Wing kinematics measurement and aerodynamics of free-flight maneuvers in drone-flies

The time courses of wing and body kinematics of two free-flying drone-flies, as they performed saccades, were measured using 3D high-speed video, and the morpho- logical parameters of the wings and body of the insects were also measured. The measured wing kinematics was used in a Navier-Stokes solver to compute the aerodynamic forces and moments acting on the insects. The main results are as following. （1） The turn is mainly a 90° change of heading. It is made in about 10 wingbeats （about 55 ms）. It is of interest to note that the number of wingbeats taken to make the turn is approximately the same as and the turning time is only a little different from that of fruitflies measured recently by the same approach, even if the weight of the droneflies is more than 100 times larger than that of the fruitflies. The long axis of body is about 40° from the horizontal during the maneuver. （2） Although the body rotation is mainly about a vertical axis, a relatively large moment around the yaw axis （axis perpendicular to the long axis of body）, called as yaw moment, is mainly needed for the turn, because moment of inertial of the body about the yaw axis is much larger than that about the long axis. （3） The yaw moment is mainly pro- duced by changes in wing angles of attack： in a right turn, for example, the dronefly lets its right wing to have a rather large angle of attack in the downstroke （generally larger than 50°） and a small one in the upstroke to start the turn, and lets its left wing to do so to stop the turn, unlike the fruitflies who generate the yaw moment mainly by changes in the stroke plane and stroke amplitude.

Recruitment maneuvers in acute respiratory distress syndrome: The safe way is the best way

Acute respiratory distress syndrome(ARDS) represents a serious problem in critically ill patients and is associated with in-hospital mortality rates of 33%-52%. Recruitment maneuvers(RMs) are a simple, low-cost, feasible intervention that can be performed at the bedside in patients with ARDS. RMs are characterized by the application of airway pressure to increase transpulmonary pressure transiently. Once non-aerated lung units are reopened, improvements are observed in respiratory system mechanics, alveolar reaeration on computed tomography, and improvements in gas exchange(functional recruitment). However, the reopening process could lead to vascular compression, which can be associated with overinflation, and gas exchange may not improve as expected(anatomical recruitment). The purpose of this review was to discuss the effects of different RM strategies- sustained inflation, intermittent sighs, and stepwise increases of positive end-expiratory pressure(PEEP) and/or airway inspiratory pressure- on the following parameters: hemodynamics, oxygenation, barotrauma episodes, and lung recruitability through physiological variables and imaging techniques. RMs and PEEP titration are interdependent events for the success of ventilatory management. PEEP should be adjusted on the basis of respiratory system mechanics and oxygenation. Recent systematic reviews and meta-analyses suggest that RMs are associated with lower mortality in patients with ARDS. However, the optimal RM method(i.e., that providing the best balance of benefit and harm) and the effects of RMs on clinical outcome are still under discussion, and further evidence is needed.

Respiratory Volume Monitoring to Assess the Effect of Airway Maneuvers on Ventilation during Upper Endoscopy

Introduction: Propofol use during endoscopic procedures has become increasingly popular and assessing and maintaining airway patency is a significant challenge. Anesthesiologists often use airway maneuvers to maintain airway patency and ventilation during procedural sedation. A novel, non-invasive, Respiratory Volume Monitor (RVM) that provided continuous, real-time measurements of minute ventilation (MV), tidal volume (TV) and respiratory rate (RR) was used to monitor respiratory performance before, during, and after endoscopic procedures, quantify MV changes before and after airway maneuvers, and to quantify propofol-induced respiratory depression. Methods: RVM traces were obtained from 25 patients undergoing sedation for endoscopic procedures. Airway maneuvers were performed in 19/25 patients. All 25 patients received propofol as the primary sedative. Results: Forty-five airway maneuvers were performed. During these maneuvers, all respiratory parameters increased relative to pre-maneuver levels. On average, MV increased by 24% ± 5% (mean ± SEM), TV 14% ± 5% and RR: 17% ± 6%. The cohort average MVBASELINE was 9.5 ± 0.7 L/min (TV = 670 ± 60 ml, RR = 15 ± 0.7). Following propofol MV decreased transiently, reaching nadir five minutes after the last dose of propofol at 82% ± 10% of baseline (MV = 7.5 ± 1.0 L/min). The reduction in MV was driven by reduction in TV, not RR. Conclusions: Data demonstrated that RVM was able to track changes in ventilation and was able to quantify respiratory changes following airway maneuvers. All patients had a significant reduction in ventilatory volumes after propofol. Five minutes after the last dose of propofol, MV and TV were significantly reduced while RR was not, suggesting that monitoring respiratory rate alone was not a sufficient indicator of respiratory status.

