To satisfy the modern track traffic's demand for maintaining high precision and continuity of navigation under complex environmental conditions,and to address the issue of positioning drift caused by data outages in nonlinear dynamic integrated navigation systems,this paper proposes a novel adaptive estimation method for observation errors in nonlinear dynamic integrated navi gation systems. This method is based on a Probabilistic Time Series Transformer model,aiming to resolve the aforementioned issues. By introducing self-learning capabilities through the Probabilistic Time Series Transformer,the method adaptively adjusts the impact of state prediction and observation information outages on the dynamic navigation system. The Probabilistic Time Series Transformer is composed of a dual-loop system of a generative model and an inference model, combined with LSTM network to tackle the challenges of multivariate time series modeling. The integrated navigation system based on the Probabilistic Time Series Transformer optimizes the error compensation mechanism by establishing a relationship between the current Kalman filter gain and the optimal estimation error,thereby improving the accuracy and stability of the nonlinear navigation system. Experimental results demonstrate that the proposed method not only effectively controls the impact of GNSS outages on the nonlinear navigation system but also accurately estimates and compensates for observation model system errors. The average positioning error in various complex scenarios is less than 10m. The suppression of positioning drift in the observation model is better than that of other filtering methods.

The space adhesive climbing robot can be attached to the outer surface of the spacecraft and complete the external inspection and operation tasks independently,which is an important way to realize the long-term unmanned in-orbit service of the spacecraft. In order to solve the problem of insufficient generalization ability of the control strategy of the adhesive climbing robot after unexpected changes in spacecraft surface characteristics,the mechanism of adhesion force is constructed under the framework of reinforcement learning,and the intensive reward function is constructed by combining the “follow-update”mechanism of the foot contact force,and the proximal policy optimization-clip (PPO-clip)algorithm is used to train and generate the adhesion crawling strategy of the robot in microgravity environment. The results show that the strategy convergence rate increases by about 14.81% under the “follow-update”mechanism of foot contact force. The climbing strategy obtained can maintain the adhesion stability of the robot on a flat surface,and has the ability to reach the target position with an arrival error of less than 0.1m. On surfaces with an unpredictable height change of ±40mm and an unpredictable slope change of ±18°,the climbing strategy obtained on the flat surface can achieve stable adhesion climbing of the robot.

In order to study the impact of variable engine thrust on rocket ballistic performance, the optimization and analysis of rocket trajectory based on variable thrust engine is carried out by using the Gaussian pseudo-spectrum method,including trajectory comparison analysis under variable thrust and fixed thrust,and the influence of thrust adjustment ability on trajectory and trajectory comparison analysis based on variable thrust engine under different optimization objectives. The results show that if the specific impulse is unchanged and engineering constraints are not considered,the thrust adjustment ability of the engine will make the trajectory of the rocket more flexible,and the speed and height coverage of the flight end will be increased,and the normal overload of the flight will be reduced. In addition,the greater the engine's ability to regulate thrust,the more adaptable a rocket's active segment trajectory is.

Aiming at the problem of multiple satellites collaborative planning with unobservable ground moving targets,this paper studies the online imaging scheduling method based on improved deep reinforcement learning algorithms. First,based on the satellite imaging coverage calculation method,an imaging strip partitioning algorithm is proposed. Second,based on the visible time window,strip and satellite orbit information,a multiple satellites cooperative observation mission planning model based on the partially observable Markov decision process (POMDP)is established. Then,a proximal policy optimization algorithm with an action mask and advantage normalization mechanism is proposed,which improves the convergence rate of the algorithm for solving the partial strip coverage task area scheduling problem. Finally,the correctness and superiority of the proposed algorithm are verified by three sets of simulations.

In response to the singular phenomena that are prone to occur during attitude maneuvers of the application control moment gyroscope (CMG)satellites,an attitude dynamics equation is established with CMG speed commands as input. The established state space equation is discretized,and optimization calculation indicators are designed. Online optimization calculation of input speed commands is used to minimize torque errors caused by commonly used CMG control laws. A predictive control algorithm based on optimization iteration is designed to provide an attitude maneuver feedback controller with a closed-loop structure. In order to reduce the computa tional burden of online optimization and minimize the number of optimization calculations,a satellite attitude maneuver predictive controller with an event-triggered mechanism is designed,the controller can avoid CMG singularity and control satellite rapid maneuver,and effectively reduces the burden of in-orbit calculation on this basis. Through the simulation of the event-triggered attitude maneuver prediction controller for rigid body satellites,it is further demonstrated that this controller has the remarkable ability to significantly reduce the online computing burden.

In order to solve the problem that the telemetry data is easily affected by events and the optical image is easily affected by weather,this paper presents a method for judging the characteristic events of space launches by using external radar data. The method makes use of the feature events when the vernier ranging will have a large measurement error,through the vernier ranging increment difference structure judgment basis,and the detection of its extreme point to complete the judgment. The measured data of eight launches of four types of rockets are experimentally verified and compared with the telemetry data. The results show that the method can accurately detect characteristic events such as rocket stage separation and throwing fairing. The judgment time of stage separation is compared with the telemetry data,and the deviation is within 1s.

