Jiazhen Lu

False star detection and isolation during star tracking based on improved chi-square tests

The star sensor is a precise attitude measurement device for a spacecraft. Star tracking is the main and key working mode for a star sensor. However, during star tracking, false stars become an inevitable interference for star sensor applications, which may result in declined measurement accuracy. A false star detection and isolation algorithm in star tracking based on improved chi-square tests is proposed in this paper. Two estimations are established based on a Kalman filter and a priori information, respectively. The false star detection is operated through adopting the global state chi-square test in a Kalman filter. The false star isolation is achieved using a local state chi-square test. Semi-physical experiments under different trajectories with various false stars are designed for verification. Experiment results show that various false stars can be detected and isolated from navigation stars during star tracking, and the attitude measurement accuracy is hardly influenced by false stars. The proposed algorithm is proved to have an excellent performance in terms of speed, stability, and robustness.

On-orbit calibration for star sensors without priori information

The star sensor is a prerequisite navigation device for a spacecraft. The on-orbit calibration is an essential guarantee for its operation performance. However, traditional calibration methods rely on ground information and are invalid without priori information. The uncertain on-orbit parameters will eventually influence the performance of guidance navigation and control system. In this paper, a novel calibration method without priori information for on-orbit star sensors is proposed. Firstly, the simplified back propagation neural network is designed for focal length and main point estimation along with system property evaluation, called coarse calibration. Then the unscented Kalman filter is adopted for the precise calibration of all parameters, including focal length, main point and distortion. The proposed method benefits from self-initialization and no attitude or preinstalled sensor parameter is required. Precise star sensor parameter estimation can be achieved without priori information, which is a significant improvement for on-orbit devices. Simulations and experiments results demonstrate that the calibration is easy for operation with high accuracy and robustness. The proposed method can satisfy the stringent requirement for most star sensors.

Accurate and Autonomous Star Acquisition Method for Star Sensor under Complex Conditions

Star sensor is a preferred attitude measurement device for its extremely high accuracy. Star acquisition is the essential and critical procedure, which is aiming at acquiring accurate star areas. However, degenerated acquisition results under complex conditions become one of the major restrictions for modern star sensor. In this paper, an accurate and autonomous star acquisition method is proposed. Mathematical morphology and variable thresholding are combined for accurate star extraction; motion PSF is estimated in frequency domain and nonlinear filter is adopted for star restoration. Accurate star acquisition can be achieved based on only one star image. Simulations and laboratory experiments are conducted for verification. Several existing methods are also reproduced for comparison. Acquisition results demonstrate that the proposed method is effective and an excellent performance can be achieved autonomously under complex conditions, along with more detected stars and improved acquisition accuracy.

Angular velocity estimation based on star vector with improved current statistical model Kalman filter.

Angular velocity information is a requisite for a spacecraft guidance, navigation, and control system. In this paper, an approach for angular velocity estimation based merely on star vector measurement with an improved current statistical model Kalman filter is proposed. High-precision angular velocity estimation can be achieved under dynamic conditions. The amount of calculation is also reduced compared to a Kalman filter. Different trajectories are simulated to test this approach, and experiments with real starry sky observation are implemented for further confirmation. The estimation accuracy is proved to be better than 10-4u2009u2009rad/s under various conditions. Both the simulation and the experiment demonstrate that the described approach is effective and shows an excellent performance under both static and dynamic conditions.

Optimal scheme of star observation of missile-borne inertial navigation system/stellar refraction integrated navigation

To achieve accurate and completely autonomous navigation for spacecraft, inertial/celestial integrated navigation gets increasing attention. In this study, a missile-borne inertial/stellar refraction integrated navigation scheme is proposed. Position Dilution of Precision (PDOP) for stellar refraction is introduced and the corresponding equation is derived. Based on the condition when PDOP reaches the minimum value, an optimized observation scheme is proposed. To verify the feasibility of the proposed scheme, numerical simulation is conducted. The results of the Extended Kalman Filter (EKF) and Unscented Kalman Filter (UKF) are compared and impact factors of navigation accuracy are studied in the simulation. The simulation results indicated that the proposed observation scheme has an accurate positioning performance, and the results of EKF and UKF are similar.

Classification of Methods in the SINS/CNS Integration Navigation System

The known methods used for strapdown inertial navigation system (SINS)/celestial navigation system (CNS) integration are classified based on two categories of measurement in this paper. One category is called the “attitude observation method,” in which the measurement is derived by the difference between the optimal attitude information of the star sensor and the SINS. The other category is called the “star vector observation method,” in which the measurement is derived by the difference between the original star vector information of the star sensor. The attitude angle observation equation of the first category is generally obtained by using the relationship between the attitude angle errors and the Phi-angle (or tilt errors), and the attitude matrix observation equation is obtained by using the relationship between the attitude matrix and the Psi-angle (or platform errors). However, the interrelationship between these two observation equations has not been developed in previous studies. A simpler attitude angle observation method based on the Psi-angle instead of the Phi-angle is proposed to reveal the interrelationship between these two methods. This proposed method is basically the principle behind the SINS/CNS integration and depicts the physical meaning clearly. In addition, the internal relationships of the second category and the interrelationship of these two categories are also analyzed to show their equivalence to each other. Numerical simulations verify the correctness of the analysis. Experimental studies indicate that the integration accuracy of the two categories is also exactly equivalent.

A hybrid method for accurate star tracking using star sensor and gyros

Star tracking is the primary operating mode of star sensors. To improve tracking accuracy and efficiency, a hybrid method using a star sensor and gyroscopes is proposed in this study. In this method, the dynamic conditions of an aircraft are determined first by the estimated angular acceleration. Under low dynamic conditions, the star sensor is used to measure the star vector and the vector difference method is adopted to estimate the current angular velocity. Under high dynamic conditions, the angular velocity is obtained by the calibrated gyros. The star position is predicted based on the estimated angular velocity and calibrated gyros using the star vector measurements. The results of the semi-physical experiment show that this hybrid method is accurate and feasible. In contrast with the star vector difference and gyro-assisted methods, the star position prediction result of the hybrid method is verified to be more accurate in two different cases under the given random noise of the star centroid.

A novel star extraction method based on modified water flow model

Star extraction is the essential procedure for attitude measurement of star sensor. The great challenge for star extraction is to segment star area exactly from various noise and background. In this paper, a novel star extraction method based on Modified Water Flow Model(MWFM) is proposed. The star image is regarded as a 3D terrain. The morphology is adopted for noise elimination and Tentative Star Area(TSA) selection. Star area can be extracted through adaptive water flowing within TSAs. This method can achieve accurate star extraction with improved efficiency under complex conditions such as loud noise and uneven backgrounds. Several groups of different types of star images are processed using proposed method. Comparisons with existing methods are conducted. Experimental results show that MWFM performs excellently under different imaging conditions. The star extraction rate is better than 95%. The star centroid accuracy is better than 0.075 pixels. The time-consumption is also significantly reduced.