Search

Airborne target's micro-motion such as rotation or vibration causes phase modulation, termed as micro-Doppler effect, into radar signals. The feature of micro-motion is one of the most obvious features for radar recognition in mid-course phase. In traditional works, it is assumed that the micro-motion of the scatterer is the same as the ballistic target. However, with the variation of the aspect angle of ISAR, the position of the scatterer changes. In this paper, the movement of a ballistic missile in mid-course is modeled and analyzed. A false target jamming method is proposed by combining the micro-motion modulation and the electromagnetic scattering modulation. Compared with the methods using ideal point models, our method is able to generate a vivid false target with structural information, micro-motion and variation of the scatterer's RCS. The micro-motion effect of the false target is presented through ISAR imaging and time-frequency analysis. The effectiveness and correctness of the algorithm is verified by simulation.

Airborne target's micro-motion such as rotation or vibration causes phase modulation, termed as micro-Doppler effect, into radar signals. The feature of micro-motion is one of the most obvious features for radar recognition in mid-course phase. In traditional works, it is assumed that the micro-motion of the scatterer is the same as the ballistic target. However, with the variation of the aspect angle of ISAR, the position of the scatterer changes. In this paper, the movement of a ballistic missile in mid-course is modeled and analyzed. A false target jamming method is proposed by combining the micro-motion modulation and the electromagnetic scattering modulation. Compared with the methods using ideal point models, our method is able to generate a vivid false target with structural information, micro-motion and variation of the scatterer's RCS. The micro-motion effect of the false target is presented through ISAR imaging and time-frequency analysis. The effectiveness and correctness of the algorithm is verified by simulation.

Airborne target's micro-motion such as rotation or vibration causes phase modulation, termed as micro-Doppler effect, into radar signals. The feature of micro-motion is one of the most obvious features for radar recognition in mid-course phase. In traditional works, it is assumed that the micro-motion of the scatterer is the same as the ballistic target. However, with the variation of the aspect angle of ISAR, the position of the scatterer changes. In this paper, the movement of a ballistic missile in mid-course is modeled and analyzed. A false target jamming method is proposed by combining the micro-motion modulation and the electromagnetic scattering modulation. Compared with the methods using ideal point models, our method is able to generate a vivid false target with structural information, micro-motion and variation of the scatterer's RCS. The micro-motion effect of the false target is presented through ISAR imaging and time-frequency analysis. The effectiveness and correctness of the algorithm is verified by simulation.

Airborne target's micro-motion such as rotation or vibration causes phase modulation, termed as micro-Doppler effect, into radar signals. The feature of micro-motion is one of the most obvious features for radar recognition in mid-course phase. In traditional works, it is assumed that the micro-motion of the scatterer is the same as the ballistic target. However, with the variation of the aspect angle of ISAR, the position of the scatterer changes. In this paper, the movement of a ballistic missile in mid-course is modeled and analyzed. A false target jamming method is proposed by combining the micro-motion modulation and the electromagnetic scattering modulation. Compared with the methods using ideal point models, our method is able to generate a vivid false target with structural information, micro-motion and variation of the scatterer's RCS. The micro-motion effect of the false target is presented through ISAR imaging and time-frequency analysis. The effectiveness and correctness of the algorithm is verified by simulation.

Micro-Doppler features can be regarded as a unique signature of an object with movements and provide additional information for classification, recognition and identification of the object. Independent component analysis (ICA) can decompose micro-Doppler features into independent basis functions that represent salient physical movement attributes of the object. To study ICA of micro-Doppler features, we used a dataset generated by simulation of radar returned signals from rotating objects and tumbling objects. Fast ICA algorithm was used in our study to decompose micro-Doppler features into a set of spatial and temporal independent components. Spatial characteristics of the independent components combined with the corresponding temporal characteristics can be used to improve performance of classification, recognition and identification., See also ADM002017. Presented at the IEEE International Radar Conference held in Arlington, VA on 9-12 May 2005. Published in the Proceedings of the IEEE International Radar Conference, 2005. The original document contains color images.