Tracking Maneuvering Research Articles

On Scientific Realism and Instrumentalism in Manoeuvring Target Modelling and Tracking

On Scientific Realism and Instrumentalism in Manoeuvring Target Modelling and Tracking The basic problem of tracking manoeuvring moving objects (e.g. aircrafts, ships) lies in unpredictability of object manoeuvres, with respect to the time of occurrence, duration and the type of trajectory. In this paper most representative methods of modelling and state estimation techniques applied to Manoeuvring Target Tracking (MTT) are briefly reviewed. Classification of existing approaches is made in the context of realistic and instrumentalistic paradigms of the philosophy of science. A practical example is also given that shows the impact of selecting models and estimation methods on the performance of the tracking filter for Air Traffic Control (ATC) radar.

Inertia-independent generalized dynamic inversion feedback control of spacecraft attitude maneuvers

The generalized dynamic inversion control methodology is applied to the spacecraft attitude trajectory tracking problem. It is shown that the structure of the skew symmetric cross product matrix alleviates the need to include the inertia matrix in the control law. Accordingly, the proposed control law depends solely on attitude and angular velocity measurements, and it neither requires knowledge of the spacecraft's inertia parameters nor it works towards estimating these parameters. A linear time-varying attitude deviation dynamics in the multiplicative error quaternion is inverted for the control variables using the generalized inversion-based Greville formula. The resulting control law is composed of auxiliary and particular parts acting on two orthogonally complement subspaces of the three dimensional Euclidean space. The particular part drives the attitude variables to their desired trajectories. The auxiliary part is affine in a free null-control vector, and is designed by utilizing a semidefinite control Lyapunov function that exploits the geometric structure of the control law to provide closed loop stability. The generalized inversion singularity avoidance is made by augmenting the generalized inverse with an asymptotically stable fast mode that is driven by angular velocity error's norm from reference angular velocity. Asymptotic tracking is achieved for detumbling maneuvers as the stable augmented mode subdues singularity. If the steady state desired quaternion trajectories are time varying, then asymptotic tracking is lost in favor of close ultimately bounded tracking because the stable augmented mode continues to be excited during steady state phase of response. A rest-to-rest slew and a trajectory tracking maneuver examples are provided to illustrate the methodology.

Inertia-Independent Generalized Dynamic Inversion Spacecraft Control

AbstractThe generalized dynamic inversion control methodology is applied to the spacecraft attitude trajectory tracking problem. It is shown that the structure of the skew symmetric cross product matrix alleviates the need to include the inertia matrix in the control law. Accordingly, the proposed control law depends solely on attitude and angular velocity measurements, and it neither requires knowledge of the spacecraft's inertia parameters nor it works towards estimating these parameters. A linear time varying attitude deviation dynamics in the multiplicative error quaternion is inverted for the control variables using the generalized inversion-based Greville formula. The resulting control law is composed of auxiliary and particular parts acting on two orthogonally complement subspaces of the three dimensional Euclidean space. The particular part drives the attitude variables to their desired trajectories. The auxiliary part is affine in a free null-control vector, and is designed by utilizing a semidefinite control Lyapunov function that exploits the geometric structure of the control law to provide closed loop stability. The generalized inversion singularity avoidance is made by augmenting the generalized inverse with an asymptotically stable fast mode that is driven by angular velocity error's norm from reference angular velocity. Asymptotic tracking is achieved for detumbling maneuvers as the stable augmented mode subdues singularity. If the steady state desired quaternion trajectories are time varying, then asymptotic tracking is lost in favor of close ultimately bounded tracking because the stable augmented mode continues to be excited during steady state phase of response. A rest-to-rest slew and a trajectory tracking maneuver examples are provided to illustrate the methodology.

