Disparity-Based Generation of Line-of-Sight DSM for Image-Elevation Co-Registration to Support Building Detection in Off-Nadir VHR Satellite Images

The integration of optical images and elevation data is of great importance for 3D-assisted mapping applications. Very high resolution (VHR) satellite images provide ideal geo-data for mapping building information. Since buildings are inherently elevated objects, these images need to be co-registered with their elevation data for reliable building detection results. However, accurate co-registration is extremely difficult for off-nadir VHR images acquired over dense urban areas. Therefore, this research proposes a Disparity-Based Elevation Co-Registration (DECR) method for generating a Line-of-Sight Digital Surface Model (LoS-DSM) to efficiently achieve image-elevation data co-registration with pixel-level accuracy. Relative to the traditional photogrammetric approach, the RMSE value of the derived elevations is found to be less than 2 pixels. The applicability of the DECR method is demonstrated through elevation-based building detection (EBD) in a challenging dense urban area. The quality of the detection result is found to be more than 90%. Additionally, the detected objects were geo-referenced successfully to their correct ground locations to allow direct integration with other maps. In comparison to the original LoS-DSM development algorithm, the DECR algorithm is more efficient by reducing the calculation steps, preserving the co-registration accuracy, and minimizing the need for elevation normalization in dense urban areas.

Line-of-sight rates extraction of roll-pitch seeker under anti-infrared decoy state

In this paper,the method of extracting guidance information such as the line-of-sight(LOS)rates under the anti-infrared decoy state for the roll-pitch seeker is researched.Coordinate systems which are used to describe the angles transform are defined.The LOS angles reconstruction model of the roll-pitch seeker in inertial space is established.A Kalman filter model for extracting LOS rates of the roll-pitch seeker is proposed.In this model,the target performs constant acceleration(CA)model maneuvers.The error model of LOS rates extraction under infrared decoy state is established.Several existing methods of extracting LOS rates under anti-infrared decoy state are listed in this paper.Different from the existing methods,a novel method that uses extrapolated values of target accelerations as filter measurements is proposed to solve the guidance information extraction problem under the anti-infrared decoy state.Numerical simulations are conducted to verify the effectiveness of the proposed method under different target maneuvering models such as the CA model,the CA extended model and the singer model.The simulation results show that the proposed method of extracting guidance information such as LOS rates for the rollpitch seeker under the anti-infrared decoy state is effective.

Application of the sun line-of-sight vector in the optimal attitude estimation of deep-space probe

This paper proposed an optimal algorithm using the sun line-of-sight vector to improve the probe attitude estimation accuracy in deep-space mission.Firstly,the elaborate analysis of the attitude estimation error from vector observations was done to demonstrate that the geometric relation between the reference vectors is an important factor which influences the accuracy of attitude estimation.Then,with introduction of the sun line-of-sight vector,the attitude quaternion obtained from the star-sensor was converted into a pair of mutually perpendicular reference vectors perpendicular to the sun vector.The normalized weights were calculated according to the accuracy of the sensors.Furthermore,the optimal attitude estimation in the least squares sense was achieved with the quaternion estimation method.Finally,the results of simulation demonstrated the validity of the proposed optimal algorithm based on the practical data of the Deep Impact mission.

Flight Time Minimization of UAV for Cooperative Data Collection in Probabilistic LoS Channel

This paper investigates the data collection in an unmanned aerial vehicle(UAV)-aided Internet of Things(IoT) network, where a UAV is dispatched to collect data from ground sensors in a practical and accurate probabilistic line-of-sight(LoS) channel. Especially, access points(APs) are introduced to collect data from some sensors in the unlicensed band to improve data collection efficiency. We formulate a mixed-integer non-convex optimization problem to minimize the UAV flight time by jointly designing the UAV 3D trajectory and sensors’ scheduling, while ensuring the required amount of data can be collected under the limited UAV energy. To solve this nonconvex problem, we recast the objective problem into a tractable form. Then, the problem is further divided into several sub-problems to solve iteratively, and the successive convex approximation(SCA) scheme is applied to solve each non-convex subproblem. Finally,the bisection search is adopted to speed up the searching for the minimum UAV flight time. Simulation results verify that the UAV flight time can be shortened by the proposed method effectively.

