低信噪比、高动态环境突发信号检测与估计

Burst Signal Detection and Estimation in Low SNR and High-Dynamic Environments

  • 摘要: 针对高动态环境下突发信号检测问题,提出基于高阶项逐级消去的非线性调频 (non-linear frequency modulation,NLFM) 信号参数估计算法,利用合理近似,将其转化为相对简单的线性调频 (linear frequency modulation,LFM) 信号参数估计问题,并提出两级调频率逼近法用于LFM信号参数估计,具有原理简明、计算复杂度低等特点,便于实际工程应用. 针对接收信号功率动态变化的问题,提出自适应快速傅里叶变换 (fast Fourier transform,FFT)峰均比门限信号检测算法. 仿真结果表明,所提算法能够在信噪比为-27dB的高动态环境下准确实现信号检测与参数估计.

     

    Abstract: Aiming to the burst signal detection in high-dynamic environments, an NLFM signal parameter estimation algorithm based on high order items eliminated sequentially was presented, which converting the problem into a relatively simple issue, that is LFM signal parameter estimation. The proposed scheme has the feature of concise principle and low computational complexity, and was easily used for projects. Besides, a burst communication signals detection algorithm named as adaptive FFT PAPR (peak to average ratio) threshold detecting was raised, which could work well even the received signal power varying severely. Simulation results show that both of the two schemes could achieve signal detection and parameter estimation accurately in high-dynamic circumstances while the SNR (signal to noise ratio) is only -27dB.

     

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