Relative Navigation Algorithm Research Articles

Multiple nodes transfer alignment for airborne missiles based on inertial sensor network

Transfer alignment is an important initialization method for airborne missiles because the alignment accuracy largely determines the performance of the missile. However, traditional alignment methods are limited by complicated and unknown flexure angle, and cannot meet the actual requirement when wing flexure deformation occurs. To address this problem, we propose a new method that uses the relative navigation parameters between the weapons and fighter to achieve transfer alignment. First, in the relative inertial navigation algorithm, the relative attitudes and positions are constantly computed in wing flexure deformation situations. Secondly, the alignment results of each weapon are processed using a data fusion algorithm to improve the overall performance. Finally, the feasibility and performance of the proposed method were evaluated under two typical types of deformation, and the simulation results demonstrated that the new transfer alignment method is practical and has high-precision.

Robust Relative Navigation by Integration of ICP and Adaptive Kalman Filter Using Laser Scanner and IMU

This paper presents a robust six-degree-of-freedom relative navigation by combining the iterative closet point (ICP) registration algorithm and a noise-adaptive Kalman filter in a closed-loop configuration together with measurements from a laser scanner and an inertial measurement unit (IMU). In this approach, the fine-alignment phase of the registration is integrated with the filter innovation step for estimation correction, while the filter estimate propagation provides the coarse alignment needed to find the corresponding points at the beginning of ICP iteration cycle. The convergence of the ICP point matching is monitored by a fault-detection logic, and the covariance associated with the ICP alignment error is estimated by a recursive algorithm. This ICP enhancement has proven to improve robustness and accuracy of the pose-tracking performance and to automatically recover correct alignment whenever the tracking is lost. The Kalman filter estimator is designed so as to identify the required parameters such as IMU biases and location of the spacecraft center of mass. The robustness and accuracy of the relative navigation algorithm is demonstrated through a hardware-in-the loop simulation setting, in which actual vision data for the relative navigation are generated by a laser range finder scanning a spacecraft mockup attached to a robotic motion simulator.

Angles-only relative navigation and closed-loop guidance for spacecraft proximity operations

This research investigates angles-only relative navigation and closed-loop guidance algorithm for spacecraft mid-range orbital proximity operations when the orbital maneuver allows for range observability. Emphasis and contribution are on developing angles-only relative navigation and guidance coupling algorithm in the context of Clohessy–Wiltshire and Tschauner–Hempel dynamics. Observability analysis of the relative state is done and the general mathematical expression of the observable condition is obtained. Coupling relationship between the angles-only relative navigation and the multi-pulse sliding guidance is discussed and its analytic expression is derived. A novel closed-loop guidance scheme is designed based on the coupling relationship and unscented kalman filter. Two-body Monte Carlo simulations are conducted to evaluate the validity and test the performance of the closed-loop system. The sensitivities of the navigation and guidance accuracy to the line-of-sight angles accuracy, initial separation and initial state uncertainties, number of pulses, and dynamics are presented and discussed.

Laser-based Relative Navigation Using GPS Measurements for Spacecraft Formation Flying

This study presents a precise relative navigation algorithm using both laser and Global Positioning System (GPS) measurements in real time. The measurement model of the navigation algorithm between two spacecraft is comprised of relative distances measured by laser instruments and single differences of GPS pseudo-range measurements in spherical coordinates. Based on the measurement model, the Extended Kalman Filter (EKF) is applied to smooth the pseudo-range measurements and to obtain the relative navigation solution. While the navigation algorithm using only laser measurements might become inaccurate because of the limited accuracy of spacecraft attitude estimation when the distance between spacecraft is rather large, the proposed approach is able to provide an accurate solution even in such cases by employing the smoothed GPS pseudo-range measurements. Numerical simulations demonstrate that the errors of the proposed algorithm are reduced by more than about 12% compared to those of an algorithm using only laser measurements, as the accuracy of angular measurements is greater than 0.001° at relative distances greater than 30 km.

A novel decentralized relative navigation algorithm for spacecraft formation flying

This paper presents a novel decentralized relative navigation algorithm. The relative motion equations are derived in the Earth-Centered-Inertial frame. The relative measurements contain not only the line of sight and range between the deputy and the chief, but also the ranges among different deputies. This helps to improve the redundancy and accuracy of the relative navigation for spacecraft formation flying. In decentralized estimation algorithm, it is necessary to transmit the global states in the formation to linearize the ranges among the deputies. A sigma-point method is used to account for the uncertainty in the estimated states of other spacecraft. The relative measurements are coupled with the relative motion equation in a novel decentralized filter to determine the relative position and velocity. Simulation shows that the proposed novel decentralized estimation algorithm provides better performance than the traditional iteration algorithm.

