Reinforcement of the complete model-based decomposition for polarimetric SAR based on canonical Huynen dichotomy

doi:10.7523/j.ucas.2024.046

Abstract

Abstract:

As an important technique for the fine interpretation of the polarimetric synthetic aperture radar targets， the model-based polarimetric decomposition is dedicated to additively expanding the complex target scatterings over the canonical models of surface scattering， double-bounce scattering， and volume scattering. However， model-based decompositions suffer from negative powers and insufficient utilization of polarimetric information. The complete model-based decomposition （CMD） and its improvement solve these problems， but cause the so-called zero-power degradation. This is because CMD can not always extract a surface component and a double-bounce component from the remaining matrix after the removal of the volume scattering， and zero scattering power is then inevitable. CMD is reinforced in this paper. We find that the extraction of the surface and double-bounce components in CMD is essentially a sub-dichotomy of the canonical Huynen dichotomy that prefers volume scattering. By adaptively upgrading it with the other two sub-dichotomies of the canonical Huynen dichotomy that prefer surface scattering and dihedral scattering， respectively， the reinforced CMD can always decompose the surface and double-bounce components without degradation，and the problem of zero power is thus effectively solved. Qualitative and quantitative comparisons on measured polarimetric SAR datasets are presented to demonstrate the good performance of the proposed method.

Key words: polarimetric synthetic aperture radar, polarimetric decomposition, model-based decomposition, scattering modeling, target dichotomy

CLC Number:

TN957.52

Jiatong LI, Dong LI, Yunhua ZHANG, Xun WANG, He LU. Reinforcement of the complete model-based decomposition for polarimetric SAR based on canonical Huynen dichotomy[J]. Journal of University of Chinese Academy of Sciences, 2026, 43(3): 404-413.

Figures/Tables 11

Fig.1 Flow chart of RCMD

Fig.2 Terrain feature and Pauli RGB pseudo-color image of the airborne full-polarimetric data over Oberpfaffenhofen acquired by ESAR

Fig.3 Terrain feature and Pauli RGB pseudo-color image of the airborne full-polarimetric data over San Francisco acquired by GF-3

Fig.4 Results obtained by different decomposition methods over Oberpfaffenhofen

Table 1 Mean normalized scattering power over Oberpfaffenhofen

方法	$P s$	$P d$	$P v$
CMD-ED	45.97	26.79	27.24
CMD-MF	45.43	27.33	27.24
ICMD	45.57	27.19	27.24
RCMD	44.40	28.37	27.23

Table 1 Mean normalized scattering power over Oberpfaffenhofen

方法	$P s$	$P d$	$P v$
CMD-ED	45.97	26.79	27.24
CMD-MF	45.43	27.33	27.24
ICMD	45.57	27.19	27.24
RCMD	44.40	28.37	27.23

Table 2 Percentage of positive power pixels over Oberpfaffenhofen

方法	$P s$	$P d$	$P v$
CMD-ED	98.88	96.42	100
CMD-MF	93.38	77.67	100
ICMD	93.96	77.46	100
RCMD	100	100	100

Table 2 Percentage of positive power pixels over Oberpfaffenhofen

方法	$P s$	$P d$	$P v$
CMD-ED	98.88	96.42	100
CMD-MF	93.38	77.67	100
ICMD	93.96	77.46	100
RCMD	100	100	100

Table 3 Percentage of each component power extracted by different decomposition methods in different subregions over Oberpfaffenhofen

区域	方法	$P s$	$P d$	$P v$
A	CMD-ED	16.99	29.97	53.04
	CMD-MF	18.23	28.73	53.04
	ICMD	18.34	28.62	53.04
	RCMD	17.80	29.19	53.01
B	CMD-ED	27.26	56.38	16.36
	CMD-MF	28.65	54.99	16.36
	ICMD	28.61	55.03	16.36
	RCMD	27.10	56.55	16.35
C	CMD-ED	76.25	14.46	9.29
	CMD-MF	76.62	14.09	9.29
	ICMD	76.67	14.04	9.29
	RCMD	76.72	13.99	9.29

Table 3 Percentage of each component power extracted by different decomposition methods in different subregions over Oberpfaffenhofen

区域	方法	$P s$	$P d$	$P v$
A	CMD-ED	16.99	29.97	53.04
	CMD-MF	18.23	28.73	53.04
	ICMD	18.34	28.62	53.04
	RCMD	17.80	29.19	53.01
B	CMD-ED	27.26	56.38	16.36
	CMD-MF	28.65	54.99	16.36
	ICMD	28.61	55.03	16.36
	RCMD	27.10	56.55	16.35
C	CMD-ED	76.25	14.46	9.29
	CMD-MF	76.62	14.09	9.29
	ICMD	76.67	14.04	9.29
	RCMD	76.72	13.99	9.29

Fig.5 Results obtained by different decomposition methods over San Francisco

Table 4 Mean normalized scattering powers over San Francisco

方法	$P s$	$P d$	$P v$
CMD-ED	70.58	14.49	14.93
CMD-MF	71.37	13.70	14.93
ICMD	71.56	13.51	14.93
RCMD	69.99	16.23	14.78

Table 4 Mean normalized scattering powers over San Francisco

方法	$P s$	$P d$	$P v$
CMD-ED	70.58	14.49	14.93
CMD-MF	71.37	13.70	14.93
ICMD	71.56	13.51	14.93
RCMD	69.99	16.23	14.78

Table 5 Percentage of positive power pixels over San Francisco

方法	$P s$	$P d$	$P v$
CMD-ED	98.72	94.62	100
CMD-MF	97.70	35.58	100
ICMD	98.74	33.97	100
RCMD	100	100	100

Table 5 Percentage of positive power pixels over San Francisco

方法	$P s$	$P d$	$P v$
CMD-ED	98.72	94.62	100
CMD-MF	97.70	35.58	100
ICMD	98.74	33.97	100
RCMD	100	100	100

Table 6 Percentage of each component power extracted by different decomposition methods in different subregions over San Francisco

区域	方法	$P s$	$P d$	$P v$
A	CMD-ED	98.40	0.77	0.83
	CMD-MF	98.78	0.39	0.83
	ICMD	98.82	0.35	0.83
	RCMD	99.16	0.01	0.83
B	CMD-ED	37.13	28.41	34.46
	CMD-MF	40.80	24.74	34.46
	ICMD	40.25	25.29	34.46
	RCMD	37.28	28.56	34.06
C	CMD-ED	40.36	15.32	44.32
	CMD-MF	39.15	16.53	44.32
	ICMD	41.95	13.73	44.32
	RCMD	38.19	17.96	43.85

Table 6 Percentage of each component power extracted by different decomposition methods in different subregions over San Francisco

区域	方法	$P s$	$P d$	$P v$
A	CMD-ED	98.40	0.77	0.83
	CMD-MF	98.78	0.39	0.83
	ICMD	98.82	0.35	0.83
	RCMD	99.16	0.01	0.83
B	CMD-ED	37.13	28.41	34.46
	CMD-MF	40.80	24.74	34.46
	ICMD	40.25	25.29	34.46
	RCMD	37.28	28.56	34.06
C	CMD-ED	40.36	15.32	44.32
	CMD-MF	39.15	16.53	44.32
	ICMD	41.95	13.73	44.32
	RCMD	38.19	17.96	43.85

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