Abstract:

In view of the characteristic that the space targets can be observed intermittently by distributed star sensors, the observation information association of the space target in different time periods under star sensors is taken as the premise of accurate space object calibration based on the star sensors. The space target motion characteristic is considered. Combined with the characteristics of the space traget motion, on the basis of the previous two threshold fuzzy correlation, the track segment association algorithm of the space target under the distributed star sensor is proposed by adding the normal vector constraint of orbit plane, filtering the candidate association objects and simplifying the cost of association operation. Through the simulation, the divergence of the track extrapolation error with time is analyzed under six sets of noise levels. And the reference value of the adjustment coefficient in the fuzzy membership function is given, which makes the correlation similarity of different targets more significant under long interval. The simulation results show that the correlation accuracy of the proposed algorithm is higher than that of the nearest neighbor and the traditional fuzzy association under certain noise. When the standard deviation of the initial orbital error is 6 km at each axis position and 6 m/s at each axis velocity, the adjacent targets with a minimum phase difference of 0.5° can be distinguished. Correlation accuracy of interval 2 h is 98%, and the correlation accuracy is 90% of 7 h interval.

Key words: target association, star sensor, fuzzy association, track segment