Acoustic ray error minimization criteria and genetic algorithm for simplifying sound velocity profile

doi:10.11947/j.AGCS.2024.20230046

Abstract

Abstract:

In order to improve the computational efficiency of high-precision underwater navigation and positioning, sound velocity profile (SVP) should be moderately simplified. On the one hand, the simplification of SVP involves complex combinational optimization; on the other hand, the loss of acoustic ray precision caused by simplification needs to be considered. In this paper, a minimum acoustic ray precision loss criterion for SVP simplification is constructed, and genetic algorithm (GA) is used to solve the combinatorial optimization problem with this criterion. The results show that compared with the MOV method and area difference method for simplifying SVP, the proposed method can determine the number of simplified layers of SVP and realize the global optimization of simplified SVP under the premise of effectively controlling the accuracy loss of acoustic ray.

Key words: simplified sound velocity profile, acoustic ray tracking, genetic algorithm, combinatorial optimization, adaptive layering

CLC Number:

P229

Baojin LI, Shuqiang XUE, Wenzhou SUN, Jingsen LI, Anmin ZENG, Jiachao BIAN. Acoustic ray error minimization criteria and genetic algorithm for simplifying sound velocity profile[J]. Acta Geodaetica et Cartographica Sinica, 2024, 53(7): 1336-1344.

Figures/Tables 13

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层数	MOV简化剖面		面积差简化剖面		遗传算法简化剖面
层数	深度/m	声速/（m/s）	深度/m	声速/（m/s）	深度/m	声速/（m/s）
1	6.02	1 544.52	6.02	1 544.52	6.02	1 544.52
2	39.53	1 544.67	48	1 536.22	153.27	1 509.13
3	41.96	1 540.63	85	1 520.24	172.17	1 507.51
4	44.72	1 539.72	159	1 508.55	281.83	1 498.79
5	54.63	1 532.55	233	1 502.73	434.75	1 492.65
6	84.48	1 520.44	307	1 497.89	510.84	1 490.98
7	101.54	1 516.22	456	1 492.13	537.89	1 489.76
8	166.87	1 507.62	604	1 488.96	763.06	1 485.94
9	197.75	1 505.38	753	1 486.14	812.98	1 485.59
10	199.24	1 506.24	901	1 484.79	897.61	1 484.79
11	200.86	1 504.95	1049	1 484.37	1 198.52	1 483.90
12	219.29	1 504.37	1197	1 483.88	1 313.97	1 484.32
13	265.59	1 499.77	1332	1 484.38	1 449.13	1 485.43
14	434.75	1 492.65	1466	1 485.62	1 613.18	1 487.21
15	539.73	1 489.67	1735	1 488.77	1 793.56	1 489.50
16	778.13	1 485.63	2004	1 492.47	1 989.93	1 492.24
17	1 197.71	1 483.88	2273	1 496.64	2 290.49	1 496.89
18	1 608.47	1 487.13	2632	1 502.55	2 353.63	1 497.91
19	2 301.04	1 497.04	2991	1 508.63	2 444.25	1 499.40
20	3 269.72	1 513.35	3 269.72	1 513.35	3 269.72	1 513.35

简化SVP	水平点位误差	高程误差
MOV法简化SVP	0.73	24.15
面积差法简化SVP	0.05	-1.91
遗传算法简化SVP	0.04	0.88

剖面简化层数	测距中误差
5	254.64
6	133.58
7	62.42
8	49.96
9	9.97
10	3.36
15	0.37
20	0.42
25	0.20
30	0.28
40	0.99
50	0.42
60	0.21

简化SVP层数	声线跟踪次数	计算时间/s
13	1000	0.11
13	10 000	1.04
13	100 000	10.40
3436	1000	23.09
3436	10 000	232.98
3436	100 000	2 328.62

简化SVP层数	水平点位误差	高程误差
5	24.81	488.30
6	11.10	260.05
7	3.06	124.06
8	1.58	98.47
9	0.89	21.50
10	0.19	3.47
15	0.04	1.15
20	0.04	0.88
25	0.10	0.26
30	0.03	0.80
40	0.12	1.05
50	0.03	0.74
60	0.11	0.47