ROSIA

The implementation of ROSIA: Rotation-Search-Based Star Identification Algorithm. ROSIA is built on top of the source code obtained from https://cs.adelaide.edu.au/~aparra/project/pcr/, which is an implementation of the paper "Parra Bustos, Alvaro, Tat-Jun Chin, and David Suter. "Fast rotation search with stereographic projections for 3d registration." Proceedings of the IEEE conference on computer vision and pattern recognition. 2014."

Prerequsites:
CMAKE
g++
Python3
numba (optional) < To speed up operations. Comment out line 3 and 23 in 'catalog_preprocessing.py' if this library is not installed.

To install:
mkdir build cd build cmake .. make

To create specific onboard catalog:
./create_onboard_dataset.sh

Hyperparamters:

1. mag_thres - include only stars that are observable within the sensor's sensitivity/
2. dist_thres - (in degrees) parameters to decide which stars are too close to be considered as separate stars.
3. k - the number of closest distances to constraint each star, k = 2 is the triplet constraint as proposed in the paper.

Format of the pre-processed catalog:
x y z Magnitude HIP index CD1 CD2

Legends:
x,y,z - the star vectors in the inertia's coordinates
HIP index - the ID of stars in the HIPPARCOS catalog CD1 - closest angular distance CD2 - second closest angular distance

To create testing data:
./create_onboard_dataset.sh

Format of the testing data ('scene_id.txt'):
x y z Magnitude HIP index

Legends:
x,y,z - the star vectors in the camera's coordinates

Format of the testing data ('rot.txt')
The 3x3 rotation matrix that rotates the testing star vectors into catalog's inertia's coordinates.

Hyperparamters:

1. dist_noise_sigma - the sigma of the angular distance noise.
2. mag_noise_sigma - the sigma of the magnitude noise.
3. num_false_stars - the number of false stars in each testing instance.
4. num_scenes - number of scenes to be generated.
5. hip_catalog_filename - the directory of the original hipparcos catalog file.

To run ROSIA:
./demo.sh

Hyperparamters:

1. dist_th - angular distance threshold (radians) to facilitate angular uncertainty of the star vectors.
2. mag_th - magnitude threshold (magnitude) to facilitate magnitude uncertainty of the stars.

Format of the output text files:
lines 1 to N-3
x y z HIP index

lines N-3 to N
The (estimated) 3x3 rotation matrix that rotates the testing star vectors into catalog's inertia's coordinates.

To run the multi-pole Star-ID algorithm [1][2]. Note that the implementation doesn't utilise the k-vector technique, hence it is much slower than the actual algorithm. However, the ID results are not affected.

./MPA.sh

Format of the output text files.
x y z HIP index

[1] Schiattarella, Vincenzo, Dario Spiller, and Fabio Curti. "A novel star identification technique robust to high presence of false objects: The Multi-Poles Algorithm." Advances in Space Research 59.8 (2017): 2133-2147. [2] https://www.gaussteam.com/wordpress/wp-content/uploads/2018/02/IAA-AAS-CU-17-05-02-Schiattarella.pdf