H-INFINITY FILTER BASED PARTICLE FILTER FOR MANEUVERING TARGET TRACKING

In this paper, we propose a novel H-inflnity fllter based particle fllter (H1PF), which incorporates the H-inflnity fllter (H1F) algorithm into the particle fllter (PF). The basic idea of the H1PF is that new particles are sampled by the H1F algorithm. Since the H1F algorithm can fully take into account the current measurements, when the new algorithm calculates the proposed probability density distribution, the sampling particles can take advantage of the system current measurements to predict the system state. The particles distribution we obtained approaches nearer to the state posterior probability distribution and the H1PF alleviates the sample degeneracy problem which is common in the PF, especially when the maneuvers of the target tracking are large. Furthermore, the H1F algorithm can adjust gain imbalance factor by adjusting disturbance attenuation factor, from that the new algorithm can get the compromise between the accuracy and robustness and we can obtain satisfled accuracy and robustness. Some simulations and experimental results show that the proposed particle fllter performed better than the PF and the Kalman particle fllter (KPF) in tracking maneuvering target.

Controllable-structure Semi-ballistic Reentry Vehicle Tracking and Space-filling Model-set Design

Due to uncertainty in structure and uncertainty of flow field,the mode of the controllable-structure semiballistic reentry vehicle (SBRV) is usually unknown. Based on the analysis of the characteristics of the controllable-structure SBRV's motion and mode,the space-filling model set is proposed. The new model set is designed according to Hicknell's criterion. Compared with the model set generated by the Monte Carlo method,the new model set has a higher credibility and a smaller estimation error,and is more sensitive to maneuver. Theoretical analysis and simulation results show the reasonableness and efficiency of the space-filling model set for the maneuver tracking problem.

Roles of load-induced reorganization of multi-digit physiological tremors for a tracking maneuver

This study was undertaken to investigate the effect of low-level loading on digit tracking and the associated physiological tremors in the moving and the stationary digits. Sixteen healthy adults conducted positional tracking with the middle finger under the loaded and unloaded conditions; meanwhile, trajectory of the middle finger, electromyographic activities of the extensor digitorum (ED)/flexor digitorum superficialis, and physiological tremors of the index, middle, ring, and little fingers were recorded. The results showed that load imposition (<70 g) on the middle finger improved tracking congruency, in association with reduction of inter-digit tremor coupling and enhancement of tiny movement jerks. Principal component analysis suggested that inertial load suppressed the 8-12 Hz central rhythm but potentiated the 25-40 Hz coherence spectra of major principal components and electromyographic signals of the ED. It was concluded that low-level inertial load could facilitate corrective movement adjustments and selective digit control during manual tracking, relevant implicitly to decreased common central drive and enhanced heteronymous reflex loops.

Comparative controller design of an aerial robot

Flying capability opens novel opportunities in robotic applications, such as search and rescue, surveillance navigations and mapping operations. In this article, considering an aerial robot, i.e. an unmanned aerial vehicle (UAV), a few comparable controllers are designed to manage the system performance during various maneuvers. After introducing a nonlinear dynamics model of the system, an adaptive controller is proposed based on feedback linearization approach and using Lyapunov design method. Next, an optimal controller is designed to compare its performance with the designed adaptive controller. Stability analysis for the designed adaptation law is also studied and discussed. To evaluate the performance of designed controllers for a given aerial robot, a comprehensive simulation program is developed. It is shown that tracking errors for the state variables exponentially converge to zero, even in the presence of parameters uncertainty. In particular, it is shown that the proposed adaptive controller, based on its feedback linearization approach and Lyapunov stabilized characteristics, is able to perform perfect path tracking maneuvers, compared to the optimal controller that contains minor errors due to its feed-forward nature.

Maneuvering targets state prediction based on robust H ∞ filtering in opto-electronic tracking system

Due to the measurement time-delay, noises of the charge coupled device (CCD) tracker and maneuvering target model uncertainty characteristic in opto-electronic tracking system, the current statistical model is utilized to describe the unknown acceleration of the maneuvering target. H ∞ filter algorithm based on acceleration non-zero mean value time-correlation model is adopted for state prediction of opto-electronic tracking maneuvering targets. Some simulation and experimental results show that the prediction precision by the proposed method is nearly to be twice as much as Kalman filtering. It indicates that the H ∞ filter is effective in overcoming model change and stochastic measurement noise, and has high accuracy and good robustness.

