Posicionamento Por Ponto Preciso E Posicionamento Relativo Com Gnss: Qual É O Método Mais Acurado Atualmente?

Almeida, Marília Sanglard; Poz, William Rodrigo Dal

doi:10.1590/s1982-21702016000100010

Cited by 5 publications

(2 citation statements)

References 8 publications

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“…Almeida & Dal Poz (2016) demonstrated that an ionospheric effect is the main factor interfering with the accuracy of GNSS positioning signals at a precise point. Also, the response time of an electric steering is shorter if compared to an electro-hydraulic steering, which acts directly on tractor wheelsets (Molin et al, 2015).…”

Section: Resultsmentioning

confidence: 99%

Parallelism error in peanut sowing operation with auto-steer guidance

Santos

Silva

Tavares

et al. 2017

Rev. bras. eng. agríc. ambient.

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A B S T R A C TGNSS positioning errors are certain, regardless of the adopted positioning method. In agriculture, these errors may represent higher or lower overlapping rates between passes of a mechanical assembly, affecting operation quality. Therefore, this study evaluated the main errors arising from peanut sowing operation performed with an auto-steer guidance system by an RTX signal, using the Statistical Process Control techniques. The errors evaluated were: in tractor lateral displacement, project execution, and parallelism between passes of tractor-seeder set. The average errors of project execution in all passes were within the range specified by the manufacturer, i.e. lower than 3.8 cm. The average error of tractorseeder set was also within the accepted range. However, as shown in control charts, lateral tractor displacement had interference of terrain slope, causing average errors higher than the accepted range. Based on the control charts, project execution accuracy was satisfactory, and it is possible to use the RTX signal in agricultural operations that require accuracy lower than 3.8 cm, such as peanut sowing.Erros de paralelismo provenientes da operação de semeadura de amendoim com direcionamento automático R E S U M O Os erros de posicionamento pelo GNSS são inevitáveis, independentemente do tipo de posicionamento adotado. Na agricultura esses erros podem representar maior ou menor taxa de sobreposição entre as passadas dos conjuntos mecanizados, o que afeta, consequentemente, a qualidade da operação. Objetivou-se, neste sentido, avaliar os principais erros ocasionados durante a operação de semeadura de amendoim utilizando direcionamento automático com sinal RTX, por meio da análise do Controle Estatístico de Processo. Foram avaliados o erro de deslocamento do trator, o erro de execução do projeto, em quatro passadas, além do erro de paralelismo entre as passadas do conjunto tratorsemeadora. O erro médio de execução ficou, em todas as passadas, dentro do estipulado pelo fornecedor do sinal, com valores menores que 3,8 cm. O erro médio do conjunto trator-semeadora encontrou-se no limite do aceitável. Já para o deslocamento lateral do trator, pela análise das cartas de controle, houve interferência da declividade na ocorrência de erros acima do estipulado. Com base na análise das cartas de controle constata-se que houve precisão para o erro de execução de projeto e que é possível utilizar o sinal RTX em operações agrícolas que requerem precisão menor que 3,8 cm, como a semeadura de amendoim.

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Section: Resultsmentioning

confidence: 99%

Parallelism error in peanut sowing operation with auto-steer guidance

Santos

Silva

Tavares

et al. 2017

Rev. bras. eng. agríc. ambient.

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“…If only the control of the positional accuracy with over the world GNSS is considered, there are several comparative studies and researches as in Chen and Li (2004), Li, Taylor and Kidner (2005), Colombo (2008), Cintra, Nero and Rodrigues (2011), Arnold andZandbergen (2011), Guandalini (2012), Almeida and Dal Poz (2016).…”

Section: Introductionmentioning

confidence: 99%

A Computational Tool to Evaluate the Sample Size in Map Positional Accuracy

Nero

Cintra²,

Ferreira

et al. 2017

Bol. Ciênc. Geod.

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Abstract:In many countries, the positional accuracy control by points in Cartography or Spatial data corresponds to the comparison between sets of coordinates of well-defined points in relation to the same set of points from a more accurate source. Usually, each country determines a maximum number of points which could present error values above a pre-established threshold. In many cases, the standards define the sample size as 20 points, with no more consideration, and fix this threshold in 10% of the sample. However, the sampling dimension (n), considering the statistical risk, especially when the percentages of outliers are around 10%, can lead to a producer risk (to reject a good map) and a user risk (to accept a bad map). This article analyzes this issue and allows defining the sampling dimension considering the risk of the producer and of the user. As a tool, a program developed by us allows defining the sample size according to the risk that the producer / user can or wants to assume. This analysis uses 600 control points, each of them with a known error. We performed the simulations with a sample size of 20 points (n) and calculate the associated risk. Then we changed the value of (n), using smaller and larger sizes, calculating for each situation the associated risk both for the user and for the producer. The computer program developed draws the operational curves or risk curves, which considers three parameters: the number of control points; the number of iterations to create the curves; and the percentage of control points above the threshold, that can be the Brazilian standard or other parameters from different countries. Several graphs and tables are presented which were created with different parameters, leading to a better decision both for the user and for the producer, as well as to open possibilities for other simulations and researches in the future. Keywords: Control quality; Cartography; Simulation; Sampling; Producer's risk; User's risk. Resumo:Em muitos países, o controle da acurácia posicional, feita por pontos, em Cartografia, corresponde à comparação entre conjuntos de coordenadas de pontos bem definidos em relação ao mesmo conjunto de pontos obtido a partir de uma fonte mais precisa. Normalmente, cada país fixa um número admissível de pontos que podem apresentar erros acima de um limite pré-estabelecido. Em muitos casos, as normas definem o tamanho da amostra (20 pontos), sem maiores considerações e fixam a condição de que somente 10% dos pontos pode ultrapassar certo limite. No entanto, a dimensão da amostragem (n), considerando o risco estatístico, especialmente quando os percentuais de outliers estão próximos de 10%, para mais ou para menos, conduzem a um risco do produtor (de rejeitar um bom mapa) e o risco do usuário (de aceitar um mapa ruim). Este artigo analisa esta questão e permite a definição da dimensão de amostragem considerando o risco do produtor e do usuário. O presente trabalho analisa essa questão e permite definir do tamanho da amostra em função do risco que o produt...

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