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Phase compensation transform for human detection with LFMCW radar

机译:LFMCW雷达用于人体检测的相位补偿变换

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Efficiently accumulating the power of human echo using a linear frequency modulated continuous wave radar is difficult owing to the spread of micro-Doppler due to the varying velocity of human body motion. Consequently, the detection performance for human targets degrades. A coherent integration algorithm called phase compensation transform (PCT) is proposed to solve this issue. In PCT, the beat signal of a human target is derived for an LFMCW radar based on the Boulic model. The nonlinear phase characteristic of the beat signal caused by micro-Doppler from human motion is analyzed. The phase compensation signal is constructed to compensate the nonlinear phase from micro-Doppler during a coherent processing interval. The compensated range cell is fast Fourier transformed, and the Doppler spread resulting from periodic micro-Doppler is integrated. The performance of PCT is evaluated and compared with that of other methods. Simulation results show that PCT exhibits higher integration efficiency than moving target detection (MTD) and optimized nonlinear-phase methods. Experiment results from the LFMCW radar system demonstrate that the detection signal-to-noise ratio of PCT increases 5dB compared with that of MTD method. Besides, PCT can estimate human motion parameters simultaneously, including average radial velocity, gait frequency, and torso initial phase.
机译:由于微多普勒的传播,由于人体运动速度的变化,使用线性调频连续波雷达难以有效地积累人类回声的功率。因此,对人类目标的检测性能下降。为了解决这个问题,提出了一种称为相补偿变换(PCT)的相干积分算法。在PCT中,基于Boulic模型为LFMCW雷达推导了人类目标的拍子信号。分析了由人类运动引起的微多普勒引起的拍信号的非线性相位特性。构造相位补偿信号以在相干处理间隔期间补偿来自微多普勒的非线性相位。补偿后的距离像元经过快速傅立叶变换,并且对由周期性微多普勒产生的多普勒扩展进行了积分。评估PCT的性能并将其与其他方法进行比较。仿真结果表明,PCT具有比移动目标检测(MTD)和优化的非线性相位方法更高的集成效率。 LFMCW雷达系统的实验结果表明,与MTD方法相比,PCT的检测信噪比提高了5dB。此外,PCT可以同时估计人体运动参数,包括平均径向速度,步态频率和躯干初始阶段。

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