Landing Guidance Research Articles

Model Predictive Convex Programming for Constrained Vehicle Guidance

A new model predictive convex programming is proposed in this paper for state and input constrained vehicle guidance design. The proposed method defines a convex optimization framework considering a flexibly designed cost function subject to inequality constraints and a sensitivity relation between state increments and input corrections. This formulated convex optimization problem can be solved in a computationally efficient manner. Simulation studies of nonlinear missile and aircraft landing guidance problems demonstrate the effectiveness of the proposed approach.

A software platform for vision-based UAV autonomous landing guidance based on markers estimation

The paper concentrated on descripting the methods of UAV autonomous landing on moving target. GPS navigation and vision-based navigation were employed during different stage of autonomous landing in the simulation environment and virtual reality. Uncertain markers estimation is the main step for UAV autonomous landing. It contains the convex hull transformation, interference preclusion, ellipse fitting and specific feature matching. Furthermore, the complete visual measurement program and guidance strategy were proposed in this paper. Considerable comprehensive experiments indicated the significance and feasibility of method of vision-based UAV autonomous landing on moving target.

Enhanced predictor–corrector Mars entry guidance approach with atmospheric uncertainties

Due to the long-range data communication and complex Mars environment, the Mars lander needs to promote the ability to autonomously adapt uncertain situations ensuring high precision landing in future Mars missions. Based on the analysis of multiple disturbances, this study demonstrates an enhanced predictor–corrector guidance method to deal with the effect of atmospheric uncertainties during the entry phase of the Mars landing. In the proposed method, the predictor–corrector guidance algorithm is designed to autonomously drive the Mars lander to the parachute deployment. Meanwhile, the disturbance observer is designed to onboard estimate the effect of fiercely varying atmospheric uncertainties resulting from rapidly height decreasing. Then, with the estimation of atmospheric uncertainties compensated in the feed-forward channel, the composite guidance method is put forward such that both anti-disturbance and autonomous performance of the Mars lander guidance system are improved. Convergence of the proposed composite method is analysed. Simulations for a Mars lander entry guidance system demonstrates that the proposed method outperforms the baseline method in consideration of the atmospheric uncertainties.

Optimal Rocket Landing Guidance Using Convex Optimization and Model Predictive Control

In this paper, a novel guidance algorithm based on convex optimization, pseudospectral discretization, and a model predictive control (MPC) framework is proposed to solve the highly nonlinear and constrained fuel-optimal rocket landing problem. The main strategy is to solve the guidance problem by implementing online trajectory optimization in a receding-horizon manner and feeding the rocket with the most recently updated optimal control commands. A pseudospectral-improved successive convexification (PISC) algorithm is adopted to solve the trajectory optimization problem due to its high solution accuracy and computation speed. The PISC algorithm is then embedded in the MPC framework to construct the guidance algorithm. The recursive feasibility of the MPC-based guidance algorithm is guaranteed by executing the original and relaxed trajectory optimization algorithms in parallel. Additionally, the boundedness of the guidance error is proved. Therefore, the guidance algorithm is optimal, robust, and practically stable under constraints and disturbances. Numerical experiments are provided to demonstrate the effectiveness of the proposed algorithm.

A visual/inertial integrated landing guidance method for UAV landing on the ship

This paper presents a visual/inertial integrated guidance method for UAV shipboard landing. The airborne vision system is utilized to track infrared cooperated targets on the ship and output their center coordinates in the image. Meanwhile, the attitude information of the UAV is obtained from airborne Inertial Measurement Unit (IMU). Extended Kalman Filter (EKF) is chosen to fuse the visual and inertial information. The UAV's position, attitude, and velocity relative to the runway and the ship motion information are estimated. The ship motion information is utilized to predict the position of the intended landing point at the touchdown moment through the Autoregressive algorithm. And the motion information of the UAV is used to calculate the deviation from the intended landing path. All the information is delivered to the flight control system to calculate control command. Simulation shows that the visual/inertial integrated landing guidance system achieves satisfied estimation and prediction results.

