Efficient 2-D MUSIC algorithm for super-resolution moving target tracking based on an FMCW radar

Frequency modulated continuous wave(FMCW)radar is an advantageous sensor scheme for target estimation and environmental perception.However,existing algorithms based on discrete Fourier transform(DFT),multiple signal classification(MUSIC)and compressed sensing,etc.,cannot achieve both low complexity and high resolution simultaneously.This paper proposes an efficient 2-D MUSIC algorithm for super-resolution target estimation/tracking based on FMCW radar.Firstly,we enhance the efficiency of 2-D MUSIC azimuth-range spectrum estimation by incorporating 2-D DFT and multi-level resolution searching strategy.Secondly,we apply the gradient descent method to tightly integrate the spatial continuity of object motion into spectrum estimation when processing multi-epoch radar data,which improves the efficiency of continuous target tracking.These two approaches have improved the algorithm efficiency by nearly 2-4 orders of magnitude without losing accuracy and resolution.Simulation experiments are conducted to validate the effectiveness of the algorithm in both single-epoch estimation and multi-epoch tracking scenarios.

MOVING OBJECT TRACKING IN DYNAMIC IMAGE SEQUENCE BASED ON ESTIMATION OF MOTION VECTORS OF FEATURE POINTS

An improved estimation of motion vectors of feature points is proposed for tracking moving objects of dynamic image sequence. Feature points are firstly extracted by the improved minimum intensity change （MIC） algorithm. The matching points of these feature points are then determined by adaptive rood pattern searching. Based on the random sample consensus （RANSAC） method, the background motion is finally compensated by the parameters of an affine transform of the background motion. With reasonable morphological filtering, the moving objects are completely extracted from the background, and then tracked accurately. Experimental results show that the improved method is successful on the motion background compensation and offers great promise in tracking moving objects of the dynamic image sequence.

Path planning for moving target tracking by fixed-wing UAV

For the automatic tracking of unknown moving targets on the ground,most of the commonly used methods involve circling above the target.With such a tracking mode,there is a moving laser spot on the target,which will bring trouble for cooperative manned helicopters.In this paper,we propose a new way of tracking,where an unmanned aerial vehicle(UAV) circles on one side of the tracked target.A circular path algorithm is developed for monitoring the relative position between the UAV and the target considering the real-time range and the bearing angle.This can determine the center of the new circular path if the predicted range between the UAV and the target does not meet the monitoring requirements.A transition path algorithm is presented for planning the transition path between circular paths that constrain the turning radius of the UAV.The transition path algorithm can generate waypoints that meet the flight ability.In this paper,we analyze the entire method and detail the scope of applications.We formulate an observation angle as an evaluation index.A series of simulations and evaluation index comparisons verify the effectiveness of the proposed algorithms.

Redundant discrete wavelet transforms based moving object recognition and tracking

A method for moving object recognition and tracking in the intelligent traffic monitoring system is presented. For the shortcomings and deficiencies of the frame-subtraction method, a redundant discrete wavelet transform （RDWT） based moving object recognition algorithm is put forward, which directly detects moving objects in the redundant discrete wavelet transform domain. An improved adaptive mean-shift algorithm is used to track the moving object in the follow up frames. Experimental results show that the algorithm can effectively extract the moving object, even though the object is similar to the background, and the results are better than the traditional frame-subtraction method. The object tracking is accurate without the impact of changes in the size of the object. Therefore the algorithm has a certain practical value and prospect.

Application of Road Information in Ground Moving Target Tracking

A new algorithm is developed to achieve accurate state estimation in ground moving target tracking by means of using road information. It is an adaptive variable structure interacting multiple model estimator with dynamic models modification （DMM VS-IMM for short）. Firstly, road information is employed to modify the target dynamic models used by filter, including modification of state transition matrix and process noise. Secondly, road information is applied to update the model set of a VS-IMM estimator. Predicted state estimation and road information are used to locate the target in the road network on which the model set is updated and finally IMM filtering is implemented. As compared with traditional methods, the accuracy of state estimation is improved for target moving not only on a single road, but also through an intersection. Monte Carlo simulation demonstrates the efficiency and robustness of the proposed algorithm with moderate computational loads.

Vibration characteristics of frozen soil under moving track loads

Vibration due to moving traffic loads is an important factor which induces frozen soil damage; this paper analyzed these vibration characteristics of frozen soil foundation under track loads. Firstly, seismic observation array （SOA） technology was applied to monitor the three dimensional dynamic characteristics of frozen soil under movable track load in a per- mafrost region and seasonal frozen soil area. Secondly, a numerical simulation for the response of frozen soil under movable track load was performed based on finite element analysis （FEA）, The results show that dynamic characteristics of frozen soil in perpendicular and parallel direction of the track are obviously different. In the direction perpendicular to the track, the vertical acceleration amplitude had an abrupt increase in the 9-10 m from the track line. In the direction parallel to the track, the acceleration in vertical and horizontal direction had a quick attenuation compared to the other direction. Lastly, various parameters were analyzed for the purpose of controlling the dynamic response of frozen soil and the vibration attenuation in frozen soil layer.