Line-of-Sight MIMO for High Capacity Millimeter Wave Backhaul in FDD Systems

Wireless backhaul is considered to be the key part of the future wireless network with dense small cell traffic and high capacity demand.In this paper,we focus on the design of a high spectral efficiency line-of-sight(LoS)multiple-input multiple-output(MIMO)system for millimeter wave backhaul using dual-polarized frequency division duplex(FDD).High spectral efficiency is very challenging to achieve for the system due to various physical impairments such as phase noise(PHN),timing offset(TO)as well as the poor condition number of the LoS MIMO.In this paper,we propose a holistic solution containing TO compensation,PHN estimation,precoder/decorrelator optimization of the LoS MIMO for wireless backhaul,and the interleaving of each part.We show that the proposed solution has a robust performance with end-to-end spectral efficiency of 60 bit/s/Hz for 88 MIMO.

Finite-Time Sideslip Differentiator-Based LOS Guidance for Robust Path Following of Snake Robots

This paper presents a finite-time sideslip differentiator-based line-of-sight(LOS)guidance method for robust path following of snake robots.Firstly,finite-time stable sideslip differentiator and adaptive LOS guidance method are proposed to counteract sideslip drift caused by cross-track velocity.The proposed differentiator can accurately observe the cross-track error and sideslip angle for snake robots to avoid errors caused by calculating sideslip angle approximately.In our method,the designed piecewise auxiliary function guarantees the finite-time stability of position errors.Secondly,for the case of external disturbances and state constraints,a Barrier Lyapunov functionbased backstepping adaptive path following controller is presented to improve the robot’s robustness.The uniform ultimate boundedness of the closed-loop system is proved by analyzing stability.Additionally,a gait frequency adjustment-based virtual velocity control input is derived to achieve the exponential convergence of the tangential velocity.At last,the availability and superiority of this work are shown through simulation and experiment results.

Improved lazy theta algorithm based on octree map for path planning of UAV

This paper investigates the path planning method of unmanned aerial vehicle(UAV)in threedimensional map.Firstly,in order to keep a safe distance between UAV and obstacles,the obstacle grid in the map is expanded.By using the data structure of octree,the octree map is constructed,and the search nodes is significantly reduced.Then,the lazy theta*algorithm,including neighbor node search,line-of-sight algorithm and heuristics weight adjustment is improved.In the process of node search,UAV constraint conditions are considered to ensure the planned path is actually flyable.The redundant nodes are reduced by the line-of-sight algorithm through judging whether visible between two nodes.Heuristic weight adjustment strategy is employed to control the precision and speed of search.Finally,the simulation results show that the improved lazy theta*algorithm is suitable for path planning of UAV in complex environment with multi-constraints.The effectiveness and flight ability of the algorithm are verified by comparing experiments and real flight.

洋流干扰下无人船限制水域直线跟踪安全视距制导

The collision-free straight-line following of an unmanned surface vehicle(USV)moving in a constrained water region subject to stationary and moving obstacles is addressed in this paper.USV systems are normally subjected to surge velocity constraints,yaw rate constraints,and unknown ocean currents.Herein,a safety-certificated line-of-sight(LOS)guidance method is proposed to achieve a constrained straight-line following task.First,an antidisturbance LOS guidance law is designed based on the LOS guidance scheme and an extended state observer.Furthermore,collision avoidance with waterway boundaries and stationary/moving obstacles is encoded in control barrier functions,utilizing which the safety constraints are transformed into input constraints.Finally,safety-certificated guidance signals are obtained by solving a quadratic programming problem subject to input constraints.Using the proposed safety-certified LOS guidance method,the USV can accomplish a straight-line following task with guaranteed input-to-state safety.Simulation results substantiate the efficacy of the proposed safety-certificated LOS guidance method for the straight-line following of USVs moving in a constrained water region subject to unknown ocean currents.