Navigation-Optimal-Guidance for Precision Planetary Landing by Convexification of Estimated-Error-Variance of Navigation

This paper presents a navigation optimal powered descent landing guidance for autonomous precision planetary landing. High precision navigation is required for precision landing and use of terrain relative navigation (TRN) is being studied. Since the navigation accuracy of the TRN depends on the landing trajectory, we propose the navigation optimal trajectory to improve landing accuracy. This paper defines the optimal control problem which minimizes the navigation error at landing by using the estimated error covariance of the Kalman filter of the navigation algorithm. By assumption and approximation, around reference trajectory, trace of covariance matrix is linearized with respect to the landing trajectory, and the trajectory is discrete linearized with respect to the dynamics and non-convex constraints. The problem is convexified by these discrete-linearizations and formulated to sub-problem of Second-order cone programming (SOCP). Therefore, this problem is solved by iterative convexification and convex-optimization. The effectiveness of the algorithm is confirmed by Monte Carlo simulation on Mars landing problem. In this simulation, the accuracy of TRN depends on the line of sight distance of the image sensor. The proposed guidance algorithm by using convex programming can potentially be implemented in spacecraft as onboard real-time applications.

Research on the visual/inertial integrated carrier landing guidance algorithm

In this article, we describe a visual/inertial integrated carrier landing guidance algorithm for aircraft carrier landing operations. The airborne vision system and the inertial navigation system a...

An approach and landing guidance design for reusable launch vehicle based on adaptive predictor–corrector technique

In this study, a novel predictor–corrector guidance law based on the all-coefficient adaptive control theory is proposed for the approach and landing phase of an unpowered reusable launch vehicle (RLV). The flight phase includes two portions: the initial gliding flight phase and the final exponential flare one. The equilibrium glide condition and an exponential function of altitude are used to parameterize the guidance commands of two portions and generate the guidance sequence. Based on the first order characteristic model which has the advantages of less characteristic parameters and easy analysis, the all-coefficient adaptive predictor–corrector guidance method is presented. The guidance law has the ability of generating new trajectories online according to the current states and the final conditions of the landing point. Then, the stability and finite-time convergence of the guidance law are analyzed. Considering the process constraints, the fusion guidance law is obtained. Finally, simulation results demonstrate the effectiveness and robustness of the proposed guidance law, with respect to the large initial states errors and parameter uncertainties. The simulations also show that the system under the proposed guidance law converges to a small neighborhood of zero after limited steps.

Remote Marker-Based Tracking for UAV Landing Using Visible-Light Camera Sensor.

Unmanned aerial vehicles (UAVs), which are commonly known as drones, have proved to be useful not only on the battlefields where manned flight is considered too risky or difficult, but also in everyday life purposes such as surveillance, monitoring, rescue, unmanned cargo, aerial video, and photography. More advanced drones make use of global positioning system (GPS) receivers during the navigation and control loop which allows for smart GPS features of drone navigation. However, there are problems if the drones operate in heterogeneous areas with no GPS signal, so it is important to perform research into the development of UAVs with autonomous navigation and landing guidance using computer vision. In this research, we determined how to safely land a drone in the absence of GPS signals using our remote maker-based tracking algorithm based on the visible light camera sensor. The proposed method uses a unique marker designed as a tracking target during landing procedures. Experimental results show that our method significantly outperforms state-of-the-art object trackers in terms of both accuracy and processing time, and we perform test on an embedded system in various environments.

Trajectory Optimization for Planetary Multi-Point Powered Landing

Next-generation powered landing guidance for planetary soft landing needs multi-point-guidance capabilities. A novel trajectory optimization framework for planetary multi-point powered landing is presented in this study. First, the powered landing trajectory optimization problem with three-dimensional dynamics model, boundary conditions, and path constraints is formulated. The finite-element collocation approach with collocation based on Radau points is chosen to transcribe the formulated trajectory optimization problem into a nonlinear programming problem solved by Interior Point OPTimizer (IPOPT). The proposed trajectory optimization framework utilizes optimal sensitivity based on IPOPT to select the fuel-optimal landing aim point from candidate landing aim points by one optimization computation. Then, the optimal trajectory to the best landing aim point can be efficiently obtained based on the good initial value guess provided by the sensitivity analysis. Numerical results show that the proposed algorithm effectively and efficiently addresses the planetary multi-point powered landing problem and has potential for onboard implementation.

