Hello aleksandar95,

I would like to send you the project I have already done, where I have input the values for sigma a, sigma b, and sigma c based on my experience and the explanations from the website. I would appreciate it if you could review it and tell me whether these values are suitable for this type of project.

A common approach to evaluate the a-priori stochastic model (i.e. σa, σb, and σc) is the variance-component estimation. The following image shows an example of the estimation results.

The most popular variance-component is the estimated a-posteriori variance of the unit weight. This variance is evaluated within the global test. However, the residuals and redundancies of the network can be grouped in order to derive sub-components. In JAG3D, the components refer to the observation type. Since the stochastic model for each terrestrial observation type consists of up to three components (i.e. σa, σb and σc), JAG3D derives sub-components of these variances. Each specific variance-component can be analysed in the same way as the global variance-component. The expectation value for each variance-component is $E\{\hat{\sigma}^2\} = \sigma^2$ (by convention, $\sigma^2 = 1$ in JAG3D).

What I am most interested in is what sigma a represents.

I have already answered this question and I am not sure how this question can be answered if you make your project available.

Is it the a priori standard deviation or not?

Have you read my answer to the same question? The answer is still yes.

Since we have concluded that sigma b is the instrument's accuracy.

The σb is an a-priori standard deviation which depends on the length d.

What interests me the most is what sigma a represents

It is not helpful if you ask me the same question over and over again without responding to my answer. In summery, σa is an a-priori standard deviation. It is independent of the length and is a random error of each single observation. This value is derived from empirical values for the instrument and the measurement process.

Kind regards
Micha