This program makes a surface by solving for the spacecraft position, spacecraft pointing, and landmark locations. This procedure iterates the solutions for camera pointing and landmark vectors sequentially.

(./) added descriptions below copied from other entries. Check for accuracy here.

Required Files

NM: IMAGEFILES is not needed as input. geometry does not read the image files

Output Files

Optional Files

User Warning

Using geometry

The inputs for geometry are:

Here are two annotated samples that show geometry inputs:

 120<- do 1 followed by 2
 30 <- do them 30 times
 y  <- use limbs for pointing
 n  <- stop when done

 20 <- do 2 only
 10 <- do it 10 times
 n  <- don't use limbs for pointing
 n  <- stop when done

The default is to do these operations for all landmarks in LMRKLIST.TXT and all images in PICTLIST.TXT.

If INIT_LITHOS.TXT contains a record




then the files used are reduced. "filename1" is used instead of PICTLIST.TXT and "filename2" is used instead of LMRKLIST.TXT.

Additional Reference

Geometry Estimation Terms

geometry_imagedataoffset.jpg geometry_errosfromincorrectdataoffset.jpg

More Detailed Description of Geometry

NM comments: Solution of landmarks is also based on two additional constraints: limb height constraint constraints from the shape model

solution of camera position and pointing is also based on additional constraints image-to-image correlation limb appearance in image

other comments: option 1 solves for landmarks based on all 4 contributions, from position & pointing nominals, from relative landmark-to-landmark, from limbs and from shape model

option 2 solves for camera position and pointing based on 4 constraints, from nominal position, pointing from landmarks from image-to-image correlation and from limbs

The output covariances from one iteration become the input covariances for the next iteration so the schematic for updating sumfiles, and lmkfiles, should include the update of their uncertainties.

The typical use is a series of steps such as 120, 3 or more iterations. Assume we created some new landmarks. The above steps mean that we first use the apriori position & pointing information to solve for the landmarks, then, since there's some error in the a priori position and pointing inputs we use the landmarks to solve for position and pointing and so on until the corrections have converged, typically 3 iterations. However if we are in a situation where believe the landmarks are correct and the camera pointing/position are incorrect then we simply run option 2 only. This is what autoregister does, when we add new images to an existing landmark database. If we are in a scenario that we believe the camera position/pointing are correct and not the landmarks then we run option 1 only. Another consideration is the relative contribution of each constraint in the landmark/position/pointing solution via the additional weights in INIT_LITHOS.TXT, LMKWTS and PICWTS E.g., if the shape model is too coarse for the resolution of maps we are working with we may want to reduce the influence of the shape model as a constraint in the solution of the landmarks by reducing the value of WR in INIT_LITHOS.TXT If we believe that the S/C state is very well known compared to the landmarks we may want to not allow the landmarks to change the camera position much, by either using a very small position uncertainty in the nominals or in addition by reducing the value of WB in PICWTS


(Compiled by TC)