卫星激光通信终端光跟踪检测的数理基础

卫星激光通信光束的传播在空间属于远场衍射，而在地面光学跟踪检验中属于近场衍射。采用菲涅耳衍射理论研究了远场衍射和近场衍射对于产生光学跟踪位置误差信号的本质上的差别并且分析了等效条件，证明了近场检验中采用卫星相对角度运动轨迹的光束扫描可以准确模拟远场相对运动，同时也得到了光斑特性和卫星抖动模拟的分析。澄清了卫星激光通信终端光学跟踪性能检验中的基本概念，具有实际指导意义。

空间激光跟瞄中指向驱动电机运动特性研究

设计了一种深空非合作目标的激光扫描、捕获、跟踪地面实验装置,通过模拟深空同轨道运动的两颗卫星跟瞄过程,在理论上计算了跟瞄装置中光束指向驱动电机的最小加速度和其在跟踪过程中的运动特性。理论分析与仿真结果表明,当卫星偏离光斑中心一定距离时,指向驱动电机先加速后减速,补偿这个偏心,重新捕获跟踪卫星;重新捕获到跟踪所需时间受电机加速度和望远镜探测精度以及探测器响应处理时间影响,其中探测器精度对重新捕获到跟踪所需时间影响较大,探测器响应处理时间要减小到最小;为了使从捕获到跟踪过程中卫星始终在扫描光斑范围内,经纬仪驱动电机的最小角加速度为25.5°/s2。

Millimeter Wave Amplitude Comparison Monopulse Using a Waveguide Rotman Lens

A 94 GHz waveguide Rotman lens is described which can be used to implement an amplitude comparison monopulse RADAR. In transmit mode, adjacent dual beam ports are excited with equal amplitude and phase to form a sum radiation pattern, and in receive mode, the outputs of the beam port pairs are combined using magic tees to provide a sum and a difference signal which can be used to calculate an angular error estimate for target acquisition and tracking. This approach provides an amplitude comparison monopulse system which can be scanned in azimuth and which has a low component count, with no requirement for phase shift circuitry in the array feed lines, making it suitable for mm-wave frequencies. A 12 input (beam ports), 12 output (array ports) lens is designed using CST Microwave Studio, and the predicted results are presented.

Desenvolvimento e testes de software de um receptor de GPS para uso espacial

Spacecraft move with high speeds and suffer abrupt changes in acceleration. So, an onboard GPS receiver could calculate navigation solutions if the Doppler effect is taken into consideration during the satellite signals acquisition and tracking. Thus, for the receiver subject to such dynamic cope these shifts in the frequency signal, resulting from this effect, it is imperative to adjust its acquisition bandwidth and increase its tracking loop to a higher order. This paper presents the changes in the GPS Orion s software, an open architecture receiver produced by GEC Plessey Semiconductors, nowadays Zarlink, in order to make it able to generate navigation fix for vehicle under high dynamics, especially Low Earth Orbit satellites. GPS Architect development system, sold by the same company, supported the modifications. Furthermore, it presents GPS Monitor Aerospace s characteristics, a computational tool developed for monitoring navigation fix calculated by the GPS receiver, through graphics. Although it was not possible to simulate the software modifications implemented in the receiver in high dynamics, it was observed that the receiver worked in stationary tests, verified also in the new interface. This work also presents the results of GPS Receiver for Aerospace Applications experiment, achieved with the receiver s participation in a suborbital mission, Operation Maracati 2, in December 2010, using a digital second order carrier tracking loop. Despite an incident moments before the launch have hindered the effective navigation of the receiver, it was observed that the experiment worked properly, acquiring new satellites and tracking them during the VSB-30 rocket flight.

Tracking people in 3D using position, size and shape

This paper presents a prototype tracking system for tracking people in enclosed indoor environments where there is a high rate of occlusions. The system uses a stereo camera for acquisition, and is capable of disambiguating occlusions using a combination of depth map analysis, a two step ellipse fitting people detection process, the use of motion models and Kalman filters and a novel fit metric, based on computationally simple object statistics. Testing shows that our fit metric outperforms commonly used position based metrics and histogram based metrics, resulting in more accurate tracking of people.