无人艇自适应路径跟踪控制器的设计与验证

针对航行环境和船速变化下的无人艇路径跟踪控制问题,本文提出了一种基于变增益内模控制方法的无人艇自适应路径跟踪控制器。结合状态空间型船舶线性数学模型、差分GPS和电子罗经的数据实现对无人艇操纵响应模型的在线参数估计;建立基于变增益内模控制方法的无人艇艏向控制器,并根据计算出的无人艇操纵性指数在线调节控制器的参数;利用Line-of-Sight(LOS)制导算法设计并实现无人艇的自适应路径跟踪控制器。实船实验结果表明:在实际的航行环境中,该自适应路径跟踪控制器具有良好的控制性能。

Adaptive sliding-mode path following control system of the underactuated USV under the influence of ocean currents

The path-following control of the asymmetry underactuated unmanned surface vehicle(USV) under external disturbances such as unknown constant and irrational ocean currents is discussed, and an adaptive sliding-mode path-following control system is proposed, which comprises a path-variable updated law,a modified integral line-of-sight(ILOS) guidance law based on a time-varying lookahead distance and adaptive feedback linearizing controllers combined with sliding-mode technique. A more accurate USV model without the assumption of having diagonal inertia and damping matrices is first presented, aiming at improving the performance of the path-following control. Next, the coordinate transformation is adopted to decouple the sway dynamic from the rudder angle, and the path-following errors dynamics without non-singular problem are presented in the moving Frenet-Serret frame. Then, based on the cascaded theorem and the adaptive sliding-mode method, the adaptive control law of position errors and course error are designed, among which the lookahead distance and integral gain are all computed as different functions of cross-track error to estimate and compensate the sideslip angle caused by external disturbances adaptively. Finally, according to the Lyapunov and cascaded theorem, the control system proposed is proved to be uniform globally asymptotic stability(UGAS) and uniform semiglobal exponential stability(USGES) when the control objectives are all achieved. Simulation results illustrate the precision and high-quality performance of this new controller.

Inverse Optimal Control for Speed-varying Path Following of Marine Vessels with Actuator Dynamics

A controller which is locally optimal near the origin and globally inverse optimal for the nonlinear system is proposed for path following of over actuated marine crafts with actuator dynamics. The motivation is the existence of undesired signals sent to the actuators, which can result in bad behavior in path following. To attenuate the oscillation of the control signal and obtain smooth thrust outputs, the actuator dynamics are added into the ship maneuvering model. Instead of modifying the Line-of-Sight (LOS) guidance law, this proposed controller can easily adjust the vessel speed to minimize the large cross-track error caused by the high vessel speed when it is turning. Numerical simulations demonstrate the validity of this proposed controller.

The Influence of LOS Components on the Statistical Properties of the Capacity of Amplify-and-Forward Channels

Amplify-and-forward channels in cooperative networks provide a promising improvement in the network coverage and system throughput. Under line-of-sight (LOS) propagation conditions in such cooperative networks, the overall fading channel can be modeled by a double Rice process. In this article, we have stud-ied the statistical properties of the capacity of double Rice fading channels. We have derived the analytical expressions for the probability density function (PDF), cumulative distribution function (CDF), level- crossing rate (LCR), and average duration of fades (ADF) of the channel capacity. The obtained results are studied for different values of the amplitudes of the LOS components in the two links of double Rice fading channels. It has been observed that the statistics of the capacity of double Rice fading channels are quite dif-ferent from those of double Rayleigh and classical Rice fading channels. Moreover, the presence of an LOS component in any of the two links increases the mean channel capacity and the LCR of the channel capacity. The validity of the theoretical results is confirmed by simulations. The results presented in this article can be very useful for communication system designers to optimize the performance of cooperative networks in wireless communication systems.

