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首页> 外文期刊>EURASIP journal on advances in signal processing >Robust adaptive monopulse algorithm based on main lobe constraints and subspace tracking
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Robust adaptive monopulse algorithm based on main lobe constraints and subspace tracking

机译:基于主瓣约束和子空间跟踪的鲁棒自适应单脉冲算法

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In continuous wave (CW) radar and high pulse repetition frequency pulse-Doppler (HPRF-PD) radar, the interference plus noise sample snapshots are hard to be obtained. The desired signal in the received snapshots makes the LCMV-based adaptive monopulse algorithm sensitive to pattern look direction error. A linearly constrained subarray robust adaptive monopulse algorithm based on main lobe maintenance constraint and subspace tracking is developed in this paper. The constraint of main lobe maintenance is obtained by signal subspace projection. The bi-iterative least-square (Bi-LS) subspace tracking is used to update the signal subspace, and a power-associated method is developed to determine the dimension of the projection subspace automatically. The proposed robust adaptive monopulse algorithm can achieve high-angle estimation accuracy and good robustness to look direction error while expending only one additional degree of freedom compared to conventional LCMV-based method.
机译:在连续波(CW)雷达和高脉冲重复频率脉冲多普勒(HPRF-PD)雷达中,很难获得干扰加噪声样本的快照。接收到的快照中的所需信号使基于LCMV的自适应单脉冲算法对图案外观方向误差敏感。提出了一种基于主瓣维持约束和子空间跟踪的线性约束子阵列鲁棒自适应单脉冲算法。通过信号子空间投影获得主瓣维持的约束。使用双向最小二乘(Bi-LS)子空间跟踪来更新信号子空间,并开发了一种与功率相关的方法来自动确定投影子空间的尺寸。与传统的基于LCMV的方法相比,所提出的鲁棒自适应单脉冲算法可以实现高角度估计精度和良好的鲁棒性,以观察方向误差,同时仅扩展了一个额外的自由度。

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