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首页> 外文期刊>International journal of information acquisition >APPROACH OF MULTIPLE MOVING TARGETS DETECTION FOR MICROWAVE SURVEILLANCE SENSORS
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APPROACH OF MULTIPLE MOVING TARGETS DETECTION FOR MICROWAVE SURVEILLANCE SENSORS

机译：微波监视传感器的多运动目标检测方法

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摘要

Multiple moving targets detection is one of the fundamental problems in information acquisition. In this paper, the use of a transformable period and symmetrical linear frequency modulated (TPS-LFM) waveform for microwave surveillance sensor multiple moving targets identification, is proposed. In order to accurately estimate target's true position and velocity, a relatively unknown yet powerful technique, the so-called fractional Fourier transform (FrFT), is applied to estimate the moving target parameters. By mapping a target's signal onto a fractional Fourier axis, the FrFT permits a constant-velocity target to be focused in the fractional Fourier domain thereby affording orders of magnitude improvement in signal-clutter-ratio. Moving target velocity and position parameters are derived and expressed in terms of an optimum fractional angle and a measured fractional Fourier position, allowing a target to be accurately located. Moreover, to resolve the problem whereby weak targets are covered by the sidelobes of strong ones, the CLEAN technique is also applied. Simulation results show that the method is effective in estimating target velocity and position parameters for microwave surveillance sensors.
机译：多运动目标检测是信息获取中的基本问题之一。该文提出一种可变周期对称线性调频（TPS-LFM）波形对微波监控传感器多运动目标的识别。为了准确估计目标的真实位置和速度，应用了一种相对未知但功能强大的技术，即所谓的分数阶傅里叶变换（FrFT）来估计移动目标参数。通过将目标的信号映射到分数阶傅里叶轴上，FrFT 允许将恒速目标聚焦在分数阶傅里叶域中，从而将信号杂波比提高几个数量级。移动目标速度和位置参数以最佳分数角和测量分数傅里叶位置的形式推导和表示，从而可以准确定位目标。此外，为了解决弱目标被强目标的旁瓣覆盖的问题，还应用了CLEAN技术。仿真结果表明，该方法能够有效地估计微波监视传感器的目标速度和位置参数。

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