Approach and landing guidance design for reusable launch vehicle using multiple sliding surfaces technique

An autonomous approach and landing (A&L) guidance law is presented in this paper for landing an unpowered reusable launch vehicle (RLV) at the designated runway touchdown. Considering the full nonlinear point-mass dynamics, a guidance scheme is developed in three-dimensional space. In order to guarantee a successful A&L movement, the multiple sliding surfaces guidance (MSSG) technique is applied to derive the closed-loop guidance law, which stems from higher order sliding mode control theory and has advantage in the finite time reaching property. The global stability of the proposed guidance approach is proved by the Lyapunov-based method. The designed guidance law can generate new trajectories on-line without any specific requirement on off-line analysis except for the information on the boundary conditions of the A&L phase and instantaneous states of the RLV. Therefore, the designed guidance law is flexible enough to target different touchdown points on the runway and is capable of dealing with large initial condition errors resulted from the previous flight phase. Finally, simulation results show the effectiveness of the proposed guidance law in different scenarios.

Aerial Target Tracking Algorithm Based on Faster R-CNN Combined with Frame Differencing

We propose a robust approach to detecting and tracking moving objects for a naval unmanned aircraft system (UAS) landing on an aircraft carrier. The frame difference algorithm follows a simple principle to achieve real-time tracking, whereas Faster Region-Convolutional Neural Network (R-CNN) performs highly precise detection and tracking characteristics. We thus combine Faster R-CNN with the frame difference method, which is demonstrated to exhibit robust and real-time detection and tracking performance. In our UAS landing experiments, two cameras placed on both sides of the runway are used to capture the moving UAS. When the UAS is captured, the joint algorithm uses frame difference to detect the moving target (UAS). As soon as the Faster R-CNN algorithm accurately detects the UAS, the detection priority is given to Faster R-CNN. In this manner, we also perform motion segmentation and object detection in the presence of changes in the environment, such as illumination variation or “walking persons”. By combining the 2 algorithms we can accurately detect and track objects with a tracking accuracy rate of up to 99% and a frame per second of up to 40 Hz. Thus, a solid foundation is laid for subsequent landing guidance.

Autonomous Landing of a Fixed Wing UAV with a Ground-based Visual Guidance System

Fixed wing UAV autonomous landing guidance system needs high precision, fast tracking speed. This paper designs and built a set of Ground-based visual guidance system, which first introduces the visual landing guidance system principle, composition, analysis of the mathematical model and error analysis of the system; The Adaboost algorithm is applied to the recognition of UAV, where UAV samples and non-UAV are chosen for training cascade classifie. After the recognition of UAV, the UAV tracking system based on vision is designed. Finally, the reliability, tracking speed and precision of the system are verified by field experiments. The experimental results show that the designed landing guidance system could meet the requirements of the precise autonomous landing of a fixed wing UAV.

Enabling technologies for Chinese Mars lander guidance system

Chinese first Mars exploration activity, orbiting landing and roaming collaborative mission, has been programmed and started. As a key technology, Mars lander guidance system is intended to serve atmospheric entry, descent and landing (EDL) phases. This paper is to report the formation process of enabling technology road map for Chinese Mars lander guidance system. First, two scenarios of the first-stage of the Chinese Mars exploration project are disclosed in detail. Second, mission challenges and engineering needs of EDL guidance, navigation, and control (GNC) are presented systematically for Chinese Mars exploration program. Third, some useful related technologies developed in China's current aerospace projects are pertinently summarized, especially on entry guidance, parachute descent, autonomous hazard avoidance and safe landing. Finally, an enabling technology road map of Chinese Mars lander guidance is given through technological inheriting and improving.

