Engineering Papers⌕ Search

SEARCH · Engineering Papers

Results for “target tracking”

Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.

At least 37 records · Page 2
All sourcesNASA NTRSDOE OSTI
NASA NTRSDate not supplied

Target Tracking with Distributed Sensing and Optimal Data Migration

The paper presents an Extended Kalman Filter based framework for airborne target tracking using adaptive information fusion from multi-modal multi-rate distributed sensors network. First, the tracking algorithm execution location is determined using an optimal data migration strategy, which also computes the associated delays for each sensor data to arrive at the computing location. Next, the fast (zero-delay) sensors information is dynamically fused in the filter correction procedure at the arrival instance of each valid sensor reading. Finally, the target estimation is updated based on the valid slow (delayed) data, which are grouped according to the delay-time steps before application of the Larsen's method. This approach is applied to the synthetic sensor data generated by means of the ground based radar and camera models for the simulated target flight in Reflection simulation environment.

Distributed sensing↗
NASA NTRSDate not supplied

Target Tracking with Distributed Sensing and Optimal Data Migration

The paper presents an Extended Kalman Filter based framework for airborne target tracking using adaptive information fusion from multi-modal multi-rate distributed sensors network. First, the tracking algorithm execution location is determined using an optimal data migration strategy, which also computes the associated delays for each sensor data to arrive at the computing location. Next, the fast (zero-delay) sensors information is dynamically fused in the filter correction procedure at the arrival instance of each valid sensor reading. Finally, the target estimation is updated based on the valid slow (delayed) data, which are grouped according to the delay-time steps before application of the Larsen's method. This approach is applied to the synthetic sensor data generated by means of the ground based radar and camera models for the simulated target flight in Reflection simulation environment.

Distributed sensing↗
NASA NTRS2006

Improvement in Visual Target Tracking for a Mobile Robot

In an improvement of the visual-target-tracking software used aboard a mobile robot (rover) of the type used to explore the Martian surface, an affine-matching algorithm has been replaced by a combination of a normalized- cross-correlation (NCC) algorithm and a template-image-magnification algorithm. Although neither NCC nor template-image magnification is new, the use of both of them to increase the degree of reliability with which features can be matched is new. In operation, a template image of a target is obtained from a previous rover position, then the magnification of the template image is based on the estimated change in the target distance from the previous rover position to the current rover position (see figure). For this purpose, the target distance at the previous rover position is determined by stereoscopy, while the target distance at the current rover position is calculated from an estimate of the current pose of the rover. The template image is then magnified by an amount corresponding to the estimated target distance to obtain a best template image to match with the image acquired at the current rover position.

Kim, Won↗
NASA NTRS1977

Prediction of pilot reserve attention capacity during air-to-air target tracking

Reserve attention capacity of a pilot was calculated using a pilot model that allocates exclusive model attention according to the ranking of task urgency functions whose variables are tracking error and error rate. The modeled task consisted of tracking a maneuvering target aircraft both vertically and horizontally, and when possible, performing a diverting side task which was simulated by the precise positioning of an electrical stylus and modeled as a task of constant urgency in the attention allocation algorithm. The urgency of the single loop vertical task is simply the magnitude of the vertical tracking error, while the multiloop horizontal task requires a nonlinear urgency measure of error and error rate terms. Comparison of model results with flight simulation data verified the computed model statistics of tracking error of both axes, lateral and longitudinal stick amplitude and rate, and side task episodes. Full data for the simulation tracking statistics as well as the explicit equations and structure of the urgency function multiaxis pilot model are presented.

Onstott, E. D.↗
NASA NTRS1991

Mid-course multi-target tracking using continuous representation

The thrust of this paper is to present a new approach to multi-target tracking for the mid-course stage of the Strategic Defense Initiative (SDI). This approach is based upon a continuum representation of a cluster of flying objects. We assume that the velocities of the flying objects can be embedded into a smooth velocity field. This assumption is based upon the impossibility of encounters in a high density cluster between the flying objects. Therefore, the problem is reduced to an identification of a moving continuum based upon consecutive time frame observations. In contradistinction to the previous approaches, here each target is considered as a center of a small continuous neighborhood subjected to a local-affine transformation, and therefore, the target trajectories do not mix. Obviously, their mixture in plane of sensor view is apparent. The approach is illustrated by an example.

