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A Three-Dimensional Localization Method for Multistatic SAR Based on Numerical Range-Doppler Algorithm and Entropy Minimization
- Source :
- Remote Sensing, Vol 9, Iss 5, p 470 (2017)
- Publication Year :
- 2017
- Publisher :
- MDPI AG, 2017.
-
Abstract
- In traditional localization methods for synthetic aperture radar (SAR), the range sum estimation and Doppler centroid estimation (DCE) are required. The DCE error can influence the localization accuracy greatly. In addition, the target height information cannot be obtained by these methods. In this paper, a three-dimensional localization method for multistatic SAR based on the numerical range-Doppler (RD) algorithm and entropy minimization principle is proposed. In this method, the raw data from each transmitter and receiver (T/R) pair are focused by the numerical RD algorithm with the initial location value of the reference target. Then, Newton iteration is used to solve the target location value with the information of the bistatic range sum (BRS) in different SAR images with respect to different T/R pairs. Generally, the initial location value of the reference target is not accurate, and it can influence the imaging quality and accuracy of other target locations. We use entropy to measure image quality and iterate imaging with the new location value of the reference target, until the entropy gets the minimum value. Therefore, we can get the optimal location value of the reference target, which can make image entropy reach the minimum. Finally, all targets can be located by the Newton iteration method with their BRS in each T/R pair that are obtained from the images with minimum entropy. Compared with traditional localization methods for monostatic SAR, the proposed method not only effectively eliminates the influences of DCE errors, but also can get the target height information. Therefore, it improves the localization accuracy and can achieve three-dimensional localization. The effectiveness of the localization approach is validated by a numerical simulation experiment.
Details
- Language :
- English
- ISSN :
- 20724292
- Volume :
- 9
- Issue :
- 5
- Database :
- Directory of Open Access Journals
- Journal :
- Remote Sensing
- Publication Type :
- Academic Journal
- Accession number :
- edsdoj.f308122f04ef405a840040d2efb37f50
- Document Type :
- article
- Full Text :
- https://doi.org/10.3390/rs9050470