Table 2.

Scoring criteria star identification algorithm.

Criterium	Definition
Identification Rate	The ratio of scenes in which the correctly identified number of stars i is larger than a pre-defined number N to the scenes where i<N
Runtime	The average time the identification algorithm takes to identify N body vectors in one scene
Storage Size	The amount of storage memory the identification algorithm uses
Memory usage	The amount of Random Access Memory the identification algorithm uses on average
False Positive Rate	The rate of wrongly identified scenes with a positive confidence flag
False Star Robustness	The robustness of the algorithm against the number of false stars f in a scene, taking into consideration the ratio of f to the number of real stars present in the scene r. (Note that real stars not present in the database may be considered as false stars)—usually in terms of identification rate over f
Dropped Star Robustness	The robustness of the algorithm against the number of dropped stars d, taking into consideration the ratio of d to r—usually in terms of identification rate over d
Positional Noise Robustness	The robustness of the algorithm with respect to the positional noise, usually in terms of identification rate over the average positional noise in a scene
Magnitude Noise Robustness	The robustness of the algorithm with respect to the magnitude noise, usually in terms of identification rate over the average positional noise in a scene
Angular Rate Robustness	The robustness of the algorithm with respect to the simulated angular rate of the sensor—usually in terms of identification rate over angular rate.
Iterations per acquisition	The average number of iterations needed in order to identify N stars.
Complexity	The level of complexity of implementation and maintenance of the algorithm as well as the database structure