Zak, Michail↗
NASA NTRS2005

Target Tracking, Approach, and Camera Handoff for Automated Instrument Placement

This paper describes the target designation, tracking, approach, and camera handoff technologies required to achieve accurate, single-command autonomous instrument placement for a planetary rover. It focuses on robust tracking integrated with obstacle avoidance during the approach phase, and image-based camera handoff to allow vision-based instrument placement. It also provides initial results from a complete system combining these technologies with rover base placement to maximize arm manipulability and image-based instrument placement.

target tracking↗
DOE OSTI2025

Content-aware foveated camera for multi-target tracking

Modern image sensors deliver substantial space-time bandwidth, yet indiscriminate acquisition often overwhelms memory, computation, and downstream perception. We present a content-aware, multi-foveated camera that dynamically reallocates sensing and magnification to multiple regions of interest (ROIs). A phase-only spatial light modulator (SLM) serves as a solid-state, inertia-free beam-steering and lens element, enabling per-frame field-of-view (FOV) reconfiguration and content-aware target tracking. By interleaving frames across foveae, our system preserves a wide-FOV situational context while refreshing each ROI at high rates, thereby reducing data volume without degrading task performance. We constructed a prototype employing a single-SLM, single-sensor architecture and demonstrated its application in real-time multi-object tracking with dynamic ROI maintenance across multiple viewpoints. The approach offers a general pathway to integrate detection, tracking, and segmentation algorithms in the acquisition loop, shifting workload from post hoc processing to intelligent capture.

Zang, Zihan [Univ. of California, Los Angeles, CA ↗
NASA NTRS2009

Visual Target Tracking in the Presence of Unknown Observer Motion

Much attention has been given to the visual tracking problem due to its obvious uses in military surveillance. However, visual tracking is complicated by the presence of motion of the observer in addition to the target motion, especially when the image changes caused by the observer motion are large compared to those caused by the target motion. Techniques for estimating the motion of the observer based on image registration techniques and Kalman filtering are presented and simulated. With the effects of the observer motion removed, an additional phase is implemented to track individual targets. This tracking method is demonstrated on an image stream from a buoy-mounted or periscope-mounted camera, where large inter-frame displacements are present due to the wave action on the camera. This system has been shown to be effective at tracking and predicting the global position of a planar vehicle (boat) being observed from a single, out-of-plane camera. Finally, the tracking system has been extended to a multi-target scenario.

image mosaic↗
NASA NTRS2013

Tool for Automated Retrieval of Generic Event Tracks (TARGET)

Methods have been developed to identify and track tornado-producing mesoscale convective systems (MCSs) automatically over the continental United States, in order to facilitate systematic studies of these powerful and often destructive events. Several data sources were combined to ensure event identification accuracy. Records of watches and warnings issued by National Weather Service (NWS), and tornado locations and tracks from the Tornado History Project (THP) were used to locate MCSs in high-resolution precipitation observations and GOES infrared (11-micron) Rapid Scan Operation (RSO) imagery. Thresholds are then applied to the latter two data sets to define MCS events and track their developments. MCSs produce a broad range of severe convective weather events that are significantly affecting the living conditions of the populations exposed to them. Understanding how MCSs grow and develop could help scientists improve their weather prediction models, and also provide tools to decision-makers whose goals are to protect populations and their property. Associating storm cells across frames of remotely sensed images poses a difficult problem because storms evolve, split, and merge. Any storm-tracking method should include the following processes: storm identification, storm tracking, and quantification of storm intensity and activity. The spatiotemporal coordinates of the tracks will enable researchers to obtain other coincident observations to conduct more thorough studies of these events. In addition to their tracked locations, their areal extents, precipitation intensities, and accumulations all as functions of their evolutions in time were also obtained and recorded for these events. All parameters so derived can be catalogued into a moving object database (MODB) for custom queries. The purpose of this software is to provide a generalized, cross-platform, pluggable tool for identifying events within a set of scientific data based upon specified criteria with the possibility of storing identified events into a searchable database. The core of the application uses an implementation of the connected component labeling (CCL) algorithm to identify areas of interest, then uses a set of criteria to establish spatial and temporal relationships between identified components. The CCL algorithm is used for identifying objects within images for computer vision. This application applies it to scientific data sets using arbitrary criteria. The most novel concept was applying a generalized CCL implementation to scientific data sets for establishing events both spatially and temporally. The combination of several existing concepts (pluggable components, generalized CCL algorithm, etc.) into one application is also novel. In addition, how the system is designed, i.e., its extensibility with pluggable components, and its configurability with a simple configuration file, is innovative. This allows the system to be applied to new scenarios with ease.

