GNSS autonomous navigation method for HEO spacecraft

For global navigation satellite system(GNSS)in the application of high earth orbit(HEO)determination,there are problems such as small number of visible satellites and weak signal magnitude.The transmitting and receiving errors of GNSS signal in the environment of HEO space are analyzed,and related compensating scheme is also proposed.Acquisition of GNSS signal is implemented by using weak signal acquisition technology based on Duffing.Precise tracking of weak GNSS signal is also realized by adopting dynamic detection and compensation technology based on Duffing chaotic oscillator.Simulation results show that,certain acquisition sensitivity and navigation precision can be reached,and the acquisition and tracking of weak GNSS signal can be realized by using the proposed technology,which provides good technology support for autonomous navigation of HEO and large elliptical spacecrafts.

Accurate 3D geometry measurement for non-cooperative spacecraft with an unfocused light-field camera

This work explores an alternative 3D geometry measurement method for non-cooperative spacecraft guiding navigation and proximity operations.From one snapshot of an unfocused light-field camera, the 3D point cloud of a non-cooperative spacecraft can be calculated from sub-aperture images with the epipolar plane image(EPI) based light-field rendering algorithm.A Chang'e-3 model(7.2 cm×5.6 cm×7.0 cm) is tested to validate the proposed technique.Three measurement distances(1.0 m, 1.2 m, 1.5 m) are considered to simulate different approaching stages.Measuring errors are quantified by comparing the light-field camera data with a high precision commercial laser scanner.The mean error distance for the three cases are 0.837 mm, 0.743 mm, and 0.973 mm respectively, indicating that the method can well reconstruct 3D geometry of a non-cooperative spacecraft with a densely distributed 3D point cloud and is thus promising in space-related missions.

Hardware-in-the-loop simulation technology of wide-band radar targets based on scattering center model

Hardware-in-the-loop （HWIL） simulation technology can verify and evaluate the radar by simulating the radio frequency environment in an anechoic chamber. The HWIL simulation technology of wide-band radar targets can accurately generate wide-band radar target echo which stands for the radar target scattering characteristics and pulse modulation of radar transmitting signal. This paper analyzes the wide-band radar target scattering properties first. Since the responses of target are composed of many separate scattering centers, the target scattering characteristic is restructured by scattering centers model. Based on the scattering centers model of wide-band radar target, the wide-band radar target echo modeling and the simulation method are discussed. The wide-band radar target echo is reconstructed in real-time by convoluting the transmitting signal to the target scattering parameters. Using the digital radio frequency memory （DRFM） system, the HWIL simulation of wide-band radar target echo with high accuracy can be actualized. A typical wide-band radar target simulation is taken to demonstrate the preferable simulation effect of the reconstruction method of wide-band radar target echo. Finally, the radar target time-domain echo and high-resolution range profile （HRRP） are given. The results show that the HWIL simulation gives a high-resolution range distribution of wide-band radar target scattering centers.

Toward the recognition of spacecraft feature components:A new benchmark and a new model

Countries are increasingly interested in spacecraft surveillance and recognition which play an important role in on-orbit maintenance,space docking,and other applications.Traditional detection methods,including radar,have many restrictions,such as excessive costs and energy supply problems.For many on-orbit servicing spacecraft,image recognition is a simple but relatively accurate method for obtaining sufficient position and direction information to offer services.However,to the best of our knowledge,few practical machine-learning models focusing on the recognition of spacecraft feature components have been reported.In addition,it is difficult to find substantial on-orbit images with which to train or evaluate such a model.In this study,we first created a new dataset containing numerous artificial images of on-orbit spacecraft with labeled components.Our base images were derived from 3D Max and STK software.These images include many types of satellites and satellite postures.Considering real-world illumination conditions and imperfect camera observations,we developed a degradation algorithm that enabled us to produce thousands of artificial images of spacecraft.The feature components of the spacecraft in all images were labeled manually.We discovered that direct utilization of the DeepLab V3+model leads to poor edge recognition.Poorly defined edges provide imprecise position or direction information and degrade the performance of on-orbit services.Thus,the edge information of the target was taken as a supervisory guide,and was used to develop the proposed Edge Auxiliary Supervision DeepLab Network(EASDN).The main idea of EASDN is to provide a new edge auxiliary loss by calculating the L2 loss between the predicted edge masks and ground-truth edge masks during training.Our extensive experiments demonstrate that our network can perform well both on our benchmark and on real on-orbit spacecraft images from the Internet.Furthermore,the device usage and processing time meet the demands of engineering applications.

