Proper utilization of the remote sensing payload output data in a real situation of a high-resolution satellite, deeply depends on the detailed orientation and relative attitude of the sensitive elements such as star sensors, optical payloads and etc. Very small unknown installation errors between star sensor and optical payload axes, will results in several hundred meters pointing error for imaging payload footprint on the ground targets. In practice, the final error and transform matrixes of elements coordinate systems to each other as well as to the satellites body must be accurately determined. Different methods are widely using in satellite industries where the CMM method is the most well-known of them. In this manuscript we introduced a practical methodology to extract the accurate mutual coordinate transformation matrix of sensitive satellite elements and to the satellite body. Our general approach was to improve the operational pointing accuracy of imaging payloads missions and improving the reliability of the final payload data. This method is using four theodolites in a predefined architecture along with some very accurate alignment cubes. After final assembly and integration of the whole satellite, final alignment accuracy depends on the individual instrument's accuracies. Using proper instruments, the attitude of sensitive elements coordinate system with respect to the satellite body coordinate system is measured at the order of several arcseconds. The proposed method, in addition to improving the final accuracy, has other advantages such as simplicity in setup and speeding up the implementation.