Clune, Thomas↗
NASA NTRS2004

Autonomous target tracking of small bodies during flybys

Spacecraft flybys of small solar system bodies provide important science return in the form of images of the target body taken around closest approach. In order to maximize the number of images taken of the target, an autonomous closed-loop tracking system has been developed to maintain lock on the target during the flyby. The system uses images to estimate the spacecrafts target-relative position and attitude, which is then used to point the camera. The system has been successfully used twice: the Deep Space 1 flyby of comet Borrelly and the Stardust flyby of asteroid Annefrank. This paper describes in detail the tracking algorithms and flight results.

Synnott, Stephen P.↗
NASA NTRS1988

Preliminary Orbit Determination System (PODS) for Tracking and Data Relay Satellite System (TDRSS)-tracked target Spacecraft using the homotopy continuation method

The Preliminary Orbit Determination System (PODS) provides early orbit determination capability in the Trajectory Computation and Orbital Products System (TCOPS) for a Tracking and Data Relay Satellite System (TDRSS)-tracked spacecraft. PODS computes a set of orbit states from an a priori estimate and six tracking measurements, consisting of any combination of TDRSS range and Doppler tracking measurements. PODS uses the homotopy continuation method to solve a set of nonlinear equations, and it is particularly effective for the case when the a priori estimate is not well known. Since range and Doppler measurements produce multiple states in PODS, a screening technique selects the desired state. PODS is executed in the TCOPS environment and can directly access all operational data sets. At the completion of the preliminary orbit determination, the PODS-generated state, along with additional tracking measurements, can be directly input to the differential correction (DC) process to generate an improved state. To validate the computational and operational capabilities of PODS, tests were performed using simulated TDRSS tracking measurements for the Cosmic Background Explorer (COBE) satellite and using real TDRSS measurements for the Earth Radiation Budget Satellite (ERBS) and the Solar Mesosphere Explorer (SME) spacecraft. The effects of various measurement combinations, varying arc lengths, and levels of degradation of the a priori state vector on the PODS solutions were considered.

Kirschner, S. M.↗
NASA NTRS2009

Target-Tracking Camera for a Metrology System

An analog electronic camera that is part of a metrology system measures the varying direction to a light-emitting diode that serves as a bright point target. In the original application for which the camera was developed, the metrological system is used to determine the varying relative positions of radiating elements of an airborne synthetic aperture-radar (SAR) antenna as the airplane flexes during flight; precise knowledge of the relative positions as a function of time is needed for processing SAR readings. It has been common metrology system practice to measure the varying direction to a bright target by use of an electronic camera of the charge-coupled-device or active-pixel-sensor type. A major disadvantage of this practice arises from the necessity of reading out and digitizing the outputs from a large number of pixels and processing the resulting digital values in a computer to determine the centroid of a target: Because of the time taken by the readout, digitization, and computation, the update rate is limited to tens of hertz. In contrast, the analog nature of the present camera makes it possible to achieve an update rate of hundreds of hertz, and no computer is needed to determine the centroid. The camera is based on a position-sensitive detector (PSD), which is a rectangular photodiode with output contacts at opposite ends. PSDs are usually used in triangulation for measuring small distances. PSDs are manufactured in both one- and two-dimensional versions. Because it is very difficult to calibrate two-dimensional PSDs accurately, the focal-plane sensors used in this camera are two orthogonally mounted one-dimensional PSDs.

Liebe, Carl↗
NASA NTRS1990

Real time visual tracking of targets in six dimensions

Six dimensional target information is produced by a target tracking vision system for use in real time target tracking by a robotic system. The vision system described in this paper produces three axes of position data and three axes of orientation data using a single camera which views a three dimensional target. The system performs target detection, target discrimination and determines the target position and orientation relative to the camera. As the target information is determined, it is communicated to a computer which is controlling the robot motion in real time. Details of the image processing algorithms and image processing hardware used in the vision system are discussed in the paper.

Walsh, Peter M.↗