Area Variation Based Color Snake Algorithm for Moving Object Tracking

A snake algorithm has been known that it has a strong point in extracting the exact contour of an object. But it is apt to be influenced by scattered edges around the control points. Since the shape of a moving object in 2D image changes a lot due to its rotation and translation in the 3D space, the conventional algorithm that takes into account slowly moving objects cannot provide an appropriate solution. To utilize the advantages of the snake algorithm while minimizing the drawbacks, this paper proposes the area variation based color snake algorithm for moving object tracking. The proposed algorithm includes a new energy term which is used for preserving the shape of an object between two consecutive images. The proposed one can also segment precisely interesting objects on complex image since it is based on color information. Experiment results show that the proposed algorithm is very effective in various environments.

AN ADAPTIVE MOVING TARGET TRACKING ALGORITHM FOR SMART ANTENNA SYSTEMS

In wireless communication environment, the time-varying channel and angular spreads caused by multipath fading and the mobility of Mobile Stations (MS) degrade the performance of the conventional Direction-Of-Arrival (DOA) tracking algorithms. On the other hand, although the DOA estimation methods based on the Maximum Likelihood (ML) principle have higher resolution than the beamforming and the subspace based methods, prohibitively heavy computation limits their practical applications. This letter first proposes a new suboptimal DOA estimation algorithm that combines the advantages of the lower complexity of subspace algorithm and the high accuracy of ML based algo- rithms, and then proposes a Kalman filtering based tracking algorithm to model the dynamic property of directional changes for mobile terminals in such a way that the association between the estimates made at different time points is maintained. At each stage during tracking process, the current suboptimal estimates of DOA are treated as measurements, predicted and updated via a Kalman state equation, hence adaptive tracking of moving MS can be carried out without the need to perform unduly heavy computations. Computer simulation results show that this proposed algorithm has better per- formance of DOA estimation and tracking of MS than the conventional ML or subspace based algo- rithms in terms of accuracy and robustness.

A NUMERICAL STUDY OF THE EFFECT OF TAIWAN ISLAND TERRAIN ON TYPHOON HAITANG (0505) TRACK

The track of Typhoon Haitang (0505), which passed through the Taiwan Island and landed again, has been successfully simulated by using the non-hydrostatic mesoscale atmospheric model MM5. Its structure is analyzed on the landing stage, and it is found that there exist good relationships between the typhoon abnormal moving track and its asymmetry structure. The effect of terrain of Taiwan Island on the typhoon Haitang, which made it rotate before landing and present a"V"type abnormal moving track in Taiwan straits, has also been simulated. Further analysis shows that the terrain of Taiwan Island not only directly affects the typhoon moving track, but also changes the typhoon track by affecting its asymmetric structure. Therefore, the typhoon asymmetric structure and the effect of terrain of Taiwan Island together results in the abnormal rotating track. The terrain of Taiwan Island tends to increase the SW-NE asymmetric structure of the typhoon and has different effect on SE-NW asymmetric structure during the landfall process of typhoon Haitang before entering and moving out of the Taiwan straits.

Dynamic Target Detection and Tracking Based on Quantum Illumination LIDAR

In the detection process of classic radars such as radar/lidar,the detection performance will be weakened due to the presence of background noise and loss.The quantum illumination protocol can use the spatial correlation between photon pairs to improve image quality and enhance radar detection performance,even in the presence of loss and noise.Based on this quantum illumination LIDAR,a theoretic scheme is developed for the detection and tracking of moving targets,and the trajectory of the object is analyzed.Illuminated by the quantum light source as Spontaneous Parametric Down-Conversion(SPDC),an opaque target can be identified from the background in the presence of strong noise.The static objects obtained by classical and quantum illumination are compared,respectively,and the advantages of quantum illumination are verified.The moving objects are taken at appropriate intervals to obtain the images of the moving objects,then the images are visualized as dynamic images,and the three-frame difference method is used to obtain the target contour.Finally,the image is performed by a series of processing on to obtain the trajectory of the target object.Several different motion situations are analyzed separately,and compared with the set object motion trajectory,which proves the effectiveness of the scheme.This scheme has potential practical application value.

An image-based decoupling controller of quadrotor for moving target tracking

Different from the traditional controller system for quadrotor tasks, the vision-based strategiesare more practical and powerful to execute more complex tasks, becoming more attractive toresearchers. In this paper, an image-feature-based controller with states extracted in imagesdirectly is proposed for the quadrotor to track a moving underground target, in which suitableimage features are defined and a coupling problem between position and attitude loop is solvedby a decoupling algorithm. Moreover, the external disturbances caused by visual noise, wind, orother problems are eliminated by a robust observer with low-pass filters. A Lyapunov-based stabilitymethod is presented to prove the convergent properties of the system. Finally, a simulationusing python3.6 with realistic images is established to verify that the system is stable and withhigh performance, the results of which show the data of unmanned aerial vehicle in movingtarget tracking.