Generalised dynamic inversion spacecraft control design methodologies

Generalised dynamic inversion control design methodologies for realisation of linear spacecraft attitude servo-constraint dynamics is introduced. A prescribed stable linear second-order time-invariant ordinary differential equation in a spacecraft attitude deviation norm measure is evaluated along solution trajectories of the spacecraft equations of motion, yielding a linear relation in the control variables. Generalised inversion of the relation results in a control law that consists of particular and auxiliary parts. The particular part works to drive the spacecraft attitude variables in order to nullify the attitude deviation norm measure, and the auxiliary part provides the necessary spacecraft internal stability by proper design of the involved null-control vector. Two constructions of the null-control vector are made, one by solving a state-dependent Lyapunov equation, yielding global spacecraft internal stability. The other is globally perturbed feedback linearising, but yields local stability of the spacecraft internal dynamics. The control designs utilise a damped generalised inverse to limit the growth of the controls coefficient Moore-Penrose generalised inverse as the steady-state response is approached. Both designs guarantee uniformly ultimately bounded attitude trajectory tracking errors. The null-control vector design freedom furnishes an advantage of the approach over classical inverse dynamics, because it can be used to reduce dynamic inversion control signal magnitude. The design methodologies are illustrated by two spacecraft slew and trajectory tracking manoeuvres.

Atypical task-invariant organization of multi-segment tremors in patients with Parkinson’s disease during manual tracking

The objective of the study was to investigate the interplay between involuntary tremulous activities and task performance under volitional control for patients with Parkinson’s disease (PD) during position tracking. A volunteer sample of nine untreated patients and nine age-matched healthy subjects participated in this study. They performed a sinusoidal tracking maneuver with a shoulder and a static pointing task; meanwhile, a position trace of the index and accelerometer data in the upper limb were recorded to characterize tracking performance and postural–kinetic tremors. In reference to postural tremor, the kinetic tremor of control subjects during tracking was considerably modulated, leading to a lower regularity and greater spectral deviation. In contrast, patients with PD demonstrated greater postural and kinetic tremors than control subjects, and tremulous movements of the patients were comparatively task-invariant. The prominent coherence peak, which occurred at 8–12 Hz in control subjects, was atypically presented at 5–8 Hz for PD patients with poorer tracking performance. Functionally, congruency of position tracking was related to amplitude of kinetic tremor after subtracting from amplitude of postural tremor. In conclusion, task-dependent organization of tremulous movements was impaired in patients with PD. The inferior tracking performance of the patients correlated implicitly with kinetic tremor, signifying some sharing of neural substrates for manual tracking and tremor generation.

Development of Flight Control Laws for the T-50 Advanced Supersonic Jet Trainer

The T-50 advanced supersonic jet trainer employs the Relaxed Static Stability (RSS) concept to improve the aerodynamic performance while the flight control system stabilizes the unstable aircraft and provides adequate handling qualities. The T-50 flight control laws employ a proportional-plus-integral type controller based on a dynamic inversion method in longitudinal axis and a proportional type controller based on a blended roll system with simple roll rate feedback and beta-betadot feedback system. These control laws are verified by flight tests with various maneuver set flight envelopes and the control laws are updated to resolve flight test issues. This paper describes several concepts of flight control laws used in T-50 to resolve those flight test issues. Control laws for solving the roll-off problem during pitch maneuver in asymmetric loading configurations, improving the departure resistance in negative angle of attack conditions and enhancing the fine tracking performance in air-to-air tracking maneuvers are described with flight test data.

