Which statement best describes a priori observation weights?

• A. They reflect known precision before processing.
• B. They are determined after the adjustment.
• C. They are used to drop poor data.
• D. They modify the satellite ephemeris.

Answer: (A)

A priori observation weights express the expected precision of measurements before any adjustment is performed. They come from known instrument characteristics, calibration results, and prior measurement statistics, and they are used to form the weighting in the least-squares solution (typically as the inverse variances). This means observations deemed more precise get higher influence on the solution, while less precise ones contribute less. These weights are fixed before processing and do not come from the adjustment results themselves, which would be a posteriori information. They also don’t inherently drop data or modify the satellite ephemeris; they simply determine how strongly each observation type or measurement instance pulls the estimated parameters during the adjustment.