Daily organ tracking in intensity-modulated radiotherapy of prostate cancer using an electronic portal imaging device with a dose saving acquisition mode

BACKGROUND AND PURPOSE: Daily use of conventional electronic portal imaging devices (EPID) for organ tracking is limited due to the relatively high dose required for high quality image acquisition. We studied the use of a novel dose saving acquisition mode (RadMode) allowing to take images with one monitor unit per image in prostate cancer patients undergoing intensity-modulated radiotherapy (IMRT) and tracking of implanted fiducial gold markers. PATIENTS AND METHODS: Twenty five patients underwent implantation of three fiducial gold markers prior to the planning CT. Before each treatment of a course of 37 fractions, orthogonal localization images from the antero-posterior and from the lateral direction were acquired. Portal images of both the setup procedure and the five IMRT treatment beams were analyzed. RESULTS: On average, four localization images were needed for a correct patient setup, resulting in four monitor units extra dose per fraction. The mean extra dose delivered to the patient was thereby increased by 1.2%. The procedure was precise enough to reduce the mean displacements prior to treatment to < o =0.3 mm. CONCLUSIONS: The use of a new dose saving acquisition mode enables to perform daily EPID-based prostate tracking with a cumulative extra dose of below 1 Gy. This concept is efficiently used in IMRT-treated patients, where separation of setup beams from treatment beams is mandatory.

Person tracking using motion detection and optical flow

Person tracking systems to date have either relied on motion detection or optical flow as a basis for person detection and tracking. As yet, systems have not been developed that utilise both these techniques. We propose a person tracking system that uses both, made possible by a novel hybrid optical flow-motion detection technique that we have developed. This provides the system with two methods of person detection, helping to avoid missed detections and the need to predict position, which can lead to errors in tracking and mistakes when handling occlusion situations. Our results show that our system is able to track people accurately, with an average error less than four pixels, and that our system outperforms the current CAVIAR benchmark system.

Improved simultaneous computation of motion detection and optical flow for object tracking

Object tracking systems require accurate segmentation of the objects from the background for effective tracking. Motion segmentation or optical flow can be used to segment incoming images. Whilst optical flow allows multiple moving targets to be separated based on their individual velocities, optical flow techniques are prone to errors caused by changing lighting and occlusions, both common in a surveillance environment. Motion segmentation techniques are more robust to fluctuating lighting and occlusions, but don't provide information on the direction of the motion. In this paper we propose a combined motion segmentation/optical flow algorithm for use in object tracking. The proposed algorithm uses the motion segmentation results to inform the optical flow calculations and ensure that optical flow is only calculated in regions of motion, and improve the performance of the optical flow around the edge of moving objects. Optical flow is calculated at pixel resolution and tracking of flow vectors is employed to improve performance and detect discontinuities, which can indicate the location of overlaps between objects. The algorithm is evaluated by attempting to extract a moving target within the flow images, given expected horizontal and vertical movement (i.e. the algorithms intended use for object tracking). Results show that the proposed algorithm outperforms other widely used optical flow techniques for this surveillance application.

Fixed-wing attitude estimation using temporal tracking of the horizon and optical flow

In this paper, a method has been developed for estimating pitch angle, roll angle and aircraft body rates based on horizon detection and temporal tracking using a forward-looking camera, without assistance from other sensors. Using an image processing front-end, we select several lines in an image that may or may not correspond to the true horizon. The optical flow at each candidate line is calculated, which may be used to measure the body rates of the aircraft. Using an Extended Kalman Filter (EKF), the aircraft state is propagated using a motion model and a candidate horizon line is associated using a statistical test based on the optical flow measurements and the location of the horizon. Once associated, the selected horizon line, along with the associated optical flow, is used as a measurement to the EKF. To test the accuracy of the algorithm, two flights were conducted, one using a highly dynamic Uninhabited Airborne Vehicle (UAV) in clear flight conditions and the other in a human-piloted Cessna 172 in conditions where the horizon was partially obscured by terrain, haze and smoke. The UAV flight resulted in pitch and roll error standard deviations of 0.42◦ and 0.71◦ respectively when compared with a truth attitude source. The Cessna flight resulted in pitch and roll error standard deviations of 1.79◦ and 1.75◦ respectively. The benefits of selecting and tracking the horizon using a motion model and optical flow rather than naively relying on the image processing front-end is also demonstrated.

Distributed object tracking with robot and disjoint camera networks

We describe a novel two stage approach to object localization and tracking using a network of wireless cameras and a mobile robot. In the first stage, a robot travels through the camera network while updating its position in a global coordinate frame which it broadcasts to the cameras. The cameras use this information, along with image plane location of the robot, to compute a mapping from their image planes to the global coordinate frame. This is combined with an occupancy map generated by the robot during the mapping process to track the objects. We present results with a nine node indoor camera network to demonstrate that this approach is feasible and offers acceptable level of accuracy in terms of object locations.

