Guidance Scenario Research Articles

On-line 3D motion estimation using low resolution MRI

Image processing such as deformable image registration finds its way into radiotherapy as a means to track non-rigid anatomy. With the advent of magnetic resonance imaging (MRI) guided radiotherapy, intrafraction anatomy snapshots become technically feasible.MRI provides the needed tissue signal for high-fidelity image registration. However, acquisitions, especially in 3D, take a considerable amount of time. Pushing towards real-time adaptive radiotherapy, MRI needs to be accelerated without degrading the quality of information.In this paper, we investigate the impact of image resolution on the quality of motion estimations. Potentially, spatially undersampled images yield comparable motion estimations. At the same time, their acquisition times would reduce greatly due to the sparser sampling. In order to substantiate this hypothesis, exemplary 4D datasets of the abdomen were downsampled gradually. Subsequently, spatiotemporal deformations are extracted consistently using the same motion estimation for each downsampled dataset. Errors between the original and the respectively downsampled version of the dataset are then evaluated.Compared to ground-truth, results show high similarity of deformations estimated from downsampled image data. Using a dataset with voxel size, deformation fields could be recovered well up to a downsampling factor of 2, i.e. . In a therapy guidance scenario MRI, imaging speed could accordingly increase approximately fourfold, with acceptable loss of estimated motion quality.

Investigation into Air Interception Guidance Algorithms for Autonomous Aerial Hard Docking of Dissimilar Platforms

Autonomous aerial hard docking is the process where an aircraft approaches and forms a rigid connection with another aircraft. After the docking process is complete, it is not necessary for the lift and propulsion system of the docked aircraft to be operating. Docking allows the larger aircraft to carry the small aircraft outside its airframe, thereby extending the range of endurance of the smaller aircraft. In this paper, we investigate specific scenario where docking occurs between a rotary wing aircraft and a fixed wing aircraft. To perform the above procedure, a guidance system on each platform has to ensure interception while satisfying the primary interception condition of velocity vector co-linearity at the moment of intercept of the two trajectories or flight paths. Pursuit guidance and proportional navigation were assessed as candidates for further development for the terminal docking phase. Since the platforms are in quasi-perfect knowledge of each other, the pursuer evader scenario is replaced by the pursuer-pursuer scenario. The novelty of this work lies in the formulation of terminal constraints, as well as the findings obtained. This paper concludes that contrary to the missile guidance scenario, pursuit based guidance laws provide superior baseline laws from which AAHD guidance and navigation laws can be developed.

A Novel Decoupled LOS Rate Estimator for Terminal Guidance

An novel decoupled estimation algorithm based on kalman filter is presented to solve the line-of-sight (LOS) rate estimation problem in terminal guidance of air-to-air combat. The measurements of target azimuth and elevation are obtained by missile-borne active radar seeker which use a monopulse doppler radar. As it cant be directly measured by this kind of radar, the LOS rate which is needed as the input of guidance law should be estimated from these angle measurements. The close-loop simulation of LOS rate estimation in typical terminal guidance scenario that an air-to-air missile seeks a military fighter validates the presented algorithm.

A Novel Decoupled LOS Rate Estimator for Terminal Guidance

An novel decoupled estimation algorithm based on kalman filter is presented to solve the line-of-sight (LOS) rate estimation problem in terminal guidance of air-to-air combat. The measurements of target azimuth and elevation are obtained by missile-borne active radar seeker which use a monopulse doppler radar. As it cant be directly measured by this kind of radar, the LOS rate which is needed as the input of guidance law should be estimated from these angle measurements. The close-loop simulation of LOS rate estimation in typical terminal guidance scenario that an air-to-air missile seeks a military fighter validates the presented algorithm.