Star sensor is a high-precision attitude measurement device,and its attitude measurement accuracy plays a decisive role in navigation. In order to analyze the impact of star points'random errors on the accuracy of star sensors,based on the QUEST algorithm,an analytical model for the influence of star points'random errors on the star sensor accuracy is proposed by solving the Wahba problem. The relationship between the random centroid error of star points and the accuracy of star sensors is analyzed using this model. The simulation results show that the uniformity and average distance of star points relative to the detector origin affect the attitude accuracy of star sensors, rather than the field of view. The analytical model reveals the relationship between the star points' random error,the star points position and attitude accuracy. The three-axis attitude solution accuracy of the proposed model is (98.1%,93.3%,96.1%),while that of the empirical model is (58.8%,61.5%,26.9%). The accuracy analysis of star sensors has important guiding significance for the design,calibration,and astronomical navigation of star sensor optical systems.

Aiming at the application requirements of high attitude measurement accuracy of interferometric star tracker,the influence of grating diffraction efficiency on the measurement accuracy of starlight interferometry is analyzed. Based on the angular spectrum propagation theory,the im aging angle measurement model of the interferometric star tracker is constructed,and the energy distribution of the interference star point is simulated by numerical calculation. At the same time, the influence of the diffraction efficiency change caused by the change of the incident angle and the wavelength on the angle measurement accuracy of the starlight is analyzed respectively. The results show that the change of grating diffraction efficiency caused by the change of incident angle has little effect on the accuracy of starlight interferometry in the field of view of star sensor. The change of diffraction efficiency caused by wavelength change has a great influence on the accuracy of starlight interferometry. With the increase of spectral width,the accuracy of starlight interferometry decreases as a whole. When the starlight changes from monochromatic light to polychromatic light with spectral width of 300nm,the accuracy of starlight interferometry decreases from about 0.01″to about 0.3″.The analysis results of this paper can provide theoretical basis and technical support for the engineering application of interferometric star tracker.

The construction of navigation star list is an important task in the design stage of star sensor system. Because the interferometric star sensor only retains part of the interference order, the energy of the image point is low. The spectral component divides a beam of starlight into multiple image points,the energy of the image points is further weakened,and the pixel space occupied by the image points formed by multiple image points becomes larger,resulting in the inability to distinguish the adjacent star points that are too close. In order to establish the star list suitable for interferometric star sensor,by setting the threshold of angular distance,the list is screened for the first time,and dark stars,variable stars and binary stars with too close angular distance are excluded. In order to ensure the uniformity of the catalog,Fibonacci grid points are used as spher ical reference points,and the secondary screening of the catalog is carried out based on the reference points. The result shows that the number of stars is small and the uniformity is good,which can meet the demand of interferometric star sensor.

The main factors affecting the acquisition probability of midcourse and terminal guidance of compound-guided air-to-air missiles in the scene of multi-missile cooperative operation are analyzed. The target pointing angle errors and acquisition probability of cooperative search technology of air-to-air missiles are studied,and search strategies based on a cooperative search of two missiles are proposed. Through simulation analysis,an optimal searching strategy for the cooperative search of two missiles is formed to improve the acquisition probability of multiple missiles in the shortest possible time. At the same time,the cooperative detection technology can reduce the requirement of false alarm probability of a single missile,lessen the demand for detection signal-to-noise ratio,and improve the detection distance of the seeker,while keeping the total false alarm probability of multiple missile systems unchanged.

To address the problem of the accuracy of the binocular vision measurement system, this paper proposes and develops an error analysis model for convergent and parallel binocular vision systems. It analyzes the relationship between key camera structural parameters,including baseline,focal length,lens mounting structure,calibration accuracy,and the depth of the measured object and the resulting measurement errors. The study explores the impact of these factors on measurement accuracy and presents a simulation analysis. By considering the constraints of the field of view,the simulation results show that the error model established by the above analysis can effectively estimate the measurement error of the binocular vision system,and provide a theoretical model for the subsequent measurement error correction,and the suggestions for designing suitable structures and parameters for the construction of the required binocular vision system.

To meet the requirements of the space load platform's vibration depression,a novel modularized active-passive hybrid actuator is developed. First,a general structure with a passive hydraulic damping module,a voice coil motor module and a displacement measurement module in serial is proposed. Second,the influence of damping hole structure parameters on the damping coefficients and force transform of the damping module are analyzed. Then,the simulation is carried out using finite element analysis software to optimize the voice motor's structure parameters for enlarging the output force density and force stability. Finally,the output force is tested to verify the effectiveness of the design. The experimental results indicate that the actuator can achieve smooth force output throughout its full stroke,with an output density of 3.87×10^-4 N/mm³.