Schur补理论把约束条件转换为线性矩阵不等式，将欺骗干扰优化策略转化为求解半定规划凸优化问题。仿真结果验证了所提欺骗干扰优化策略的有效性。

Deception jamming optimization strategy against adaptive filtering for netted radar

Aiming at the fact that the adaptive filtering is used to estimate the target state in the netted radar system when the tracking target is maneuvering, a deception jamming optimization strategy was proposed on the basis of the netted radar with the plot fusion data processing structure. The model of the target tracked by the netted radar was described according to the state and measurement equation, the adaptive filtering model of tracking maneuvering target was established at the same time. Based on all this, a deception jamming model was established, and the influence relationship of false target deception jamming against the adaptive filtering state estimation error covariance of the netted radar fusion center was derived under the constraint of target maneuver detection. The trace of the error covariance matrix was used to quantify the effect of deception jamming and stand for the objective function of optimization. The Schur complement theory of matrix was used to change the constraints to a linear matrix inequality, and a deception jamming optimization strategy was changed in the solution to the convex optimization problem for semidefinite programming. The simulation results verify the effectiveness of the proposed deception jamming optimization strategy.