Parameter Method Data Processing for CPⅢ Precise Trigonometric Leveling Network

doi:10.11947/j.JGGS.2020.0307

Abstract

Abstract:

In view of the limitation of the difference method, the adjustment model of CPⅢ precise trigonometric leveling control network based on the parameter method was proposed in the present paper. The experiment results show that this model has a simple algorithm and high data utilization, avoids the negative influences caused by the correlation among the data acquired from the difference method and its accuracy is improved compared with the difference method. In addition, the strict weight of CPⅢ precise trigonometric leveling control network was also discussed in this paper. The results demonstrate that the ranging error of trigonometric leveling can be neglected when the vertical angle is less than 3 degrees. The accuracy of CPⅢ precise trigonometric leveling control network has not changed significantly before and after strict weight.

Key words: CPⅢ leveling control network;; precise trigonometric leveling; parameter method; minimum norm quadratic unbiased estimate

Jianzhang LI, Haowen YAN. Parameter Method Data Processing for CPⅢ Precise Trigonometric Leveling Network[J]. Journal of Geodesy and Geoinformation Science, 2020, 3(3): 67-75.

Figures/Tables 6

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S/N	Line Length /km	Constraint points	Parameter method					Difference method
S/N	Line Length /km	Constraint points	Mean value of leveling difference	Maximum leveling difference	Mean variation of elevation difference between adjacent points	Maximum variation of elevation difference between adjacent points	Number of exceeding limit		Mean value of leveling difference	Maximum leveling difference	Mean variation of elevation difference between adjacent points	Maximum variation of elevation difference between adjacent points	Number of exceeding limit
1	4	9	0.35	2.35	0.34	2.54	1	0.69		2.47	0.47	2.91	2
2	5	11	0.27	1.65	0.27	1.88	0	0.34		2.60	0.31	2.09	1
3	7	15	0.53	1.88	0.55	1.59	0	0.61		2.58	0.58	2.29	2
4	10	21	0.75	2.21	0.68	1.99	0	1.43		3.63	0.81	2.42	2
5	6	13	0.46	1.60	0.49	2.13	1	0.64		2.91	0.57	2.33	3
6	6	13	0.55	1.77	0.49	2.13	1	0.67		1.89	0.59	2.02	2
7	6	13	0.53	1.88	0.51	2.23	2	0.66		2.84	0.53	2.12	2
8	6	13	0.44	1.85	0.53	1.86	0	0.52		2.08	0.57	3.05	5
9	4	8	0.36	1.96	0.33	2.42	1	0.70		2.36	0.51	2.95	1
10	5	10	0.58	2.22	0.56	1.86	0	0.59		2.31	0.57	2.24	1