Integral sliding mode control based approach and landing guidance law with finite-time convergence

In this study, a novel finite-time sliding mode control law is proposed and its application to the approach and landing (A&L) guidance problem is detailed. The proposed control strategy is designed through a combination of integral sliding mode (ISM) concept and polynomial feedback control law. The advantages of this approach are that the robustness is ensured throughout the motion, the convergence time can be chosen in advance and the system states can be expressed in an analytical way. Through the A&L guidance problem, the potential of the developed approach is demonstrated. The guidance scheme can land the reusable launch vehicle at the designated touchdown point with a reasonable amount of vertical velocity. The associated law features in its closed-loop form and the on-line trajectory generation ability. The required information only includes the instantaneous flight conditions and the terminal constraints. Numerical simulations in different scenarios are provided to validate the effectiveness of the proposed method.

Guidance Summary and Assessment of the Chang’e-3 Powered Descent and Landing

On 14 December 2013, Chang’e-3 successfully touched down on the surface of the moon, setting off its roaming exploration activities. Before this significant step, years of design, development, and testing of the Chang’e-3 powered descent and landing guidance, navigation, and control system were conducted to prepare for the most challenging robotic spacecraft landing endeavor attempted on the moon to date. In this paper, the mission and system design of Chang’e-3 are first described. Then, the guidance algorithms of powered descent and soft landing are summarized and assessed in detail. The powered descent and landing guidance technologies developed for Chang’e-3, including autonomous hazard detection and avoidance, lay the critical foundation for future lunar pinpoint soft-landing missions.

Analytic Approach and Landing Guidance through a Novel Time-Varying Sliding Mode Control Method

AbstractIn this paper, a nonlinear guidance law is developed for the approach and landing (A&L) phase of a reusable launch vehicle (RLV). First, a novel time-varying sliding mode control (TVSMC) technique is introduced. The main feature of this technique is that it enables the system states to converge to zero at the desired finite time. Then, the developed technique is applied to the A&L guidance law design. The guidance law possesses the capability of generating trajectories online according to the current system states and the terminal constraints. Therefore, there is no need to design any reference trajectories in advance. In addition, the analytic solutions of the altitude and flight path angle can be obtained in advance by solving a first-order linear differential equation. These analytic solutions can also be used to estimate the boundary of the normal load factor of the RLV. The effectiveness of the proposed guidance strategy and the accuracy of the analytic solutions are demonstrated through nume...

基于日盲区紫外成像的无人机着陆引导技术研究

基于日盲区紫外成像的无人机着陆引导技术研究

Mars precision landing guidance based on model predictive control approach

A precision landing guidance design for the Mars powered descent phase is proposed based on model predictive control (MPC) approach. Dynamics model used for the formulation are convexificated and linearized to adopt the convex optimization technique, which has been suggested by researchers of Jet Propulsion Laboratory. To employ the receding horizon frame and reduce the number of control inputs, the convex optimization problem is augmented with Laguerre functions. To represent the minimum fuel consumption or minimum landing error precisely unlike the optimal control theory, new cost function is designed by combining them with weighting factors. Moreover, the stability of the proposed guidance design for the independent control inputs calculated from each time step is verified by using Lyapunov stability analysis. Finally, numerical simulations are conducted to examine the suggested guidance formulation and to compare the performance with an optimal solution.

Constrained Reachability and Controllability Sets for Planetary Precision Landing via Convex Optimization

This paper presents a convex optimizations-based method to compute the set of initial conditions from which a given landing accuracy to a target can be achieved (constrained controllability set) and the set of states that can be reached from a given set of initial states (constrained reachability set) for a planetary landing vehicle with all the relevant control and mission constraints. The proposed method is based on the lossless convexification of the powered-descent landing guidance problem and methods of convex optimization and computational geometry. These techniques are used to generate approximations that can be arbitrarily close to the actual reachability or controllability sets. The quantification of these sets allows evaluation of the feasibility of a prescribed landing accuracy for a given vehicle and an expected set of dispersions from the parachute descent phase of a planetary landing mission. Since these sets are generated systematically and quickly, a wide range of design options can be evaluated for different mission requirements. Consequently, the proposed method can enable lander vehicle design optimization as a reliable analysis tool for systematic design and system engineering.