MULTI-LOCATION INVERSE SYNTHETIC APERTURE RADAR IMAGE FUSION AT THE DATA LEVEL
Open Access
- Author:
- Li, Zhixi
- Graduate Program:
- Electrical Engineering
- Degree:
- Doctor of Philosophy
- Document Type:
- Dissertation
- Date of Defense:
- August 30, 2007
- Committee Members:
- Ram Mohan Narayanan, Committee Chair/Co-Chair
Hrb Systems Professor: Nirmal K Bose, Committee Member
Douglas Henry Werner, Committee Member
Jia Li, Committee Member - Keywords:
- Inverse Synthetic Aperture Radar
Radar Imaging
Data Fusion
Fourier Transform
Slicy Database
Receiver Operating Characteristics - Abstract:
- Although techniques for resolution enhancement in single-aspect radar imaging have made rapid progress in recent years, it does not necessarily imply that such enhanced images will improve target identification or recognition. However, when multiple looks of the same target from different aspects are obtained, the available knowledge increases allowing more useful target information to be extracted. Physics based image fusion techniques can be developed by processing the raw data collected from multiple inverse synthetic aperture radar (ISAR) sensors, even if these individual images are at different resolutions. The technique maps multiple data sets collected by multiple radars with different system parameters on to the same spatial-frequency space. The composite image can be reconstructed using the inverse 2-D Fourier Transform over the separated multiple integration areas. An algorithm called the Matrix Fourier Transform (MFT) is proposed to realize such a complicated integral. This algorithm can be regarded as an exact interpolation such that there is no information loss caused by data fusion. The rotation centers need to be carefully selected in order to properly register the multiple images before performing the fusion. A comparison of the Image Attribute Rating (IAR) curves between the fused image and the spatially-averaged images quantifies the improvement in the detected target features. The technique shows considerable improvement over a simple spatial averaging algorithm and thereby enhances target recognition. It is also demonstrated that this ISAR image fusion method is capable of imaging the maneuvering targets by selecting correct common projection plane, accurate motion estimation, and appropriate system configuration.