In this paper, we introduce a compact 6 × 8 channel multiple-input multiple-output frequency-modulated continuous-wave radar system capable of determining the three-dimensional positions of targets despite utilizing a linear virtual array. The compact system, containing two cascaded radar transceiver ICs, has 48 virtual channels. We conduct a direction of arrival estimation with these virtual channels to determine the azimuth angle. To overcome the spatial limitation of the linear array, we use frequency-steered transmit antennas, which vary their main lobe direction during the frequency chirp, allowing the elevation angle to be determined by using a sliding window fast Fourier transform algorithm. In this study, we present the system’s concept along with the associated signal processing. By taking measurements in different scenarios, each with differently placed corner reflectors, we investigate the capability of the system to separate adjacent targets concerning range, azimuth, and elevation. These measurements are additionally employed to point out the design trade-offs inherent to the system.

This paper proposes an aerodynamic analysis of the shuttlecock and a novel method for predicting shuttlecock trajectory. First, we have established a shuttlecock track data set by an infrared-based binocular vision system. Then the unscented Kalman filter algorithm is designed to further filter the noise and visual recognition algorithm errors. Third, the radial basis function (RBF)-based track prediction model is designed. This method offers a concept to obtain the neural network model of different kinds of flying or moving objects. The experimental results show that the proposed method can predict the shuttlecock trajectory in real time at high accuracy and can be used for implementing the algorithm of return strategies in the near future.

Vision-based tracking of an object using perspective projection inherently results in non-linear measurement equations in the Cartesian coordinates. The underlying object kinematics can be modelled by a linear system. In this paper we introduce a measurement conversion technique that analytically transforms the non-linear measurement equations obtained from a stereo-vision system into a system of linear measurement equations. We then design a robust linear filter around the converted measurement system. The state estimation error of the proposed filter is bounded and we provide a rigorous theoretical analysis of this result. The performance of the robust filter developed in this paper is demonstrated via computer simulation and via practical experimentation using a robotic manipulator as a target. The proposed filter is shown to outperform the extended Kalman filter (EKF).

The ability of freely-flying honeybees to track moving targets was examined by training to collect a reward on a target, and then videotaping their approach to the target while it was in motion. Training experiments were carried out with several groups of bees, using various colors for the target and the background. Computer-aided frame-by-frame analysis of video recordings was used to plot the instantaneous positions of the target, as well as the position and orientation of the approaching bee in three dimensions. The results show that bees are perfectly capable of tracking moving targets and landing on them. When the distance of the target is greater than 15 cm, approaching bees correct for angular deviations of the target from the midline, both in the horizontal and in the vertical plane. In either plane, the input vaariables that are important to the tracking system seem to be (1) the angular bearing of the target with respect and (2) the angular velocity of the target with respect to the eye. The tracking control system tends to orient the bee such that the target is located frontally, at an angle of Ca. 35 deg below the bee's long axis. The chromatic properties of tracking behavior were investigated by employing combinations of colors for the target and background such that the boundary between the target and the background presented a contrast that was visible either only to the green-sensitive receptors of the bee's eye, or only to theblue-sensitive receptors. The results of these experiments suggest that, in controlling tracking, the measurement of the angular velocity of the target is derived almost exclusively from signals from the green-sensitive receptors, as is the case with previously studied movement-sensitive behavior. However, the measurement of the angular bearing of the target is derived from the blue-sensitive receptors as well as the green-sensitive noes. When the target is closer than Ca. 15 cm, approaching bees use translational maneuvers, in addition to rotational ones, to track the moving target. Translational target tracking appears to be driven primarily by signals from the green-sensitive receptors.

This paper describes real-time computer vision algorithms for detection, identification, and tracking of moving targets in video streams generated by a moving airborne platform. Moving platforms cause instabilities in image acquisition due to factors such as disturbances and the ego-motion of the camera that distorts the actual motion of the moving targets. When the camera is mounted on a moving observer, the entire scene (background and targets) appears to be moving and the actual motion of the targets must be separated from the background motion. The motion of the airborne platform is modeled as affine transformation and its parameters are estimated using corresponding feature sets in consecutive images. After motion is compensated, the platform is considered as stationary and moving targets are detected accordingly. A number of tracking algorithms including particle filters, mean-shift, and connected component were implemented and compared. A cascaded boosted classifier with Haar wavelet feature extraction for moving target classification was developed and integrated with the recognition system that uses joint-feature spatial distribution. The integrated smart video surveillance system has been successfully tested using the Vivid Datasets provided by the Air Force Research Laboratory. The experimental results show that system can operate in real time and successfully detect, track, and identify multiple targets in the presence of partial occlusion.

This paper deals with a method for robot navigation towards a moving goal. The goal maneuvers are not a priori known to the robot. Our method is based on the use of the kinematics equations of the robot and the goal combined with geometrical rules. First a kinematics model for the tracking problem is derived and two strategies are suggested for robot navigation, namely the velocity pursuit guidance law and the deviated pursuit guidance law. It turns out that in both cases, the robot's angular velocity is equal to the line of sight angle rate. Important properties of the navigation strategies are discussed and proven. In the presence of obstacles, two navigation modes are used: the tracking mode, which has a global aspect and the obstacle avoidance mode, which has a local aspect. In the obstacle avoidance mode, a polar diagram combining information about obstacles and directions corresponding to the pursuit is constructed. An extensive simulation study is carried out, where the efficiency of both strategies is illustrated for different scenarios.

An efficient calibration-free visual servoing method is presented. The nonlinear optimization problem is formulated with the residual term for tracking a target. The residual term is estimated based on the secant approximation method. The image Jacobian is estimated using the affine model of the end-effector feature. Some experimental results are presented for a moving target.

A scattering layer consisting mainly of krill (Meganyctiphanes norvegica) was studied with a submersible transducer, to assess the behaviour of individual organisms in situ by means of split-beam target tracking. Individuals were resolved and tracked, but a rapid increase in average swimming speeds with depth suggested that inaccuracies in the angular estimates affected the estimates. Attempts were made to smooth the tracks during post-processing. Smoothed speeds suggested that most (>78%) invertebrates swam at speeds below 12 cm s–1 (mode ~4 cm s–1), with components of speed larger in the horizontal plane than in the vertical.

The reaction of fish induced by a trawling vessel was measured using the Bergen Acoustic Buoy. It is a free-floating buoy with a split beam echo sounder system. Individual fish trajectories were obtained by target tracking methods, and average swimming velocities as a function of depth and time before and after passage of the vessel was calculated. A measure for the change in behaviour was applied, showing a significant response during and after propeller passage. The change in horizontal displacement speed is significant at all depths, while the change in vertical displacement velocity is significant at all but one layer of depth. The horizontal reaction seems to occur a bit later than the diving reaction. After the main response, a slightly higher mean horizontal displacement speed was observed for the deepest layers. This indicates a change in the fish state after being exposed to the vessel/gear.