CSI-based passive intrusion detection bound estimation in indoor NLoS scenario

Passive intrusion detection is important for many indoor safety applications.By utilizing widespread WiFi infrastructures,channel state information(CSI)based intrusion detection methods have attractive advantages such as low cost,non-line-of-sight(NLoS)support,and privacy protection.However,existing CSI-based methods lack in-depth and intensive analysis of intrusion detection bound.To the best of our knowledge,this is the first work that precisely characterizes and models CSI-based intrusion detection bound in typical indoor NLoS scenario.A bound is defined as an intruder’s farthest position from the transmitter during intrusion detection.To derive a model for the bound,we first derived an intrusion-disturbed NLoS channel model by analyzing the influence of human intrusion on the NLoS wireless channel.Subsequently,based on the channel model,we further derived an intrusion detection bound model.Based on the derived bound model,we proposed a practical system to estimate the real intrusion detection bound.Extensive experiments were conducted based on practical systems.The experimental and simulation results verified and demonstrated the effectiveness of the derived bound model.Our work not only reveals the fundamental performance limit of the basic intrusion detection method in an indoor NLoS scenario,but also provides a valuable reference for bound estimation for other fine-grained wireless sensing applications.

Multiple Robots Formation Manoeuvring and Collision Avoidance Strategy

This paper presents a multiple robots formation manoeuvring and its collision avoidance strategy. The direction priority sequential selection algorithm is employed to achieve the raw path, and a new algorithm is then proposed to calculate the turning-compliant waypoints supporting the multi-robot formation manoeuvre. The collision avoidance strategy based on the formation control is presented to translate the collision avoidance problem into the stability problem of the formation. The extension-decomposition-aggregation scheme is next applied to solve the formation control problem and subsequently achieve the collision avoidance during the formation manoeuvre. Simulation study finally shows that the collision avoidance problem can be conveniently solved if the stability of the constructed formation including unidentified objects can be satisfied.

Atmospheric Ducting Effect in Wireless Communications:Challenges and Opportunities

Atmospheric ducting has a significant impact on electromagnetic wave propagation.Radio signals that are trapped and guided by the atmospheric duct can travel a much longer distance over the horizon with lower attenuation since the signal power does not spread isotropically through the atmosphere.Atmospheric ducting brings both challenges and opportunities to wireless communications.On one hand,the signals propagating in the atmospheric duct may interfere with a receiver far away as remote co-channel interference.On the other hand,a point-to-point link can be established directly through the atmospheric duct to enable beyond line-of-sight communications.In this article,the formation of the atmospheric duct and its effects on radio wave propagation are first overviewed.Then solutions and standardization activities in the 3rd Generation Partnership Project(3GPP)to mitigate atmospheric duct induced remote interference are presented.Finally,the applications and design challenges of atmospheric duct enabled beyond line-of-sight communications are reviewed and future research directions are suggested.

Machine learning based altitude-dependent empirical LoS probability model for air-to-ground communications

Line-of-sight(LoS)probability prediction is critical to the performance optimization of wireless communication systems.However,it is challenging to predict the LoS probability of air-to-ground(A2G)communication scenarios,because the altitude of unmanned aerial vehicles(UAVs)or other aircraft varies from dozens of meters to several kilometers.This paper presents an altitude-dependent empirical LoS probability model for A2G scenarios.Before estimating the model parameters,we design a K-nearest neighbor(KNN)based strategy to classify LoS and non-LoS(NLoS)paths.Then,a two-layer back propagation neural network(BPNN)based parameter estimation method is developed to build the relationship between every model parameter and the UAV altitude.Simulation results show that the results obtained using our proposed model has good consistency with the ray tracing(RT)data,the measurement data,and the results obtained using the standard models.Our model can also provide wider applicable altitudes than other LoS probability models,and thus can be applied to different altitudes under various A2G scenarios.