一种高效的外辐射源雷达高径向速度目标实时检测方法

摘要

外辐射源雷达中传统的2维相干积累(模糊函数)运算量大，难以实时实现，且积累时间内高径向速度目标会出现距离徙动现象，导致信噪比下降，降低了系统的弱目标检测能力。该文采用外辐射源雷达中一种快速实时相干积累方法，利用2维分时滤波的原理，即通过信号分段处理，段内为快时间，段间为慢时间，沿快时间匹配滤波及沿慢时间通过FFT获取多普勒信息，实现相干积累检测的实时处理方法，并且给出一种适合实际应用的分段方案；在此基础上，通过 keystone 变换校正了高径向速度目标的距离徙动，提高了微弱目标的检测能力。算法计算效率高，较现有方法实时处理能力强，且校正过程中信号能量损失很小，是一种高效、可实时实现的高速目标检测方法。文中对积累及徙动校正的实时能力进行了分析。基于DTTB数字电视信号的仿真及实际数据分析表明，该文算法可在保证处理增益的前提下，满足相干积累及徙动校正的实时处理需求。%For passive radar, the computation cost of traditional 2-dimentional coherent integration (ambiguity function) is high, which makes it hard to perform in real-time processing. And range migration may occur during the integration time, leading to a Signal-to-Noise ratio (SNR) decrease. The migration may cause a detection ability loss. A migration compensation algorithm is proposed with keystone transform based on a real-time integration method in this article to realize real-time processing of 2-dimational integration. The real-time integration includes: 1-dimentional signal is divided into segments, match filtering is applied to each segment, and FFT is applied across segments. An improved segment method is introduced for application demand. Based on this method, an effective method to rectify range migration is proposed using keystone transform in this article, enhancing the detection ability of weak targets. The algorithm can improve computation efficiency with less energy loss, and is easier to perform in real-time then other algorithms. So it’s a real-time and efficient target detection method. In this article the real-time processing ability of integration and migration compensation is analyzed. Experiments based on simulated signal and real-life signal show that the algorithm can realize real-time processing with effective processing gain.