A modiΡed pseudo-noise（PN） code regeneration method is proposed to improve the clock tracking accuracy without impairing the code acquisition time performance.Thus,the method can meet the requirement of high accuracy ranging measurements in short time periods demanded by radio-science missions.The tracking error variance is derived by linear analysis.For some existing PN codes,which can be acquired rapidly,the tracking error variance performance of the proposed method is about 2.6 dB better than that of the JPL scheme（originally proposed by Jet Propulsion Laboratory）,and about 1.5 dB better than that of the traditional double loop scheme.
Xiaojun Jin Zhonghe Jin Chaojie Zhang Jianwen Jiang Yangming Zheng
In a pico-satellite with small volume, measurements from on-board three-axis magnetometer （TAM） are not accurate, as it can be easily disturbed by other electronic systems. To improve its accuracy, a scheme of compensation methods is introduced in this article. The scheme is based on an improved meast, rement model of pico-satellite TAM, and it mainly consists of three steps. First, in satellite design stage, several techniques are recommended to simplify the afterwards compensations. Then after satellite assembly, TAM ground tests and pre-launch calibration with least-square batch filter are introduced to improve magnetometer performance. At the end, a post-launch calibration with unscented Kalman filter （UKF） is implemented with in-orbit data. The compensation scheme is used in the development of Chinese pico-satellite ZDPS-1A made by Zhejiang University. Results show that with the introduced compensation scheme, the maximum error of ZDPS-1A TAM can be reduced from 80 mG to 6 naG （1 G=10^-4T）.
This article presents a near-Earth satellite orbit estimation method for pico-satellite applications with light-weight and low-power requirements. The method provides orbit information autonomously from magnetometer and sun sensor, with an extended Kalman filter （EKF）. Real-time position/velocity parameters are estimated with attitude independently from two quantities： the measured magnitude of the Earth’s magnetic field, and the measured dot product of the magnetic field vector and the sun vector. To guarantee the filter’s effectiveness, it is recommended that the sun sensor should at least have the same level of accuracy as magnetometer. Furthermore, to reduce filter’s computation expense, simplification methods in EKF’s Jacobian calculations are introduced and testified, and a polynomial model for fast magnetic field calculation is developed. With these methods, 50% of the computation expense in dynamic model propagation and 80% of the computation burden in measurement model calculation can be reduced. Tested with simulation data and compared with original magnetometer-only methods, filter achieves faster convergence and higher accuracy by 75% and 30% respectively, and the suggested simplification methods are proved to be harmless to filter’s estimation performance.