Relative navigation for autonomous formation flying satellites using the state-dependent Riccati equation filter

A relative navigation method for autonomous formation flying using the state-dependent Riccati equation filter (SDREF) is presented. In the SDREF, nonlinear relative dynamics, including J2 perturbation, are parameterized into a state-dependent coefficient (SDC) form without any loss of nonlinearity. The relative navigation algorithm is established based on the carrier-phase differential GPS (CDGPS) and single-frequency GPS data, in which the SDREF is used as a nonlinear estimator. To evaluate the SDREF performance, two different extended Kalman filters (EKFR1 and EKFR2) are introduced. The dynamic models of all the filters are based on relative motion including J2 perturbation. However, the SDREF and the EKFR1 use linear state propagation, whereas EKFR2 employs nonlinear state propagation. The navigation simulation is performed for each filter using live GPS signals simulated by a GPS signal generator, and the result is analyzed in terms of estimation accuracy and computational load. As a result, the SDREF provides a relative navigation solution with 3-D RMS accuracies of 6.0mm and 0.153mm/s for position and velocity, respectively, for a separation of 50km with a computation time of approximately 34s. The simulation results demonstrate that the SDREF estimates the relative states as rapidly as the EKFR1 and as accurately as the EKFR2, which means that the developed SDREF combines the strong points of EKFR1 and EKFR2 and overcomes their disadvantages.

月球软着陆自主障碍识别与避障制导方法

An autonomous hazard detection and roughne hazard-avoidance guidance method for soft lunar landing is presented to mitigate the landing risks due to the uncertainty and hazards of the lunar terrain, such as surface roughness and slope. The method is composed of roughne hazard detection and a landing site selection algorithm. The high-precision relative autonomous navigation algorithm is based on image data, and the autonomous hazard-avoidance guidance algorithm is based on an adjusted thrust engine. The theoretic deduction and simulation analysis shows that a safe landing site is acquired and autonomous pinpoint hazard avoidance is achieved using the presented method. The method can be used to improve the achievement of a soft landing and has been successfully used in the Change-3 soft landing mission.

An algorithm and observability research of autonomous navigation and joint attitude determination in asteroid exploration descent stage

In this paper, an autonomous relative navigation and joint attitude determination algorithm in asteroid exploration descent stage is researched based on feature point information of perpendicular asteroid surface image observed by optical navigation camera, distance vectors from spacecraft to asteroid measured by three angled installed lidars and relative velocity increment measured by accelerometer when the relative distance vector to the centroid of asteroid can not be obtained. The inertial attitude of spacecraft is determined by sun vector, star vectors and inertial angular velocity respectively measured by sun sensor, star trackers and inertial reference unit. Also, in order to obtain measurement error model transferred from sensor noise, a covariance matrix solver considering error correlation is presented via the error model of normalized vector to first order. Numerical simulation and improved observability evaluation of filtering are undertaken to discuss the results of complete sensor observation and weak observation of lidars, and verify the effectiveness of the presented relative navigation and attitude determination algorithm.

Stereo Vision-Based Relative Navigation Algorithm for Satellites Formation Flying

Space mission with multiple spacecraft formation is an important means to space operation. A new relative navigation algorithm based on stereo vision is developed aiming at high navigation precision requirement of spacecraft formation flying. It uses stereo vision camera attached on the tracking craft as measurement sensor, gets the relative location of target craft in the tracking craft body reference frame with imaging parallax. Relative motion equation is built in inertial frame, and discretized as the state equation of the system. Measurement information of stereo vision is used as measurement value, and the two-step filter relative navigation algorithm based on Kalman filter is designed to estimate relative navigation state in real time, and finally validated by simulation. The simulation results prove this algorithm can meet the relative navigation precision requirements of formation flying.

