  Space surveillance by radar is especially used for the low Earth orbit to
maintain a database, also called catalogue, of objects on orbit. Among others,
surveillance radars which are constantly scanning a region of interest in the
sky are used for this purpose. The detections from such a radar which cannot be
assigned to an already known catalogue object might not contain enough
information to obtain a reliable initial orbit for a new catalogue entry from a
single measured pass, also called tracklet. Instead, two tracklets can be
combined to improve the quality of the initial orbit which leads to the
correlation problem. This means that it has to be tested whether two tracklets
belong to the same object and an initial orbit has to be derived by combining
the tracklets. A common approach to condense the information in the tracklet is
fitting them with so-called attributables. Because radar observations include
different types of observables, the fitting of these attributables has to be
considered as an important part of the entire correlation process. This paper
analyses the effect of the attributable fitting considering the achieved
accuracy and influence on the tracklet correlation. A new singularity-free
coordinate system is introduced, which improves the results of the fitting and
correlation. Finally, a test on a simulated survey scenario introduces two
additional filters to remove false positive correlations. It is shown that the
attributable-based approach can be applied successfully to tracklets of up to
three minutes length with different detection frequencies.
