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A Group Invariance Approach to a Very Weak LFM Signal Detection

机译:一种基团的不变性方法,对LFM信号检测非常弱

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This paper considers the detection of a very low signal to noise ratio (SNR, linear frequency modulated (LFM) radar waveforms from data received by a wideband receiver. The optimal method involves a computationally intensive two dimensional search. Faster alternatives, include the discrete ambiguity approach to LFM detection/estimation which is computationally efficient but is well known to be applicable only at moderately high SNR, while the windowed Fourier transform can be used to detect low SNR signals, but only for quite small chirp rates. Here we utilize multiple time and frequency shifts applied to the received data to structure the problem as one of detection of a multi-channel unknown rank-one component in noise. Our method which involves only a one dimensional search over chirp rate, works at very low SNR and can handle multiple signals and interferers The generalized-likelihood ratio test (GLR, the Bayesian test are discussed and compare with the generalized coherence test. The detection performance are demonstrated through numerical simulations.
机译:本文考虑了从宽带接收器接收的数据的信噪比(SNR,线性频率调制(LFM)雷达波形的非常低的信号。最佳方法涉及计算密集的二维搜索。更快的替代方案包括离散的歧义实现高效但众所周知的LFM检测/估计的方法仅适用于中等高SNR,而窗口傅立叶变换可用于检测低SNR信号,但仅用于相当小的啁啾率。我们在这里使用多个时间和频移应用于接收的数据,以将问题结构构成为噪声中的多通道未知等级的一个组件的问题之一。我们涉及仅通过啁啾速率进行一维搜索,在非常低的SNR上工作,可以处理多个信号和干扰符合广义似然比测试(GLR,贝叶斯测试,并与广义相干测试进行比较。通过数值模拟证明了检测性能。

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