Algorithm with Patterned Singular Value Approach for Highly Reliable Autonomous Star Identification

In the work reported in this paper, a lost-in-space star pattern identification algorithm for agile spacecraft was studied. Generally, the operation of a star tracker is known to exhibit serious degradation or even failure during fast attitude maneuvers. While tracking methods are widely used solutions to handle the dynamic conditions, they require prior information about the initial orientation. Therefore, the tracking methods may not be adequate for autonomy of attitude and control systems. In this paper a novel autonomous identification method for dynamic conditions is proposed. Additional constraints are taken into account that can significantly decrease the number of stars imaged and the centroid accuracy. A strategy combining two existing classes for star pattern identification is proposed. The new approach is intended to provide a unique way to determine the identity of stars that promises robustness against noise and rapid identification. Moreover, representative algorithms implemented in actual space applications were utilized as counterparts to analyze the performance of the proposed method in various scenarios. Numerical simulations show that the proposed method is not only highly robust against positional noise and false stars, but also guarantees fast run-time, which is appropriate for high-speed applications.

Optimization of guide star catalog for daytime star sensors

Daytime star sensor provides accuracy navigation information to air vehicles near the ground in the daytime by observing stars. It has been an important development of modern star sensors. In order to achieve a high signal-to-noise ratio, daytime star sensors work in the infrared band to avoid interferences from sky background. Daytime star sensors output accurate attitudes by identifying the observed stars in the field of view (FOV) according to the loaded guide star catalog. Guide stars are usually required to be distributed uniformly on the celestial sphere to improve the performance of star pattern identification. The parameters including limiting magnitude and FOV are determined by processing the 2MASS star catalog as the original star data and performing star distribution statistics. After constellation features are discussed, the idea of distributing stars in the local FOV to constellations is put forward by using the star pair angular separations. An optimization algorithm to build the guide star catalog for daytime stars is proposed to achieve evenly distributed guide stars. The guide star catalog is established and analyzed, proving that the proposed algorithm has simple calculation and easy realization. The Boltzmann entropy of obtained guide star catalog drops two orders of magnitude. Guide stars are distributed more uniformly.

Pentagram star pattern identification algorithm applied in three-head star sensors

A pentagram star pattern identification algorithm for three-head star sensors was proposed. Its realization scheme was presented completely. Simulated star maps were produced by letting the three-head star sensor travel around the celestial sphere randomly and image the observed stars. Monte Carlo experiments were carried out. The performances of the pentagram algorithm were evaluated. It proves that its identification success rate reaches up to 98%.

A New Simplified Selection Algorithm of the Guide Star Catalogue for a Star Sensor

A guide star catalogue characterised by fewer guide stars, uniform distribution and high completeness is conducive to the improvement of star pattern identification and star tracking efficiency, and it has become an important study objective. A screening method, which takes “quasi-uniform distribution” of space solid angles as the principle and the size of the space solid angle corresponding to 4°×4° on the equator as the reference and divided the whole celestial sphere into 2,664 sub-blocks in sequence, is proposed in this paper. Based on this method, a “quasi-uniform” guide star catalogue with 2,937 guide stars was obtained. According to our ergodic statistical analysis of the whole celestial sphere, in a 12°×12° field of view, after the space solid angle method was used to divide the celestial sphere, the probability of emergence of three guide stars was 99·9% or above, while the number of guide stars decreased by 12·6% compared to the inscribed cube method. It can be concluded that when the completeness is equal, the space solid angle method is superior to the inscribed cube method in both capacity and distribution uniformity.