System Design for Pose Determination of Spacecraft Using Timeof-Flight Sensors

The pose determination between nanosatellites and the cooperative spacecraft is essential for swarm in-orbit services.Timeof–flight(ToF)sensors are one of the most promising sensors to achieve the tasks.This paper presented an end-to-end assessment of how these sensors were used for pose estimation.First,an embedded system was designed based on the ToF camera with lasers as a driven light source.Gray and depth images were collected to detect and match the cooperative spacecraft in real time,obtaining the pose information.A threshold-based segmentation was proposed to find a small set of the pixels belonging to reflector markers.Only operating on the defined active pixel set reduced computational resources.Then,morphological detection combined with an edge following-based ellipse detection extracted the centroid coordinate of the circular marker,while the center-of-heart rate was calculated as the recognition condition.Next,the marker matching was completed using a deterministic annealing algorithm,obtaining two sets of 3D coordinates.A singular value decomposition(SVD)algorithm estimated the relative pose between the nanosatellite and the spacecraft.In the experiments,the pose calculated by the TOF camera reached an accuracy of 0.13 degrees and 2 mm.It accurately identified the markers and determined the pose,verifying the feasibility of the ToF camera for rendezvous and docking.

Active Magnetic Compensation Based on Parametric Resonance Magnetometer

Based on the parametric resonance magnetometer(PRM)theory,this paper establishes an experimen-tal system of PRM.The experimental results are consistent with the theoretical predictions.A PRM has been developed with sensitivity of 0.5 pT/Hz^(1/2),which can detect the magnitude of residual magnetic field;furthermore,a proportion-integration-differentiation(PID)closed-loop magnetic compensation system of the residual magnetic field also has been realized.Compared with open-loop compensation,the PID closed-loop compensation reduces the average value of the residual magnetic field in the z-axis direction from 0.0244nT to-0.0023nT,and the mean-square error from 0.2083 nT to 0.0691 nT.In the same way,the average value of the residual magnetic field in the y-axis direction is reduced from 0.0816nT to-0.0042nT,and the mean-square error from 0.1316nT to 0.0461 nT.The magnitude of residual magnetic fields in both directions is decreased to the order of picotesla(pT).In addition,based on the signal waveforms of the magnetometer,a method of verifying the effect of magnetic compensation is proposed.

Drag derived altitude aided navigation method

The navigation problem of the lifting reentry vehicles has attracted much research interest in the past decade. This paper researches the navigation in the blackout zone during the reentry phase of the aircraft, when the communication signals are attenuated and even interrupted by the blackout zone. However, when calculating altitude, a pure classic inertial navigation algorithm appears imprecise and divergent. In order to obtain a more precise aircraft altitude, this paper applies an integrated navigation method based on inertial navigation algorithms, which uses drag derived altitude to aid the inertial navigation during the blackout zone. This method can overcome the shortcomings of the inertial navigation system and improve the navigation accuracy. To further improve the navigation accuracy, the applicable condition and the main error factors, such as the atmospheric coefficient error and drag coefficient error are analyzed in detail. Then the damping circuit design of the navigation control system and the damping coefficients determination is introduced. The feasibility of the method is verified by the typical reentry trajectory simulation, and the influence of the iterative times on the accuracy is analyzed. Simulation results show that iterative three times achieves the best effect.