Optimal design of left-lane line extensions considering non-yielding maneuvers at the beginning of the permitted phase

In order to restrict non-yielding maneuvers of left-turning vehicles,an optimal design of left-lane line extensions is proposed to solve the problem.A field observation was conducted to collect a data set of left-turning vehicles at the beginning of a green phase at two similar intersections(one with a permitted phase and the other with a protected phase).The comparative analysis shows no significant difference in the speed distribution using either a permitted phase or a protected phase,but it reveals that a permitted phase can lead to a larger acceleration when the left-turn vehicles pass through the conflict points.Those indicate the existence of non-yielding maneuvers of left-turn vehicles at signalized intersections with a permitted phase.Optimal designed left-lane line extensions contain two types of segments,circular curves and transition curves,and they are only related to four geometry parameters of an intersection.The proposed method is easy to use and it can offer reference for intersection channelization and traffic organization.

A METHOD FOR CALCULATING KINEMATIC PARAMETERS OF HELICOPTER IN LOOP AND ROLL MANEUVERS

A set of generallied equations which govern the klnematic parameters of helicopters in maneuvering flight is given. Loop and roll maneuvers are specially analysed in detail and the sample calculations are presented. The method established in this paper is of practical significance for aerobatic employment and design of armed helicopters.

A two-step method to detect broadcast ephemeris unavailable periods caused by BeiDou satellite orbital maneuvers

The space constellation of the BeiDou navigation satellite system(BDS) is a hybrid constellation containing medium earth orbit(MEO) satellites, geostationary earth orbit(GEO) satellites, and inclined geosynchronous orbit(IGSO) satellites. Due to the geosynchronous characteristics of GEO and IGSO, GEO satellites and IGSO satellites often need to perform orbital maneuvers, which can affect the signal-inspace(SIS) availability performance of BeiDou satellites. A two-step detection method for BeiDou satellite orbital maneuvers has been proposed in this paper. The first step is to identify orbital maneuvers based on time series analysis of broadcast ephemeris, and the second step is to verify orbital maneuvers based on bidirectional orbit prediction. The two-step detection method was used to detect the orbital maneuvers of BeiDou satellites in 2019. Through the double guarantees of identification and verification,the detection accuracy of BeiDou satellite orbital maneuvers has been effectively improved. And the orbital maneuver detection results are continued to be used to assess the SIS availability of BeiDou satellites. The results show that the availability loss of GEO satellite orbital maneuvers is about 0.45%-1.07%, and the availability loss of IGSO satellite orbital maneuvers is about 0.12%-0.19%.

Human Body Behavior as Response on Autonomous Maneuvers, Based on ATD and Human Model

In the near future, active safety systems will take more control over the vehicle driving, even up to introducing fully autonomous vehicles. Nowadays, it is expected that the active safety systems will aid avoiding collisions much more efficiently than human drivers. These systems can protect not only the passengers, but also other road users. To mitigate collision, certain maneuvers （e.g., sudden braking, lane change, etc.） need to be done in a reasonably quick time. However, this may lead to low-g energy pulses. The latter fact, may cause unexpected and, in some cases, unwanted occupant body motion resulting even in OOP （out of position） postures. New patterns of occupant reactions in such cases are, to some extent, confirmed experimentally [1-3]. This paper evaluates the limits of standard ATDs （anthropometric test devices） and chosen human models in well established maneuver scenarios. Obtained results are compared with experimental data available in the literature. Drawbacks identify new challenges for the near future simulation based safety engineering. One scenario with combined conditions of emergency braking during lane change has been used as an example of OOP posture after maneuver.

Multi-UAV cooperative maneuver decision-making for pursuitevasion using improved MADRL

Aiming at the problem of multi-UAV pursuit-evasion confrontation, a UAV cooperative maneuver method based on an improved multi-agent deep reinforcement learning(MADRL) is proposed. In this method, an improved Comm Net network based on a communication mechanism is introduced into a deep reinforcement learning algorithm to solve the multi-agent problem. A layer of gated recurrent unit(GRU) is added to the actor-network structure to remember historical environmental states. Subsequently,another GRU is designed as a communication channel in the Comm Net core network layer to refine communication information between UAVs. Finally, the simulation results of the algorithm in two sets of scenarios are given, and the results show that the method has good effectiveness and applicability.

Cooperative guidance law based on super-twisting observer for target maneuvering

To solve the problem that multiple missiles should simultaneously attack unmeasurable maneuvering targets,a guidance law with temporal consistency constraint based on the super-twisting observer is proposed.Firstly,the relative motion equations between multiple missiles and targets are established,and the topological model among multiple agents is considered.Secondly,based on the temporal consistency constraint,a cooperative guidance law for simultaneous arrival with finite-time convergence is derived.Finally,the unknown target maneuver-ing is regarded as bounded interference.Based on the second-order sliding mode theory,a super-twisting sliding mode observer is devised to observe and track the bounded interfer-ence,and the stability of the observer is proved.Compared with the existing research,this approach only needs to obtain the sliding mode variable which simplifies the design process.The simulation results show that the designed cooperative guidance law for maneuvering targets achieves the expected effect.It ensures successful cooperative attacks,even when confronted with strong maneuvering targets.

