Abstract
In this chapter we consider the nonlinear optimization problem for reconstructing the shape of an extended target from multistatic data. Because of the nonlinearity of the problem, iterative algorithms have to be introduced.
Keywords
- Initial Guess
- Additive Noise
- Additive Gaussian White Noise
- Singular Vector
- Response Matrix
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.
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© 2013 Springer International Publishing Switzerland
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Ammari, H. et al. (2013). Nonlinear Optimization Algorithms. In: Mathematical and Statistical Methods for Multistatic Imaging. Lecture Notes in Mathematics, vol 2098. Springer, Cham. https://doi.org/10.1007/978-3-319-02585-8_14
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DOI: https://doi.org/10.1007/978-3-319-02585-8_14
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Publisher Name: Springer, Cham
Print ISBN: 978-3-319-02584-1
Online ISBN: 978-3-319-02585-8
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