基于EMD能量占比的海面漂浮小目标特征检测

doi:10.12305/j.issn.1001-506X.2021.02.03

Abstract

Abstract:

Aiming at the problem that the traditional time-frequency analysis method is limited to the analysis of sea clutter, a feature detection method of floating small target on the sea surface based on empirical mode decomposition (EMD) energy proportion is proposed. Firstly, the received echo is divided into several independent intrinsic mode function (IMF) components with different scales by EMD, which can realize the decomposition of the frequency for the received echo from high frequency to low frequency. Secondly, the correlation coefficients between the IMF components and the received echo data are established respectively. And the ratio of mean to standard deviation is used as the criterion to filter the IMF components, which can automatically select the low-order IMF components with large energy and stable fluctuation. Finally, the average energy proportion of IMF component in the original signal is extracted as the feature, and the Monte Carlo method is used to set the threshold for sea surface target anomaly detection. The results of the measured data show that the performance of the proposed algorithm is better than that of the comparison algorithm.

Key words: empirical mode decomposition (EMD), correlation coefficient, energy ratio, floating small target detection

CLC Number:

TN911.23

Yanling SHI, Zipeng LIU, Xueliang ZHANG, Weiliang GU. Feature detection of floating small target on the sea surface based on EMD energy proportion[J]. Systems Engineering and Electronics, 2021, 43(2): 300-310.

Figures/Tables 17

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References 25

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数据编号	数据名称	风速/(km/h)	浪高/m	角度/(°)	目标单元	受影响单元
1	19931107_135603_starea17	9	2.2	9	9	8, 10, 11
2	19931108_220902_starea26	9	1.1	97	7	6, 8
3	19931109_191449_starea30	19	0.9	98	7	6, 8
4	19931109_202217_starea31	19	0.9	98	7	6, 8, 9
5	19931110_001635_starea40	9	1.0	88	7	5, 6, 8
6	19931111_163625_starea54	20	0.7	8	8	7, 9, 10
7	19931118_023604_stareC0000280	10	1.6	130	8	7, 9, 10
8	19931118_162155_stareC0000310	33	0.9	30	7	6, 8, 9
9	19931118_162658_stareC0000311	33	0.9	40	7	6, 8, 9
10	19931118_174259_stareC0000320	28	0.9	30	7	6, 8, 9
11	TFA10_001	6.889 7	1.850 3	172.3	16	15, 17

分量	检测概率
	#17			#31
	p_f =0.001	p_f =0.01	p_f =0.1	p_f =0.001	p_f =0.01	p_f =0.1
IMF1	0.448	0.558	0.837	0.148	0.184	0.356
IMF2	0.819	0.860	0.925	0.232 3	0.396 8	0.582 7
IMF3	0.641	0.765	0.935	0.531	0.727	0.858
IMF4	0.236	0.385	0.631	0.211	0.332	0.576
IMF5	0.011	0.029	0.075	0.021	0.028	0.150

数据编号	HH		VV		HV		VH
数据编号	ASCR/dB	p_d	ASCR/dB	p_d	ASCR/dB	p_d	ASCR/dB	p_d
1	18.309	0.746 7	3.675	0.277 5	12.961	0.757 1	13.007	0.748 2
2	4.276	0.461 6	5.694	0.911 6	5.934	0.854 6	5.926	0.851 7
3	-0.343	0.597 9	1.974	0.774 2	3.637	0.854 4	3.552	0.821 8
4	6.476	0.553 5	8.173	0.847 7	7.388	0.683 9	7.362	0.853 6
5	9.533	0.098 4	10.950	0.992 6	12.890	0.934 9	12.846	0.964
6	17.977	0.999 1	8.847	1.000 0	16.143	0.996 7	16.184	1.000 0
7	3.986	0.806 8	4.397	0.981 2	7.327	0.910 3	7.360	0.914 4
8	2.261	0.304 4	-1.491	0.441 7	4.959	0.954 2	4.963	0.956
9	11.924	1.000 0	8.683	1.000 0	14.733	1.000 0	14.730	1.000 0
10	11.817	0.998 2	6.772	1.000 0	13.730	1.000 0	13.674	1.000 0
11	—	—	19.357	1.000 0	—	—	—	—

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Feature detection of floating small target on the sea surface based on EMD energy proportion

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