Integrated orbit and attitude hardware-in-the-loop simulations for autonomous satellite formation flying

Development and experiment of an integrated orbit and attitude hardware-in-the-loop (HIL) simulator for autonomous satellite formation flying are presented. The integrated simulator system consists of an orbit HIL simulator for orbit determination and control, and an attitude HIL simulator for attitude determination and control. The integrated simulator involves four processes (orbit determination, orbit control, attitude determination, and attitude control), which interact with each other in the same way as actual flight processes do. Orbit determination is conducted by a relative navigation algorithm using double-difference GPS measurements based on the extended Kalman filter (EKF). Orbit control is performed by a state-dependent Riccati equation (SDRE) technique that is utilized as a nonlinear controller for the formation control problem. Attitude is determined from an attitude heading reference system (AHRS) sensor, and a proportional-derivative (PD) feedback controller is used to control the attitude HIL simulator using three momentum wheel assemblies. Integrated orbit and attitude simulations are performed for a formation reconfiguration scenario. By performing the four processes adequately, the desired formation reconfiguration from a baseline of 500–1000m was achieved with meter-level position error and millimeter-level relative position navigation. This HIL simulation demonstrates the performance of the integrated HIL simulator and the feasibility of the applied algorithms in a real-time environment. Furthermore, the integrated HIL simulator system developed in the current study can be used as a ground-based testing environment to reproduce possible actual satellite formation operations.

Guidance, Navigation and Control for Satellite Proximity Operations using Tschauner-Hempel Equations

In this paper, the development of relative navigation, guidance, and control algorithms of an autonomous space rendezvous and docking system are presented. These algorithms are based on using the analytical closed-form solution of the Tschauner-Hempel equations that is completely explicit in time. The navigation system uses an extended Kalman filter based on Tschauner-Hempel equations to estimate the relative position and velocity of the chaser vehicle with respect to the target vehicle and the chaser attitude and gyros biases. This filter uses the range and angle measurements of the target relative to the chaser from a simulated LIDAR system along with the star tracker and gyro measurements of the chaser. The corresponding measurement models, process noise matrix and other filter parameters are provided. The guidance and control algorithms are based on the glideslope used in the past for rendezvous and proximity operations of the Space Shuttle with other vehicles. These algorithms are used to approach, flyaround, and to depart form a target vehicle in elliptic orbits. The algorithms are general and able to translate the chaser vehicle in any direction, decelerate while approaching the target vehicle, and accelerate when moving away. Numerical nonlinear simulations that illustrate the relative navigation, attitude estimation, guidance, and control algorithms performance and accuracy are evaluated in the current paper. The analyses include the navigations errors, trajectory dispersions and attitude dispersions.

Research on relative position and attitude representation and algorithm of formation flying systems based on position and attitude dual quaternion model

To combine the attitude into spacecraft’s orbit representation in formation flying systems, this article addresses a novel position and attitude dual quaternion model to simultaneously describe the relative position and attitude. Besides, the Quasi-global positioning system measurement model is used to realize the relative autonomous navigation. Finally, numerical simulations indicate that both models and the relative autonomous navigation algorithm meet the demand of formation flying systems. The results show that models are reasonable and concise and that the algorithm is more efficient.

Vision navigation algorithm for mine agent based on quaternion

Autonomous relative navigation is the key technology in mining or rescuing. On the basis of mine requirement and the theories of machine vision, an autonomous relative navigation algorithm for mine agent based on quaternion was proposed. In rotation transformation, this algorithm was represented by using quaternion. Because the Jacobi matrix of this method is lower than that of Hall algorithm, the calculation efficiency is improved by using this algorithm. The results of these experiments show that the computation burden of this algorithm based on quaternion is about half that of Hall algorithm. This algorithm based on quaternion is improved as a valid way to solve the problem of mine real-time navigation.

月球软着陆避障段定点着陆导航方法研究

Hazard avoidance phase is one of the most important flight phases in lunar descent and safe landing. In this phase, the navigation system must take the capability of detecting hazards, designating a safe site and guiding the lander to the selected safe site, besides the normal ability of providing the information about position, velocity and attitude. The basic navigation instrument in hazard avoidance phase is Inertial Navigation System (INS). In order to eliminate the accumulated calculation errors in INS, the measurements from other sensors are always introduced, such as optical cameras and altimeters. In this paper, a relative navigation method for safe landing based on optical images is proposed. First, a safe landing site and a series image features are selected using image processing techniques, and then a kind of accurate relative navigation algorithm is performed by matching and tracking those selected image features. The simulation results imply that this method is effective to reduce the INS errors and can be used for hazard avoidance and pinpoint landing on the moon.

