高分辨率雷达距离像用于目标识别的研究

针对飞机目标的分类问题,研究将雷达目标的高距离分辨率(high range resolution,HRR)像用于识别的方法。介绍两类基于目标HRR像的特征:差分功率谱和微分倒谱,并选择基于SARPROP(simulated anneal-ing resilient propagation)算法的多层前馈神经网络作为分类器。利用4种飞机缩比模型的重点散射源二维分布测试数据和频率步进法,得到目标的一维距离像。对上述两类距离像特征进行了分类,结果表明,差分功率谱特征对于一维距离像具有较高的识别率,并具有较好的抗噪性能。

Target recognition using high resolution radar range profiles

The problem of target recognition using the high resolution radar range profiles is discussed.Two feature extraction methods based on differential power spectrum(DPS) and differential cepstrum,originally used in the research area of speech signal processing and homomorphic signal processing are respectively introduced to the radar target recognition community.Two differential power spectrum based features are applied to target classification.A multi-layered feed forward neural network with SARPROP(simulated annealing resilient propagation) algorithm is selected as classifier.The range profiles are obtained with step-frequency technique and the two-dimension backscatter distribution data of four different scaled aircraft models.Simulations are presented to evaluate the classification performance with the above features.The results show that the differential power spectrum based feature is effective and robust for the radar target recognition.