Optimal guidance law in quantum mechanics

Following de Broglie’s idea of a pilot wave, this paper treats quantum mechanics as a problem of stochastic optimal guidance law design. The guidance scenario considered in the quantum world is that an electron is the flight vehicle to be guided and its accompanying pilot wave is the guidance law to be designed so as to guide the electron to a random target driven by the Wiener process, while minimizing a cost-to-go function. After solving the stochastic optimal guidance problem by differential dynamic programming, we point out that the optimal pilot wave guiding the particle’s motion is just the wavefunction Ψ(t,x), a solution to the Schrödinger equation; meanwhile, the closed-loop guidance system forms a complex state–space dynamics for Ψ(t,x), from which quantum operators emerge naturally. Quantum trajectories under the action of the optimal guidance law are solved and their statistical distribution is shown to coincide with the prediction of the probability density function Ψ∗Ψ.

Partial stabilization-based guidance

A novel nonlinear missile guidance law against maneuvering targets is designed based on the principles of partial stability. It is demonstrated that in a real approach which is adopted with actual situations, each state of the guidance system must have a special behavior and asymptotic stability or exponential stability of all states is not realistic. Thus, a new guidance law is developed based on the partial stability theorem in such a way that the behaviors of states in the closed-loop system are in conformity with a real guidance scenario that leads to collision. The performance of the proposed guidance law in terms of interception time and control effort is compared with the sliding mode guidance law by means of numerical simulations.

Optimal Image-Guidance Scenario With Cone-Beam Computed Tomography in Conventionally Fractionated Radiotherapy for Lung Tumors

To determine the residual setup errors of several image guidance scenarios, using cone-beam computed tomography (CBCT) in conventionally fractionated radiotherapy for lung tumors. Thirteen lung cancer patients were treated with conventionally fractionated radiotherapy, using daily image guidance with CBCT, resulting in 389 CBCT scans which were registered to the planning scan using automated soft-tissue registration. Using the resulting daily alignment data, 4 imaging frequency scenarios were analyzed: (A) no imaging; (B) weekly imaging with a 3-mm threshold; (C) first 5 fractions imaged, then weekly imaging with a patient-specific threshold; and (D) imaging every other day. The systematic setup error (Sigma) was reduced with increasing frequency of imaging from 3.4 mm for no imaging to 1.0 mm for imaging every other day. Random setup error (sigma), however, varied little regardless of the frequency of imaging: 2.9, 3.0, 3.4, and 3.2 mm for scenarios A, B, C, and D, respectively. The setup margins required to account for the residual error of each imaging scenario were 1 to 1.6 cm for scenario A, 4 to 6 mm for scenarios B and C, and 4 to 5 mm for scenario D. As the residual error of daily CBCT was not included in this analysis, these margins compare with a margin of zero for daily CBCT. Daily image guidance is ideal as the setup margin can be reduced by about 5 mm versus a nondaily imaging scenario. However, if daily image guidance is not possible, there is little benefit in imaging more often than once a week.

Hybrid neural adaptive control for bank-to-turn missiles

A novel hybrid neural adaptive bank-to-turn (BTT) lateral autopilot is described for a short-range command-to-line-of-sight (CLOS) surface-to-air missile. This employs a multiinput-multioutput Gaussian radial basis function (RBF) network in parallel with a constant parameter, independently regulated lateral autopilot, to adaptively compensate for roll-induced cross-coupling time-varying aerodynamic derivatives and control surface constraints, in order to achieve consistent tracking performance over the flight envelope. The hybrid neural autopilot is evaluated in three dimensional (six-degree of freedom) simulation studies against realistic pitch acceleration and roll rate profiles generated from a typical CLOS guidance scenario, and its performance compared with a carefully designed gain scheduled autopilot. The results are found to be encouraging and clearly demonstrate the potential advantages of the neurocontrol scheme.

A Hybrid Autopilot for BTT Steering Using RBF Neural Nets

A hybrid neural adaptive control scheme is proposed to alleviate the tracking problems associated with a BTT autopilot. This employs a Gaussian Radial Basis Function neural network in parallel with an independendy regulated, fixed-gain lateral autopilot to adaptively compensate for roll-induced cross-coupling, time-varying aerodynamic derivatives and control surface constraints to achieve consistent tracking performance over the flight envelope. The hybrid scheme is evaluated against realistic pitch acceleration and roll rate profiles generated from a typical guidance scenario and its performance compared with constant parameter and gain scheduled autopilots.