An air combat maneuver pattern extraction based on time series segmentation and clustering analysis

Target maneuver recognition is a prerequisite for air combat situation awareness,trajectory prediction,threat assessment and maneuver decision.To get rid of the dependence of the current target maneuver recognition method on empirical criteria and sample data,and automatically and adaptively complete the task of extracting the target maneuver pattern,in this paper,an air combat maneuver pattern extraction based on time series segmentation and clustering analysis is proposed by combining autoencoder,G-G clustering algorithm and the selective ensemble clustering analysis algorithm.Firstly,the autoencoder is used to extract key features of maneuvering trajectory to remove the impacts of redundant variables and reduce the data dimension;Then,taking the time information into account,the segmentation of Maneuver characteristic time series is realized with the improved FSTS-AEGG algorithm,and a large number of maneuver primitives are extracted;Finally,the maneuver primitives are grouped into some categories by using the selective ensemble multiple time series clustering algorithm,which can prove that each class represents a maneuver action.The maneuver pattern extraction method is applied to small scale air combat trajectory and can recognize and correctly partition at least 71.3%of maneuver actions,indicating that the method is effective and satisfies the requirements for engineering accuracy.In addition,this method can provide data support for various target maneuvering recognition methods proposed in the literature,greatly reduce the workload and improve the recognition accuracy.

What Does a First Order Model Tell Us about PEEP Wave Maneuvers?

Patients with acute respiratory distress syndrome (ARDS) are currently treated with a lung protective ventilation strategy and the application of positive end-expiratory pressure (PEEP), sometimes in combination with recruitment maneuvers. In this study, the respiratory system elastance and airway resistance of each breath before, during and after a specific recruitment maneuver (PEEP wave maneuver) were analyzed in two patient groups, ARDS and control group. A reduction of elastance after the maneuver was observed in ARDS patients. In addition, only healthy lungs exhibited a reduction of the elastance during the course of the maneuver, while the lungs of ARDS patients didn’t show that reduction of elastance. The capability of PEEP wave maneuvers to improve lung ventilation was shown and the dynamic behavior of the elastance after the maneuver was illustrated. Healthy lungs adapt faster to changes in mechanical ventilation than the lungs of ARDS patients.

UAV maneuvering decision-making algorithm based on deep reinforcement learning under the guidance of expert experience

Autonomous umanned aerial vehicle(UAV) manipulation is necessary for the defense department to execute tactical missions given by commanders in the future unmanned battlefield. A large amount of research has been devoted to improving the autonomous decision-making ability of UAV in an interactive environment, where finding the optimal maneuvering decisionmaking policy became one of the key issues for enabling the intelligence of UAV. In this paper, we propose a maneuvering decision-making algorithm for autonomous air-delivery based on deep reinforcement learning under the guidance of expert experience. Specifically, we refine the guidance towards area and guidance towards specific point tasks for the air-delivery process based on the traditional air-to-surface fire control methods.Moreover, we construct the UAV maneuvering decision-making model based on Markov decision processes(MDPs). Specifically, we present a reward shaping method for the guidance towards area and guidance towards specific point tasks using potential-based function and expert-guided advice. The proposed algorithm could accelerate the convergence of the maneuvering decision-making policy and increase the stability of the policy in terms of the output during the later stage of training process. The effectiveness of the proposed maneuvering decision-making policy is illustrated by the curves of training parameters and extensive experimental results for testing the trained policy.

Multiple model PHD filter for tracking sharply maneuvering targets using recursive RANSAC based adaptive birth estimation

An algorithm to track multiple sharply maneuvering targets without prior knowledge about new target birth is proposed. These targets are capable of achieving sharp maneuvers within a short period of time, such as drones and agile missiles.The probability hypothesis density (PHD) filter, which propagates only the first-order statistical moment of the full target posterior, has been shown to be a computationally efficient solution to multitarget tracking problems. However, the standard PHD filter operates on the single dynamic model and requires prior information about target birth distribution, which leads to many limitations in terms of practical applications. In this paper,we introduce a nonzero mean, white noise turn rate dynamic model and generalize jump Markov systems to multitarget case to accommodate sharply maneuvering dynamics. Moreover, to adaptively estimate newborn targets’information, a measurement-driven method based on the recursive random sampling consensus (RANSAC) algorithm is proposed. Simulation results demonstrate that the proposed method achieves significant improvement in tracking multiple sharply maneuvering targets with adaptive birth estimation.

