基于电离层杂波监测的高频地波雷达选频关键问题研究

The ionospheric clutter seriously affects the quality of the echo spectrum, and it is difficult to be suppressed on account of its time variation, complexity and similarity to target. However, selecting an appropriate work frequency for high frequency surface wave radar will be an effective way to avoid the ionospheric clutter and to improve the radar detection performance. In order to achieve the goal of selecting the right frequency on line, in this project, ionospheric clutter is regarded as objects, and its detection, identification and evaluation will be studied. The main contents about the research are as followed: (1) Sweep frequency method is adopted in a certain period of time to monitor ionospheric clutter on many optional frequencies. Segment signal covariance matrix model is built; and the segment supper resolution algorithm is put forward for Doppler processing. (2) Ionospheric clutter detection template is designed based on the ionospheric clutter characteristics on RD spectrum and ionospheric clutter detection is achieved by template matching algorithm. According to the detection results, the identification of ionospheric clutter is achieved by the region-growing algorithm. (3) Many factors should be taken into consideration in a general way, such as the pollution range of ionospheric clutter, its strength and so on; the ionospheric clutter evaluating module needs to be solved and the high frequency surface wave radar frequency selection method will be presented. The achievements above will promote a new and integrated solution to solve the ionospheric clutter problem in high frequency surface radar.

电离层杂波严重影响高频地波雷达回波谱质量，其时变性、复杂性和类目标性使得电离层杂波较难抑制。选择合适的工作频率，是规避电离层杂波、提高高频地波雷达探测性能的有效手段。为达到在线选频的目的，本项目以电离层杂波为目标，对其进行检测、识别及评估方法的研究。主要研究内容有：(1)采取在一段时间内对多个备选频点进行多次短时间扫频监测方式，建立分段信号协方差矩阵模型，提出了分段超分辨算法进行多普勒处理。(2)根据电离层杂波在RD谱上的特征，设计电离层杂波检测模板，通过模板匹配计算实现电离层杂波检测。进一步在RD谱中以电离层杂波检测结果为基础，利用区域生长算法实现电离层杂波的识别。(3)综合考虑电离层杂波污染范围、强度等多种因素，对电离层杂波评估模型进行求解，设计高频地波雷达选频算法。以上成果可为解决高频地波雷达中的电离层杂波干扰问题提供一个全新的、完整的解决思路。

高频地波雷达作用距离不受地球曲率限制，能够对远距离的海面风场、浪场、洋流等进行大范围、全天候的实时监测；同时，它可以用于探测海面和低空目标，对经济专属区进行有效监视。但是高频地波雷达在工作时，会受到多种噪声和杂波的干扰，其中电离层杂波严重影响了雷达回波谱的质量，而其时变性、复杂性和类目标性使得电离层杂波较难抑制。等离子体理论表明电离层对电磁波的反射作用与电磁波频率密切相关，在某些工作频率上电离层杂波影响严重，甚至造成雷达无法正常工作，而在某些频率上却不会出现上述影响。因此为高频地波雷达选择合适的工作频率，是规避电离层杂波、提高雷达探测性能的有效手段。.为了避免频率选择的盲目性，需要对多个频率点回波中的电离层杂波进行有效监测，并根据监测结果为高频地波雷达推荐最优的工作频率。本项目对高频地波雷达中电离层杂波进行多个频点的实时监测，首先对回波数据采用S-MVDR算法进行多普勒频率估计，建立距离-多普勒检测平台，然后利用模板匹配和区域生长算法对其中的电离层杂波进行检测和识别，并利用多属性决策理论对电离层杂波影响程度进行评估，推荐最优工作频率。为进一步提高精度，采用基于改进灰狼优化算法优化RBF神经网络的回波提取。仿真与实测数据表明，在推荐最优工作频率下，参数反演精度明显提升。.本研究解决了电离层杂波监测及评估面临的主要技术问题，为提高雷达检测性能、实现智能频率管理提供了帮助，具有重要的理论意义和实际价值。