An improved estimator using multiple sensor data fusion for radar maneuvering target tracking systems

An algorithm for tracking multiple maneuvering targets using multiple sensor data fusion is developed in this paper. In order to solve a complicated situation due to the multiple maneuvering tracking environment, a tracking filter and a multiple‐sensor data‐fusion algorithm are applied in this study. In addition, in order to solve the data association and target maneuvering situations, a computational logic, including 1‐step conditional maximum likelihood and a variable structure model as an adaptive maneuvering compensator, is applied to solve both data association and target maneuvering problems simultaneously. The advantage of this approach is that the sensors can be installed in either fixed or moving systems, thereby improving the tracking accuracy and the reliability of the radar surveillance. In order to verify this approach, simulations of multi‐target tracking problems are conducted. Computer simulation results indicate that this approach successfully tracks multiple targets and has good performance.

IMM fuzzy probabilistic data association algorithm for tracking maneuvering target

In this paper, a new interacting multiple model fuzzy probabilistic data association (IMM-FPDA) algorithm is proposed for tracking maneuvering target. In the proposed tracker, fuzzy logic is incorporated in a conventional IMM-PDA method. In order to determine process noise covariance of the Kalman filter used in IMM-PDA, the prediction error and change of the prediction error in the last prediction are used as fuzzy inputs. To optimize parameters of the fuzzy system, a tabu search algorithm is utilized. The IMM-FPDA tracker combines advantages of the FPDA and IMM algorithms. The performance of the proposed algorithm is compared with those of the IMM and PDA-IMM algorithms using two different maneuvering tracking scenarios. It is shown from simulation results that the IMM-FPDA algorithm greatly outperforms the IMM and IMM-PDA algorithms in terms of tracking error.

The reorganization of tremulous movements in the upper limb due to finger tracking maneuvers

In light of the interplay between limb oscillatory outputs and the outcome performance of movement effectors, this study was undertaken to investigate neuromotor control in the upper limb during position tracking and posture holding. Sixteen volunteers conducted a postural pointing task and two index tracking maneuvers at 0.3 and 0.6 Hz with an outstretched arm. Limb acceleration in the index finger, hand, forearm, arm, and C7 spinal process were monitored to correlate functionally with the accuracy of index rhythmic displacements. The results showed that index oscillatory activity multiplied with tracking speed, but hand oscillatory activity declined during tracking movement. The tracking maneuvers also altered spectral distribution of the tremulous activities in the context of a lower spectral peak in the range of 8-12 Hz and suppression of spectral peaks at 2-4 Hz, in reference to that already presented in posture tremor. Consisting of three local maxima around 2-4, 8-12, and 18-22 Hz, the coherence of tremulous activity between the finger and hand during position tracking was nearly identical, but inferior to high coherence below 12 Hz during posture holding. Functionally, better tracking performance was associated with a smaller tremulous activity in the finger and hand, entailing sophisticated release of mechanical couplings in the finger-hand and hand-forearm. In conclusion, inversely related to tracking performance, limb tremulous movements were task-dependently organized, and speed-invariant coherence of limb tremulous movement specified an inter-segmental coordination, which is physiological evidence of the generalized motor program for position tracking.

Tracking maneuvering target based on neural fuzzy network with incremental neural leaning

The scheme for tracking maneuvering target based on neural fuzzy network with incremental neural learning is proposed. When tracked target maneuver occurs, the scheme can detect maneuver immediately and estimate the maneuver value accurately, then the tracking filter can be compensated correctly and duly by the estimated maneuver value. When environment changes, neural fuzzy network with incremental neural learning (INL-SONFIN) can find its optimal structure and parameters automatically to adopt to changed environment. So, it always produce estimated output very close to the true maneuver value that leads to good tracking performance and avoids miss-tracking. Simulation results show that the performance is superior to the traditional schemes and the scheme can fit changed dynamic environment to track maneuvering target accurately and duly.

