基于多相参处理间隔频响特征聚类的有源假目标鉴别方法

现有真-假目标智能识别算法大多基于监督学习,且在低信噪比条件下表现不好。针对上述问题,该文分别利用真、假目标在多个相参处理间隔(CPIs)内散射特性的时变性和唯一性,提出一种多相参处理间隔频响特征聚类的真、假目标无监督鉴别方法。首先,在快-慢时域中沿快时间维度对真、假目标进行加窗截断,提取快-慢时间域频率响应特征用于构建初步样本集;然后,通过Agglomerative聚类和特征融合网络组成的两步识别算法对真-假目标进行识别;最后,提出一种多相参处理间隔联合决策方法提升识别性能和可靠性。经仿真和实测数据检验,证明了所提方法可实现真实目标和多种有源假目标的有效分离。

雷达回波的杂波分析与系统改进

从采集的实测回波数据入手,分析了系统剩余较多区域的杂波特性,并采用多种信号处理方法处理、分析对比,得出产生杂波剩余的原因。针对不同类型的杂波剩余分别给出对系统的技术改进措施,并给出了相应措施的仿真分析结果和工程实施方案。

Long term integration of radar signals with unknown Doppler shift for ubiquitous radar

Ubiquitous radar is a new radar system that provides continuous and uninterrupted multifunction capability within a coverage volume. Continuous coverage from close-in ＂pop-up＂ targets in clutter to long-range targets impacts selection of waveform parameters. The coherent processing interval （CPI） must be long enough to achieve a certain signal-to-noise ratio （SNR） that ensures the efficiency of detection. The condition of detection in the case of low SNR is analyzed, and three different cases that would occur during integration are discussed and a method to determine the CPI is presented. The simulation results show that targets detection with SNR as low as -26 dB in the experimental system can possibly determine the CPI.