Abstract： In order to solve the problem of the relationship between navigationobservability and accuracy in nonlinear navigation system, the observability analysis method based on the error covariance matrix is adopted.The nonlinear predictive filter(NPF) is improved combined with extended Kalman filter(EKF),and the error covariance of improved predictive filter is deduced. Then the eigenvalue decomposition is carried out to analyze the relationship between the eigenvalue and navigation accuracy.Taking the autonomous navigation system of the small celestial probe landing as an example, the simulation validation is carried out and the validity and accuracy of the improved NPF algorithm are verified comparing with the EKF.The influence of different error factors on observability is analyzed, which provide a reference for the filter design of autonomous navigation system in the actual spacecraft process.

Abstract： The successful use of the standard extended Kalman filter (EKF) is restricted by the requirement on the statistics information of the measurement noise. The filtering performance may decline due to the statistical uncertainty. Although the adaptive extended Kalman filter (AEKF) is available for recursive covariance estimation, it is often less accurate than the EKF with accurate noise statistics. Aiming at this problem, this paper develops a parallel adaptive extended Kalman filter (PAEKF) by combining the EKF and the AEKF with an adaptive law, such that the final state estimate is dominated by the EKF when the prior noise covariance is accurate, while the AEKF is activated when the actual noise covariance deviates from its nominal value. The PAEKF can reduce the sensitivity of the algorithm to the model uncertainty, and ensure the estimation accuracy in the normal case. For spacecraft relative attitude and position estimation, the simulation results demonstrate that the PAEKF has the advantage of both the AEKF and the EKF.

Abstract： In this paper, the realization methods of “sum of all coefficients being one (SACO)” for the strongly uncertain system are researched, where the strongly uncertain system means that its static gain and its bound are unknown and the range of the static gain is large. The principle SACO was found by Prof. Hongxin Wu in 1980’, which shows that the sum of the coefficients for the discretized systems of unknown continuous systems is one under certain conditions, playing an important role on the solution to the key problems in closeloop identification and adaptive control. A transformation is needed for systems to realize the conditions because the SACO holds under certain conditions, where using the reciprocal of the nominal value of the static gain as the input transformation has been widespread utilized due to easy implementation. However, when the uncertainties are larger, the transformation will bring larger errors. This problem is deeply investigated in this paper. We specifically show that the effects on the realization of SACO of the ratio between the uncertainties and the nominal value of the static gain. When the ratio is lower, the SACO can be realized approximately; otherwise, when the ratio is higher, we need to furthermore choose appropriate sampling duration to approximately realize the SACO. The conclusions obtained in this paper lay certain foundation on the practical applications of the characteristic model theory.

 3DTOF camera can obtain the amplitude and depth map of target at the same time. Threedimension clouds of points of target are achieved at real time, which is a fine technology for threedimension imaging. In this paper, we introduce the operational principle and application scenarios of 3DTOF camera, and take a picture of target imitating the application of detection of short range target in the space. At the same time, we analyze the influence factors of imaging in different conditions, and the source of deviation and calibration methods. While, via the achievement of depth information, we test accuracy of distance detection.

 The spinning satellite must actively rotate after satelliterocket separation, so the calculation of the spinning rate is the premise to judge the spin of the satellite. The sun sensor is the most effective method to calculate the spinning rate after satelliterocket separation, but it is disabled when the satelliterocket separation is under shadow, which is a new question for the calculation of the spinning rate. There are also earth sensor and acceleration sensor on the spinning satellite. The acceleration sensor is used for the nutation measure; if the nutation motion is weak, it cannot feel the cycle of the sine signal, so it is uncertain for the spinning rate calculation. Earth sensor is usually used on synchronous orbit; but when satelliterocket separation happens, the orbit height is too low and the counter will overflow. The method in this text uses the cycle integration to calculate the spinning rate when the counter overflows. This method is used on FY2(09) satellite, and it is also a reference for the application of the earth sensor in different orbit.

 In the field of space, the means of repairing spacecraft onboard are mainly about the onboard repair of software. The SPARC platform is the most widely used processor of aerospace industry in Chinese. Considering the spacecraft software onboard repair issues for SPARC platforms, a method of quadratic linking is proposed to generate onboard software repair inject code, which can solve the problem of onboard repair injection code relocation. After being injected through the ground remote control, using the hook function embedded in the spacecraft onboard software, the flexible implementation of the dynamic replacement and the recovery of the onboard function module can greatly improve the onboard software recovery capability of the SPARC platform. Through the practical engineering application of multiple onboard spacecraft, the feasibility and correctness of the method are proved, and it has a good engineering application value.

Spacebased light gas gun (SLGG) provides a more effective way for space attack and defense and space debris removal due to its stable performance and easy miniaturization. The primary precondition of the SLGG to accomplish the task is to strike the space target accurately. To evaluate the firing accuracy comprehensively and accurately, firstly, the shooting error distribution model is established. Three firing accuracy evaluation factors, including shooting accuracy, dispersion and hit probability are formulated. Then, a general framework, including simulation fire test, data preprocessing, fire accuracy evaluation, is proposed to evaluate SLGG firing accuracy. Finally, firing accuracy evaluation of the target with circular orbit at the height of 10354 km is performed via the designed framework. The results reveal that the firing accuracy is about 48 meters and CEP is about 87 meters under current defined scenarios. The errors are mainly caused by the orbit determination of noncooperative target. Moreover, the influence of errors on firing accuracy is amplified due to the long range. The hit probability is about one in a thousand, and increases with the increase of target size.