Fat and thin adaptive HMM filters for vision based detection of moving targets

Computer vision is an attractive solution for uninhabited aerial vehicle (UAV) collision avoidance, due to the low weight, size and power requirements of hardware. A two-stage paradigm has emerged in the literature for detection and tracking of dim targets in images, comprising of spatial preprocessing, followed by temporal filtering. In this paper, we investigate a hidden Markov model (HMM) based temporal filtering approach. Specifically, we propose an adaptive HMM filter, in which the variance of model parameters is refined as the quality of the target estimate improves. Filters with high variance (fat filters) are used for target acquisition, and filters with low variance (thin filters) are used for target tracking. The adaptive filter is tested in simulation and with real data (video of a collision-course aircraft). Our test results demonstrate that our adaptive filtering approach has improved tracking performance, and provides an estimate of target heading not present in previous HMM filtering approaches.

Neurons Activated During Fear Memory Consolidation and Reconsolidation are Mapped to a Common and New Topography in the Lateral Amygdala

A key question in neuroscience is how memory is selectively allocated to neural networks in the brain. This question remains a significant research challenge, in both rodent models and humans alike, because of the inherent difficulty in tracking and deciphering large, highly dimensional neuronal ensembles that support memory (i.e., the engram). In a previous study we showed that consolidation of a new fear memory is allocated to a common topography of amygdala neurons. When a consolidated memory is retrieved, it may enter a labile state, requiring reconsolidation for it to persist. What is not known is whether the original spatial allocation of a consolidated memory changes during reconsolidation. Knowledge about the spatial allocation of a memory, during consolidation and reconsolidation, provides fundamental insight into its core physical structure (i.e., the engram). Using design-based stereology, we operationally define reconsolidation by showing a nearly identical quantity of neurons in the dorsolateral amygdala (LAd) that expressed a plasticity-related protein, phosphorylated mitogen-activated protein kinase, following both memory acquisition and retrieval. Next, we confirm that Pavlovian fear conditioning recruits a stable, topographically organized population of activated neurons in the LAd. When the stored fear memory was briefly reactivated in the presence of the relevant conditioned stimulus, a similar topography of activated neurons was uncovered. In addition, we found evidence for activated neurons allocated to new regions of the LAd. These findings provide the first insight into the spatial allocation of a fear engram in the LAd, during its consolidation and reconsolidation phase.

How small-sided and conditioned games enhance acquisition of movement and decision-making skills

This article summarizes research from an ecological dynamics program of work on team sports exemplifying how small-sided and conditioned games (SSCG) can enhance skill acquisition and decision-making processes during training. The data highlighted show how constraints of different SSCG can facilitate emergence of continuous interpersonal coordination tendencies during practice to benefit team game players.

Unmanned Aerial Vehicles (UAVs) and artificial intelligence revolutionizing wildlife monitoring and conservation

Surveying threatened and invasive species to obtain accurate population estimates is an important but challenging task that requires a considerable investment in time and resources. Estimates using existing ground-based monitoring techniques, such as camera traps and surveys performed on foot, are known to be resource intensive, potentially inaccurate and imprecise, and difficult to validate. Recent developments in unmanned aerial vehicles (UAV), artificial intelligence and miniaturized thermal imaging systems represent a new opportunity for wildlife experts to inexpensively survey relatively large areas. The system presented in this paper includes thermal image acquisition as well as a video processing pipeline to perform object detection, classification and tracking of wildlife in forest or open areas. The system is tested on thermal video data from ground based and test flight footage, and is found to be able to detect all the target wildlife located in the surveyed area. The system is flexible in that the user can readily define the types of objects to classify and the object characteristics that should be considered during classification.

Knowledge identification and acquisition in SMEs: Strategically emergent or just ad hoc

Researchers and practitioners have been preoccupied with identifying ways for larger organizations to acquire and manage knowledge, however far less research attention has been directed towards these same pursuits in small and medium-sized enterprises (SMEs). This paper examines how SMEs engage in knowledge identification and acquisition; in particular how they identify knowledge needs and source this knowledge to enhance their business. The research studied six SMEs in Australia and Denmark. Contrary to prevailing assumptions, the findings suggest that SMEs engage in identification and sourcing of critical knowledge, albeit often with less than formal processes. These organizations relied on business plans to direct knowledge activities and ensure balance between long-range planning and flexibility. The results address a lack of empirical evidence about SME approaches to knowledge identification and acquisition, and demonstrate that although SMEs may approach such activities in an informal way, they are nonetheless deliberate and strategic in their knowledge activities.