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本文研究了非高斯噪声中随机信号的检测问题。基于随机信号的参数模型和广义似然比检测理论,导出了非高斯噪声中随机信号Rao检测的数学解析式,其检测性能渐近等同于广义似然比检测但计算更有效。仿真结果表明,该检测器性能大大优于传统的能量检测器以及高斯噪声假设下的广义似然比检测器。
This paper investigates the detection of stochastic signals in non-Gaussian noise. Based on the stochastic signal parameter model and the generalized likelihood ratio detection theory, the mathematical analytic formula of random signal Rao in non-Gaussian noise is derived. The detection performance is asymptotically equivalent to the generalized likelihood ratio test but the calculation is more efficient. The simulation results show that the performance of the detector is much better than that of the traditional energy detector and the generalized likelihood ratio detector under Gaussian noise assumption.