On the use of a linear data model for parameter estimation of sinusoidal FM signals

Author(s):  
Jihao Yin ◽  
Yun Hua ◽  
Wanlin Yang ◽  
Tianqi Chen
2013 ◽  
Vol 2013 ◽  
pp. 1-13 ◽  
Author(s):  
Bin Deng ◽  
Hong-Qiang Wang ◽  
Yu-Liang Qin ◽  
Sha Zhu ◽  
Xiang Li

Parabolic-reflector antennas (PRAs), usually possessing rotation, are a particular type of targets of potential interest to the synthetic aperture radar (SAR) community. This paper is aimed to investigate PRA’s scattering characteristics and then to extract PRA’s parameters from SAR returns, for supporting image interpretation and target recognition. We at first obtain both closed-form and numeric solutions to PRA’s backscattering by geometrical optics (GO), physical optics, and graphical electromagnetic computation, respectively. Based on the GO solution, a migratory scattering center model is at first presented for representing the movement of the specular point with aspect angle, and then a hybrid model, named the migratory/micromotion scattering center (MMSC) model, is proposed for characterizing a rotating PRA in the SAR geometry, which incorporates PRA’s rotation into its migratory scattering center model. Additionally, we in detail analyze PRA’s radar characteristics on radar cross-section, high-resolution range profiles, time-frequency distribution, and 2D images, which also confirm the models proposed. A maximal likelihood estimator is developed for jointly solving the MMSC model for PRA’s multiple parameters by optimization. By exploiting the aforementioned characteristics, the coarse parameter estimation guarantees convergency upon global minima. The signatures recovered can be favorably utilized for SAR image interpretation and target recognition.


2012 ◽  
Vol 22 (6) ◽  
pp. 1137-1144 ◽  
Author(s):  
Igor Djurović ◽  
Marko Simeunović ◽  
Budimir Lutovac

2018 ◽  
Vol 149 ◽  
pp. 1-13 ◽  
Author(s):  
Igor Djurović ◽  
Pu Wang ◽  
Marko Simeunović ◽  
Philip V. Orlik

Author(s):  
Marek Sowinski ◽  
Anna Neugebauer

The main feature of the proposed model implemented by a computer package WODA, that distinguishes it from other commonly used models like QUALE 2E or WASP5, is a possibility of its automatic calibration i e parameter estimation taking into account simultaneously several sets of measured concentration data. Model WODA, developed by A. Kraszewski and R. Soncini‐Sessa, enables fitting simulated values to measured concentrations of BOD and DO based on the least‐square criterion. This model was applied for parameter estimation of the Warta River in Poland. Measured concentration data used for parameter estimation were obtained from monthly monitoring. The results are presented in the form of BOD and DO lines against measured concentrations along the analysed stretch of the Warta River. Adaptation of the model simulation results to measured data is described by quantifying characteristics. They indicate relatively good adjustment. The reasons of some differences are discussed and explained.


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