2004
DOI: 10.1109/tgrs.2003.817807
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Algorithms for Estimating the Complete Group of Polarization Invariants of the Scattering Matrix (SM) Based on Measuring All SM Elements

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Cited by 19 publications
(7 citation statements)
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“…The simulation data are produced according to [13] and [14], and without loss of generalization, the residual measurement noise is a complex Gaussian white noise. The calibration results are also compared with those obtained by the algebraic manipulation algorithm proposed in [11].…”
Section: Simulation Resultsmentioning
confidence: 99%
See 1 more Smart Citation
“…The simulation data are produced according to [13] and [14], and without loss of generalization, the residual measurement noise is a complex Gaussian white noise. The calibration results are also compared with those obtained by the algebraic manipulation algorithm proposed in [11].…”
Section: Simulation Resultsmentioning
confidence: 99%
“…So in our genetic algorithm, the size of the initial population is 70, the crossover probability is 0.8, the mutation probability is 0.1, and the algorithm stops when the best-fit individual obtains a fitness value of less than 10 −5 or after the number of generation achieves 30. All three crossover functions defined in (12)- (14) are used, and the results are averaged over 100 Monte Carlo runs. Without loss of generality, only the horizontal copolarization coefficient C s11 , the vertical copolarization coefficient C s44 , and the crosspolarization coefficients C s22 and C s33 are presented here.…”
Section: Simulation Resultsmentioning
confidence: 99%
“…We demonstrate the advantages of the optimal AMD by comparing with fixed AMDs, i.e., the AMD with horizontal transmitted polarization (H-AMD) and the AMD with vertical transmitted polarization (V-AMD), and the optimal ASD in [21]. Parameters m, ν, γ and ρ applied to describe the Sinclair matrix do not change with the orientation along the line of sight [32]. ψ ( Àπ=2 r ψ r π=2) is the orientation angle of the system basis of the object to the system coordinate frame.…”
Section: Performance Improvementmentioning
confidence: 99%
“…The other fully polarized characteristic just like polarization invariables can also be calculated for RTR [10], where arg(⋅) denotes the phase angle.…”
Section: Superresolution and Feature Extraction For Fully Polarized Isarmentioning
confidence: 99%
“…The appropriate joint processing of the polarization channels provides higher SNR level which is required to achieve high superresolution gains and makes the superresolution algorithm more robust. Furthermore, the scattering matrix will present very useful information for RTR [7][8][9][10][11].…”
Section: Introductionmentioning
confidence: 99%