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Axis rotation MTD algorithm for weak target detection

机译:用于弱目标检测的轴旋转MTD算法

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摘要

Weak target's range migration often happens for long time integration in radar detection. To compensate for linear range migration and detect weak targets effectively, a novel coherent integration detection algorithm, axis rotation moving target detection (AR-MTD), is proposed. The AR-MTD eliminates the linear range migration by rotating two-dimensional echoes data plane, and realizes coherent integration via moving target detection (MTD). As the target's resident time in a single range cell increases, the integration gain is improved clearly. Numerical experiments are presented to verify the reduction in the computational complexity of AR-MTD by selecting the velocity variation regions. Also, it is shown that the detection probability of AR-MTD is improved by nearly 20% when input signal-to-noise ratio (SNR) is -40 dB.
机译:弱目标的距离迁移通常会在雷达检测中进行长时间集成。为了补偿线性范围偏移并有效地检测弱目标,提出了一种新的相干积分检测算法,即轴旋转运动目标检测(AR-MTD)。 AR-MTD通过旋转二维回波数据平面消除了线性范围偏移,并通过移动目标检测(MTD)实现了相干集成。随着目标在单个测距单元中的驻留时间增加,积分增益会明显提高。通过选择速度变化区域,进行数值实验以验证AR-MTD的计算复杂度的降低。此外,还表明,当输入信噪比(SNR)为-40 dB时,AR-MTD的检测概率提高了近20%。

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