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Fast Implementation of Approximated Maximum Likelihood Parameter Estimation for Frequency Agile Radar under Jamming Environment

1
National Laboratory of Radar Signal Processing, Xidian University, Xidian 710071, China
2
School of Electronics and Communication Engineering, Sun Yat-sen University, Guangzhou 510275, China
*
Author to whom correspondence should be addressed.
Sensors 2020, 20(7), 2022; https://doi.org/10.3390/s20072022
Received: 10 February 2020 / Revised: 25 March 2020 / Accepted: 29 March 2020 / Published: 3 April 2020
(This article belongs to the Section Remote Sensors)
A computationally efficient target parameter estimation algorithm for frequency agile radar (FAR) under jamming environment is developed. First, the barrage noise jamming and the deceptive jamming are suppressed by using adaptive beamforming and frequency agility. Second, the analytical solution of the parameter estimation is obtained by a low-order approximation to the multi-dimensional maximum likelihood (ML) function. Due to that, fine grid-search (FGS) is avoided and the computational complexity is greatly reduced. View Full-Text
Keywords: maximum likelihood estimation; frequency agility; jamming suppression maximum likelihood estimation; frequency agility; jamming suppression
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Zhao, Y.; Wu, J.; Suo, Z.; Liu, X. Fast Implementation of Approximated Maximum Likelihood Parameter Estimation for Frequency Agile Radar under Jamming Environment. Sensors 2020, 20, 2022.

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