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Parameter Estimation of Pseudo-Random Optimized Dolph-Chebyshev Window Waveforms Using the Gauss-Newton Method | IEEE Conference Publication | IEEE Xplore

Parameter Estimation of Pseudo-Random Optimized Dolph-Chebyshev Window Waveforms Using the Gauss-Newton Method


Abstract:

The problem of estimating the parameters of the radar return from a waveform with a tunable Dolph-Chebyshev power spectral density is considered. Specifically, the gradie...Show More

Abstract:

The problem of estimating the parameters of the radar return from a waveform with a tunable Dolph-Chebyshev power spectral density is considered. Specifically, the gradients of the Dolph-Chebyshev window are derived for use with the Gauss-Newton method for determining the multiple parameters of a received waveform. The radar waveform is designed using the pseudo-random optimized frequency modulation technique. The performance of this nonlinear-least squares technique is compared to the Gauss-Newton method using gradients derived from a sinc function (as would be the case for a linear frequency modulated waveform), as well as an interpolation method. Further, the complexities of the above techniques are discussed.
Date of Conference: 06-10 May 2024
Date Added to IEEE Xplore: 13 June 2024
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Conference Location: Denver, CO, USA

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