Trajectory and Correction Maneuver During the Transfer from Earth to Halo Orbit

This article addresses the design of the trajectory transferring from Earth to Halo orbit, and proposes a timing closed-loop strategy of correction maneuver during the transfer in the frame of circular restricted three body problem （CR3BP）. The relation between the Floquet multipliers and the magnitudes of Halo orbit is established, so that the suitable magnitude for the aerospace mission is chosen in terms of the stability of Halo orbit. The stable manifold is investigated from the Poincar6 mapping defined which is different from the previous researches, and six types of single-impulse transfer trajectories are attained from the geometry of the invariant manifolds. Based on one of the trajectories of indirect transfer which are ignored in the most of literatures, the stochastic control theory for imperfect information of the discrete linear stochastic system is applied to design the trajectory correction maneuver. The statistical dispersion analysis is performed by Monte-Carlo simulation,

Fish maneuver analysis system based on sequence images

The aim is to establish an automatic system to analyze the maneuver performance of fish. A high speed camera （1 000 frame/s） is employed to record fast-start maneuver. Three steps are taken to analyze the kinematics： first, the midline in the first image is partitioned into equal interval lengths and the coordinates of all inter segmental points are saved. Secondly, these points coordinates are searched in the next frame with the digital image correlation （DIC） method, then these points are fitted with a spline curve function. Repeat this step until all the midlines are figured out frame by frame. Finally, according to the variety of midlines, the kinematics of the fast-start is calculated. Using this system to test carp C-start, the duration is divided into two stages： stage 1 is defined as the formation of the C shape and stage 2 as the return flip of the tail followed with forward motion. By tracing the middle line, the kinematic parameters of turning rate, centre of mass （CM） turning rate, CM turning radius, etc. are obtained.

An Effective Multiple Model Least Squares Method in Tracking of a Maneuvering Target

A polynomial model, time origin shifting model(TOSM, is used to describe the trajectory of a moving target .Based on TOSM, a recursive laeast squares(RLS) algorithm with varied forgetting factor is derived for tracking of a non-maneuvering target. In order to apply this algorithm to maneuvering targets tracking ,a tracking signal is performed on-line to determine what kind of TOSm will be in effect to track a target with different dynamics. An effective multiple model least squares filtering and forecasting method dadpted to real tracking of a maneuvering target is formulated. The algorithm is computationally more effcient than Kalman filter and the percentage improvement from simulations show both of them are considerably alike to some extent.

An approach to improving maneuver performance of coning algorithm

Aiming to improve the maneuver performance of the strapdown inertial navigation attitude coning algorithm a new coning correction structure is constructed by adding a sample to the traditional compressed coning correction structure. According to the given definition of classical coning motion the residual coning correction error based on the new coning correction structure is derived. On the basis of the new structure the frequency Taylor series method is used for designing a coning correction structure coefficient and then a new coning algorithm is obtained.Two types of error models are defined for the coning algorithm performance evaluation under coning environments and maneuver environments respectively.Simulation results indicate that the maneuver accuracy of the new 4-sample coning algorithm is almost double that of the traditional compressed 4-sample coning algorithm. The new coning algorithm has an improved maneuver performance while maintaining coning performance compared to the traditional compressed coning algorithm.

Maneuvering target tracking using threshold interacting multiple model algorithm

To avoid missing track caused by the target maneuvers in automatic target tracking system, a new maneuvering target tracking technique called threshold interacting multiple model （TIMM） is proposed. This algorithm is based on the interacting multiple model （IMM） method and applies a threshold controller to improve tracking accuracy. It is also applicable to other advanced algorithms of IMM. In this research, we also compare the position and velocity root mean square （RMS） errors of TIMM and IMM algorithms with two different examples. Simulation results show that the TIMM algorithm is superior to the traditional IMM alzorithm in estimation accuracy.

Autonomous air combat maneuver decision using Bayesian inference and moving horizon optimization

To reach a higher level of autonomy for unmanned combat aerial vehicle(UCAV) in air combat games, this paper builds an autonomous maneuver decision system. In this system,the air combat game is regarded as a Markov process, so that the air combat situation can be effectively calculated via Bayesian inference theory. According to the situation assessment result,adaptively adjusts the weights of maneuver decision factors, which makes the objective function more reasonable and ensures the superiority situation for UCAV. As the air combat game is characterized by highly dynamic and a significant amount of uncertainty,to enhance the robustness and effectiveness of maneuver decision results, fuzzy logic is used to build the functions of four maneuver decision factors. Accuracy prediction of opponent aircraft is also essential to ensure making a good decision; therefore, a prediction model of opponent aircraft is designed based on the elementary maneuver method. Finally, the moving horizon optimization strategy is used to effectively model the whole air combat maneuver decision process. Various simulations are performed on typical scenario test and close-in dogfight, the results sufficiently demonstrate the superiority of the designed maneuver decision method.