Hardware-in-the-loop simulations of GPS-based navigation and control for satellite formation flying

A relative navigation and formation control algorithm for satellite formation flying was developed, and a hardware-in-the-loop (HIL) simulation testbed was established and configured to evaluate this algorithm. The algorithm presented is a relative navigation estimation algorithm using double-difference carrier-phase and single-difference code measurements based on the extended Kalman filter (EKF). In addition, a state-dependent Riccati equation (SDRE) technique is utilized as a nonlinear controller for the formation control problem. The state-dependent coefficient (SDC) form is formulated to include nonlinearities in the relative dynamics. To evaluate the relative navigation and control algorithms developed, a closed-loop HIL testbed is configured. To demonstrate the performance of the testbed, a test formation flying scenario comprising formation acquisition and keeping in a low earth orbit (LEO) has been established. The relative navigation results from the closed-loop simulations show that a 3D RMS of 0.07 m can be achieved for position accuracy. The targeted leader–follower formation flying in the along-track separation of 100 m was maintained with a mean position error of approximately 0.2 m and a standard deviation of 0.9 m. The simulation results show that the HIL testbed is capable of successful demonstration of the GPS-based satellite autonomous formation flying mission.

Simulation Infrastructure for Autonomous Vision-Based Navigation Technologies

AbstractVision-based navigation technologies are currently under development in order to support future planetary exploration missions to the Moon, Mars and small bodies. By tracking landmarks and local features on the surface of celestial bodies, these technologies will provide GPS-like spacecraft localization capabilities and enable precision orbiting and/or landing toward known targets of interest. In order to contribute to the development roadmap of these technologies, this paper will present the Simulation Infrastructure for Autonomous Navigation technologies (SIAN) aiming at simulating with hardware-in-the-loop and high repeatability vision-based terrain relative navigation algorithms. This scaled simulation infrastructure aims at bridging the gap between pure software simulations and expensive helicopter or rocket-based flight tests. This paper will present the main objectives of this innovative and unique simulation infrastructure and report its conceptual and detailed design.

Trajectory Tracking Controller for Vision-Based Probe and Drogue Autonomous Aerial Refueling

This paper addresses autonomous aerial refueling between an unmanned tanker aircraft and an unmanned receiver aircraft using the probe-and-drogue method. An important consideration is the ability to achieve successful docking in the presence of exogenous inputs such as atmospheric turbulence. Practical probe and drogue autonomous aerial refueling requires a reliable sensor capable of providing accurate relative position measurements of su‐cient bandwidth, integrated with a robust relative navigation and control algorithm. This paper develops a Reference Observer Based Tracking Controller that does not require a model of the drogue or presumed knowledge of its position, and integrates it with an existing vision based relative navigation sensor. A trajectory generation module is used to translate the relative drogue position measured by the sensor into a smooth reference trajectory, and an output injection observer is used to estimate the states to be tracked by the receiver aircraft. Accurate tracking is provided by a state feedback controller with good disturbance rejection properties. A frequency domain stability analysis for the combined reference observer and controller shows that the system is robust to sensor noise, atmospheric turbulence, and high frequency unmodeled dynamics. Feasibility and performance of the total system is demonstrated by simulated docking maneuvers of an unmanned receiver aircraft docking with the non-stationary drogue of an unmanned tanker, in the presence of atmospheric turbulence. Performance characteristics of the vision based relative navigation sensor are also investigated, and the total system is compared to an earlier version. Results presented in the paper indicate that the integrated sensor and controller enable precise aerial refueling, including consideration of realistic measurements errors, plant modeling errors, and disturbances.

Principles, System Configuration and Algorithm Design of the Inertially Aided JTIDS Relative Navigation Function

The principles of operation of the Relative Navigation (RELNAV) function of the Joint Tactical Information Distribution System (JTIDS), which are based on its highly accurate time-of-arrival measurement capability and on a specially structured architecture, are described. The system configuration for implementing the RELNAV function in the JTIDS Hughes Improved Terminal (HIT) is presented. The integration options for interfacing the LN-31 Inertial Navigation Set with the HIT are discussed, and the selected interface is described. The RELNAV operational modes, control requirements and major software functions are discussed. A detailed description is given of the selected RELNAV algorithm and the associated timing and sequencing design. The filter state vector extrapolation and update formulation, the inertial processing and the source selection algorithms are presented. Some simulation results are presented.