Novel Adaptive Generalized Likelihood Ratio Detector with Application to Maneuvering Target Tracking

A novel adaptive jump-detection algorithm is introduced for scenarios involving abrupt changes in the inputs to linear systems, such as those that might occur in tracking maneuvering targets. Improving upon the standard generalized likelihood ratio (GLR) detector, presented over two decades ago, the new algorithm is characterized by increased robustness with respect to uncertainties in the system input, which frequently arise in the context of target tracking applications. The performance of the new algorithm is demonstrated in an endgame scenario involving an interceptor missile and a maneuerable tactical ballistic missile. An extensive Monte Carlo simulation study is used to demonstrate the superiority of the method over the conventional GLR method in terms of its much smaller observed false alarm probability, which actually agrees with the theoretical value. The new algorithm also facilitates a correct isolation of the abrupt change, is consistent in the usual statistical sense, and generally proves more reliable.

ANALYSIS AND IMPLEMENTATION OF A NEURAL EXTENDED KALMAN FILTER FOR TARGET TRACKING

Having a better motion model in the state estimator is one way to improve target tracking performance. Since the motion model of the target is not known a priori, either robust modeling techniques or adaptive modeling techniques are required. The neural extended Kalman filter is a technique that learns unmodeled dynamics while performing state estimation in the feedback loop of a control system. This coupled system performs the standard estimation of the states of the plant while estimating a function to approximate the difference between the given state-coupling function model and the behavior of the true plant dynamics. At each sample step, this new model is added to the existing model to improve the state estimate. The neural extended Kalman filter has also been investigated as a target tracking estimation routine. Implementation issues for this adaptive modeling technique, including neural network training parameters, were investigated and an analysis was made of the quality of performance that the technique can have for tracking maneuvering targets.

T-50 정밀추적 성능 향상을 위한 세로축 제어법칙에 관한 연구

An advanced method of Relaxed Static Stability (RSS) is utilized for improving the aerodynamic performance of modern version supersonic jet fighter aircraft. The laws of flight control system utilize RSS criteria in both longitudinal and lateral-directional axes to achieve performance enhancements. Particularly, the design of longitudinal control laws for utilizing RSS methods greatly affects the performance of the aircraft in Air-to-Air Tracking and Air-to-Ground modes, which improves weapon delivery. In the area of Air-to-Air Tracking, the development of longitudinal control laws aids in the fine tracking and gross acquisition of other aircraft. This paper proposes that new concept of longitudinal control law introduce in order to improve fine tracking performance in air-to-air tracking maneuver. Result of HQS pilot simulation and flight test, fine tracking performance improve without degradation of gross acquisition when new concept of control law is applied.

Reduced state estimators for consistent tracking of maneuvering targets

Linear Kalman filters, using fewer states than required to completely specify target maneuvers, are commonly used to track maneuvering targets. Such reduced state Kalman filters have also been used as component filters of interacting multiple model (IMM) estimators. These reduced state Kalman filters rely on white plant noise to compensate for not knowing the maneuver - they are not necessarily optimal reduced state estimators nor are they necessarily consistent. To be consistent, the state estimation and innovation covariances must include the actual errors during a maneuver. Blair and Bar-Shalom have shown an example where a linear Kalman filter used as an inconsistent reduced state estimator paradoxically yields worse errors with multisensor tracking than with single sensor tracking. We provide examples showing multiple facets of Kalman filter and IMM inconsistency when tracking maneuvering targets with single and multiple sensors. An optimal reduced state estimator derived in previous work resolves the consistency issues of linear Kalman filters and IMM estimators.

Smooth Reference Model Adaptive Sliding-Mode Control for Attitude Synchronization with a Tumbling Satellite

Attitude synchronization is a key technology in the capture of tumbling satellites, and accurate estimation of the inertia ratio of tumbling satellites is an important function to synchronize the attitude of the chaser satellite with that of the tumbling satellite. This paper proposes a new control scheme, smooth reference model adaptive sliding mode control, or SRMASMC, for attitude tracking maneuvers. An adaptive law is introduced to accurately estimate the inertia ratio of the tumbling satellite, and a smooth reference model is employed to reduce the control torque at the beginning of the tracking maneuver. The attitude tracking performance of SRMASMC is evaluated numerically and compared with that of eigenaxis rotational maneuver control and sliding mode control. The results reveal that SRMASMC offers superior performance to these methods under the conditions examined.