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Performance enhancement of wide-band radar signals, using a new adaptive CAMP algorithm in compressive sensing

机译:宽带雷达信号的性能增强,在压缩传感中使用新的自适应CAMP算法

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High resolution radar signals demands the use of high speed signal processor. Due to the sparse nature of radar signals, Compressive sensing (CS) enables the wide-band radar signals to be sampled at a low sampling rate, rather than a high sampling rate. This is attained through the use of a sparse sensing matrix. Complex approximate message passing (CAMP) algorithm is vastly used in reconstructing radar signals, because of its low complexity for real-time recovery and suitable for hardware integration. However, the CAMP algorithm achieves low detection performance at low Signal to Noise Ratios (SNRs). This paper proposes a new adaptive CAMP algorithm based on signal threshold, in order to solve the aforementioned shortcoming. Through simulation, the new adaptive CAMP is compared against the classical CAMP and the digital matched filter (DMF) algorithm using the Receiver Operating Characteristic (ROC) curves. The receivers operating characteristic curves (ROC) show that the new adaptive CAMP improves the probability of detection at lower SNRs.
机译:高分辨率雷达信号要求使用高速信号处理器。由于雷达信号的稀疏性,压缩检测(CS)使得宽带雷达信号能够以低采样速率进行采样,而不是高采样速率。这是通过使用稀疏感测矩阵实现的。复杂的近似消息传递(CAMP)算法在重建雷达信号中广泛用于重建雷达信号,因为它对实时恢复的低复杂性并适合硬件集成。然而,CAMP算法在低信噪比下实现了低的检测性能(SNR)。本文提出了一种基于信号阈值的新自适应CAMP算法,以解决上述缺点。通过仿真,使用接收器操作特性(ROC)曲线将新的自适应阵营与经典阵营和数字匹配滤波器(DMF)算法进行比较。操作特征曲线(ROC)的接收器表明,新的自适应CAMP在较低的SNR处改善了检测的概率。

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