OTHR低信噪比下的机动目标检测算法

Maneuvering Target Detection Algorithm with Low Signal-to-Noise Ratio in OTH Radar

在天波超视距雷达(OTHR)中,采用短时间相干积累时,可以提高数据率和检测效能,减小电离层污染。但采用短时间相干积累时,目标信噪比往往较低,检测难度较大,而机动目标的多普勒扩展进一步增加了目标的检测难度。传统的机动目标检测算法利用基于高阶模糊函数(HAF)的多普勒补偿算法来提高机动目标的可检测性,但由于HAF多次用到非线性变换,而每次非线性变换都会损失部分信噪比,因此对输入信噪比要求较高,难以适应于更低信噪比环境下的机动目标检测。将机动目标回波建模为三阶多项式相位信号,采用一种低非线性度的运动参数估计方法并结合多普勒补偿算法对目标回波进行处理,仅需要一次相位降阶操作,减少了信噪比损失,降低了对输入信噪比的要求。经过仿真验证,该算法的输入信噪比门限为-3dB,而HAF算法的输入信噪比门限为3dB。

Short coherent accumulation can improve the data rate and detection performance and reduce ionosphere contamination in sky-wave OTH radar. The low SNR rate is a great challenge when we detect the target using short coherent accumulation. The Doppler expansion of maneuvering target makes matter worse. The traditional detection algorithms adopt higher order ambiguity function（HAF） to compensate Doppler to improve the maneuvering target detectability. These algorithms require a higher input SNR be- cause HAF involves non-linear transformation and each non-linear transformation will reduce the SNR. So it is difficult to detect maneuvering target in lower SNR. In this paper, the echo of maneuvering target is mod- eled as a third-order polynomial phase signal. A motion parameters estimation method with low nonlinearity and Doppler compensation algorithm are used to processing target echo. The phase order is reduced only once in this algorithm. As a result, the input SNR rate is lower by using the proposed algorithm in this paper. Through simulation, the input SNR threshold of the algorithm is -- 3 dB, but the threshold of HAF algo- rithm is 3 dB.