WEI Yinsheng and XU Zhaoyang. Review of signal design for discontinuous spectrum radar[J]. Journal of Radars, 2022, 11(2): 183–197. doi: 10.12000/JR22023
Citation:
CHEN Shichao, GAO Heting, and LUO Feng. Target detection in sea clutter based on combined characteristics of polarization[J]. Journal of Radars, 2020, 9(4): 664–673. doi: 10.12000/JR20072
WEI Yinsheng and XU Zhaoyang. Review of signal design for discontinuous spectrum radar[J]. Journal of Radars, 2022, 11(2): 183–197. doi: 10.12000/JR22023
Citation:
CHEN Shichao, GAO Heting, and LUO Feng. Target detection in sea clutter based on combined characteristics of polarization[J]. Journal of Radars, 2020, 9(4): 664–673. doi: 10.12000/JR20072
Polarization is a property applying to transverse waves that specifies the geometrical orientation of the oscillations. This paper proposes a method for detecting small targets on the sea surface based on the combination of polarization features of two models. The scattering mechanism of sea clutter is random scattering at low glazing angle or glancing angle and the randomness is high as the angles do not have any specified shape. However, a target has a specific shape, and thus, the randomness of scattering will be less. Clutter is a term used for unwanted echoes in electronic systems, particularly in reference to radars. Such echoes typically return from ground, sea, rain, and animals/insects. In this literature, the randomness of a scattering mechanism in an echo is obtained from the probability density functions of polarization entropy using the Cloude decomposition model. Further, the proportion of scattering at spherical, dihedral, and helicoid angles from the target echoes will be different in the sea clutter. Therefore, the relative coefficient of power of these three scattering components in each echo is extracted based on Krogager polarization decomposition. Then, polarization features with good separability and complementarity are selected to form the polarization feature vector, and the characteristics are verified by Principle Component Analysis (PCA). Finally, One Class Support Vector Machine (OCSVM) is used for classification and recognition based on the polarization decomposition feature vector. Instead of single-polarization detection methods, our method uses two polarization modes to extract the decomposition features with separability and complementarity through polarization coherent decomposition and incoherent decomposition, respectively. The experimental results of the IPIX data show the effectiveness of our method. Thus, the detection performance of our model is better than those methods based on single-polarization decomposition in complex and difficult sea conditions.
非连续谱信号快时间域波形合成通过设计发射脉冲的调制函数使得发射信号的频谱与理论最优谱形差距最小,其是研究最多也是最广泛的非连续谱信号。快时间域的非连续谱信号调制方式有频率调制与相位编码两种。频率调制信号是通过对脉冲内的相位进行非线性调制来获得大时宽带宽积的信号,常用的频率调制信号有线性调频(Linear Frequency Modulation, LFM)信号与非线性调频(Non-Linear Frequency Modulation, NLFM)信号。相位编码信号是一种通过将宽脉冲等分为若干子脉冲,然后采用不同的相位对子脉冲进行调制的信号,常用的相位编码信号有连续相位编码信号与离散相位编码信号。
对于频率调制信号,Gerlach等人[43]、Oechslin等人[44]通过频谱置零、间隙线性调频等波形合成技术实现频谱拟合,但是上述方式合成的LFM信号会具有较高的距离旁瓣,需要在接收端通过信号处理方法来对其进行抑制。为了降低发射信号的高距离旁瓣,Weitzel等人[45]利用非线性放大元件的放大特性(Linear amplification using Nonlinear Components, LINC)提出一种非线性调频信号的波形合成方法,生成具有频谱凹陷的NLFM信号,但是这类方法生成的信号产生了显著的振幅调制,会造成目标信噪比损失。Jakabosky等人[46]提出一种基于序列投影算法的NLFM信号波形合成算法,其可利用LINC框架生成具有期望幅度和频谱的时域信号。NLFM信号虽然可以获得较好的频谱拟合特性,但是由于其是一种时域连续调制信号,其求解十分复杂,往往通过先设计一组相位编码信号,之后通过函数差值的方式获取发射信号,例如多相编码调频(Polyphase-Coded FM, PCFM)信号。
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WEI Yinsheng and XU Zhaoyang. Review of signal design for discontinuous spectrum radar[J]. Journal of Radars, 2022, 11(2): 183–197. doi: 10.12000/JR22023
WEI Yinsheng and XU Zhaoyang. Review of signal design for discontinuous spectrum radar[J]. Journal of Radars, 2022, 11(2): 183–197. doi: 10.12000/JR22023