A 38-Year Climatology of Explosive Cyclones over the Northern Hemisphere

Explosive cyclones(ECs)over two basins in the Northern Hemisphere(20°-90°N)from January 1979 to December2016 are investigated using ERA-Interim and Optimum Interpolation Sea Surface Temperature(OISST)data.The classical definition of an EC is modified considering not only the rapid drop of the central sea level pressure of the cyclone,but also the strong wind speed at the height of 10 m in which maximum wind speeds greater than 17.2 m s^-1are included.According to the locations of the northern Atlantic and northern Pacific,the whole Northern Hemisphere is divided into the"A region"(20°-90°N,90°W-90°E)and"P region"(20°-90°N,90°E-90°W).Over both the A and P regions,the climatological features of ECs,such as their spatial distribution,intensity,seasonal variation,interannual variation,and moving tracks,are documented.

Ground Moving Target Tracking with VS-IMM Using Mean Shift Unscented Particle Filter

In order to track ground moving target, a variable structure interacting multiple model （VS-IMM） using mean shift unscented particle filter （MS-UPF） is proposed in this paper. In model-conditioned filtering, sample particles obtained from the unscented particle filter are moved towards the maximal posterior density estimation of the target state through mean shift. On the basis of stop model in VS-IMM, hide model is proposed. Once the target is obscured by terrain, the prediction at prior time is used instead of the measurement at posterior time; in addition, the road model set used is not changed. A ground moving target indication （GMTI） radar is employed in three common simulation scenarios of ground target： entering or leaving a road, crossing a junction and no measurement. Two evaluation indexes, root mean square error （RMSE） and average normalized estimation error squared （ANEES）, are used. The results indicate that when the road on which the target moving changes, the tracking accuracy is effectively improved in the proposed algorithm. Moreover, track interruption could be avoided if the target is moving too slowly or masked by terrain.

CONTRAST ANALYSIS OF APRIL TYPHOONS LEO AND NEOGURI

The conventional observations data,NCAR/NCEP-2 reanalysis data,and NOAA outgoing longwave radiation data are used to investigate different characteristics of Leo and Neoguri,two April typhoons that ever made landfall on the continent of China over the past 60 years.The results showed that both Leo and Neoguri occurred during the La Nina events.Strong convective activity,weak vertical wind shear and upper-level divergence were in favor of the formation of these April typhoons.Leo originated from a monsoon depression and Neoguri evolved from an easterly wave.The meandering moving track of Leo attributed to strong northeast monsoon and a weak and changeable subtropical high;the steady moving track of Neoguri was governed by a strong and stable subtropical high.Leo and Neoguri had similar terrain conditions and intensities during landfall but were different in precipitation as water vapor transport and duration of kinetic uplifting resulted in apparent discrepancies between them.

Real-time dynamic system to path tracking and collision avoidance for redundant robotic arms

An dynamic system for real-time obstacle avoidance path planning of redundant robots is constructed in this paper. Firstly, the inter-frame difference method is used to identify the moving target and to calculate the target area, then on the basis of color features and gradient features extracted from the target area, the feature fusion Cam-Shift mean shift algorithm is used to track target, improving the robustness of the tracking algorithm. Secondly, a parallel two-channel target identification and location method based on binocular vision is proposed, updating the target＇s three-dimensional information in real time. Then, a dynamic collision-free path planning method is implemented： the safety rods are removed through the intersection test, and the minimum distance is derived directly by using the coordinate values of the target in the local coordinate system of the rod. On this basis, the obstacle avoidance gain and escape velocity related to the minimum distance is established, and obstacle avoidance path planning is implemented by using the zero space mapping matrix of redundant robot. Experiments are performed to Study the efficiency of the proposed system.

Online Approach for Spatio-Temporal Trajectory Data Reduction for Portable Devices

As location data are widely available to portable devices, trajectory tracking of moving objects has become an essential technology for most location-based services. To maintain such streaming data of location updates from mobile clients, conventional approaches such as time-based regular location updating and distance-based location updating have been used. However, these methods suffer from the large amount of data, redundant location updates, and large trajectory estimation errors due to the varying speed of moving objects. In this paper, we propose a simple but efficient online trajectory data reduction method for portable devices. To solve the problems of redundancy and large estimation errors, the proposed algorithm computes trajectory errors and finds a recent location update that should be sent to the server to satisfy the user requirements. We evaluate the proposed algorithm with real GPS trajectory data consisting of 17 201 trajectories. The intensive simulation results prove that the proposed algorithm always meets the given user requirements and exhibits a data reduction ratio of greater than 87% when the acceptable trajectory error is greater than or equal to 10 meters.