Multisensor-Based Target-Tracking Algorithm with Out-of-Sequence-Measurements in Cluttered Environments.

When processing laser detection and ranging (LADAR) sensor data for scene interpretation, for example, for the purposes of feature extraction and/or data association in mobile robotics, most previous work models such devices as processing range data which follows a normal distribution. In this paper, it is demonstrated that commonly used LADARs suffer from incorrect range readings at changes in surface reflectivity and/or range discontinuities, which can have a much more detrimental effect on such algorithms than random noise. Most LADARs fall into two categories: coaxial and separated transmitter and receiver configurations. The latter offer the advantage that optical crosstalk is eliminated, since it can be guaranteed that all of the transmitted light leaves the LADAR and is not in any way partially reflected within it due to the beam-splitting techniques necessary in coaxial LADARs. However, they can introduce a significant disparity effect, as the reflected laser energy from the target can be partially occluded from the receiver. As well as demonstrating that false range values can result due to this occlusion effect from scanned LADARs, the main contribution of this paper is that the occurrence of these values can be reliably predicted by monitoring the received signal strength and a quantity we refer to as the “transceiver separation angle” of the rotating mirror. This paper will demonstrate that a correct understanding of such systematic errors is essential for the correct further processing of the data. A useful design criterion for the optical separation of the receiver and transmitter is also derived for noncoaxial LADARs, based on the minimum detectable signal amplitude of a LADAR and environmental edge constraints. By investigating the effects of various sensor and environmental parameters on occlusion, some advice is given on how to make use of noncoaxial LADARs correctly so as to avoid range errors when scanning environmental discontinuities. © 2005 Wiley Periodicals, Inc.

High resolution LADAR (laser detection and ranging) images of scenes containing human forms have been automatically segmented and simple algorithms have been developed for recognizing human forms in various positions in both cluttered and uncluttered scenes. Registration of LADAR and color CCD images is suggested as a method to enhance the ability to segment both types of images.

The performance of Geiger-mode LAser Detection and Ranging (LADAR) cameras is primarily defined by individual pixel attributes, such as dark count rate (DCR), photon detection efficiency (PDE), jitter, and crosstalk. However, for the expanding LADAR imaging applications, other factors, such as image uniformity, component tolerance, manufacturability, reliability, and operational features, have to be considered. Recently we have developed new 32×32 and 32×128 Read-Out Integrated Circuits (ROIC) for LADAR applications. With multiple filter and absorber structures, the 50-μm-pitch arrays demonstrate pixel crosstalk less than 100 ppm level, while maintaining a PDE greater than 40% at 4 V overbias. Besides the improved epitaxial and process uniformity of the APD arrays, the new ROICs implement a Non-uniform Bias (NUB) circuit providing 4-bit bias voltage tunability over a 2.5 V range to individually bias each pixel. All these features greatly increase the performance uniformity of the LADAR camera. Cameras based on these ROICs were integrated with a data acquisition system developed by Boeing DES. The 32×32 version has a range gate of up to 7 μs and can cover a range window of about 1 km with 14-bit and 0.5 ns timing resolution. The 32×128 camera can be operated at a frame rate of up to 20 kHz with 0.3 ns and 14-bit time resolution through a full CameraLink. The performance of the 32×32 LADAR camera has been demonstrated in a series of field tests on various vehicles.

A scannerless laser detection and ranging (LADAR) system is presently in development for applications at Sandia National Laboratories. This LADAR design eliminates the need for a mechanical laser beam scanner which is often the system component that limits the use of laser radars for many applications. Range to the target scene is determined in this approach by measuring the phase shift of the intensity modulation on the received optical return compared to the reference. The approach used in this LADAR is unique because the method used to detect this phase shift is an array of time integrating detectors that also records the image of the target scene. An analytical model is presented that describes the LADAR system performance. Applications of this LADAR system also are reviewed. They include terminal guidance of advanced conventional munitions, perimeter surveillance of secure facilities, mapping potholes/cracks in the U.S. highway system for improved maintenance scheduling, active collision avoidance of commercial/private vehicles, robotic vision integrated into advanced manufacturing concepts, and a novel airborne multi-sensor system containing LADAR, SAR, and LIDAR to locate and measure the thickness of ocean oil spills.© (1993) COPYRIGHT SPIE--The International Society for Optical Engineering. Downloading of the abstract is permitted for personal use only.

The assessment of ripeness is a major part of quality evaluation and depends on several factors such as soluble solid content (SSC), acidity and firmness. Most of the methods THAT measure these qualities are destructive. So it is essential to develop an efficient and nondestructive method for measuring internal attributes of fruit. The objective of this study was to investigate visible and near infrared (Vis/NIR) spectroscopy method for prediction of SSC and pH of kiwi fruit. Near infrared spectroscopy is a fast and a nondestructive analytical technique. One of the main advantages of NIR spectroscopy is that IT allows several constituents to be measured at the same time. Transmittance determinations in the 400-1000 nm range were carried out on samples which WERE separated randomly into two groups: first group for making calibration models and second one for quality predictions. Different data preprocessing and spectra treatments such as standard normal variate transformation (SNV), multiplicative scatter correction (MSC), median filter and derivative were used to eliminate noise. Then calibration models were developed by using principal component analysis (PCA) and partial least squares (PLS). Performance of different models was assessed in terms of root mean square errors of prediction (RMSEP) and correlation coefficient (r) between the predicted and measured parameter values. The correlation coefficient and root mean square errors of prediction to soluble solids content and pH were 0.93, 0.952 and 0.259˚Brix, 0.236, respectively. The results indicated the feasibility of Vis/NIR transmittance spectral analysis to predict SSC and pH of kiwi fruit in a nondestructive way. Keywords: internal quality evaluation of fruit, kiwi fruit, Visible/NIR spectroscopy and nondestructive measurements

The aim of the present research is to calculate the Relative Accuracy (R.A) and Root Mean Square Error (RMSE) for the location of Technical Institute, Mosul in Nineveh Governorate, Iraq. at the northern part of Mosul city by using surveying Instruments (GPS 1230 , Total Station 06 & Level NAK2), to calculate the coordinates and elevations of (16) Ground Control Points which covered the study area. The field data, remote sensing techniques and GIS software (Arc Map GIS10.3) are used to check the digital map of study area that helped the administrator to take the correct decision, determining positions of the future expansionist for buildings, roads, measuring lengths, areas and there coordinates, directions as well as the total costs estimation needed for any development from the final map. The gradient percentage between the highest and lowest points is calculated to be (9.954%). Relative accuracy for the based measured points (R.A) = 1:60000), and Root Mean Square error in Easting coordinates (RMSE) = ± 0.102m, in Northing coordinates (RMSN) = ± 0.096m, the Root Mean Square for the resultant (RMSR) = ± 0.099m, and Root Mean Square for Elevations ( RMSRL)= ± 0.005m. We Matched and correlated (10) measured points from study area with their graphic data positions on the aerial photo, determining the offsets for position and elevations as follows: (RMSE = ± 0.076m), (RMSN = ± 0.125m), (RMSR = ± 0.088m), and (Root Mean Square for Elevations = RMSRL= ± 0.045m). This research enable us after checking the results to produce new maps from Aerial photograph or Digital Image to use it for land uses and future extensions in whole study area.

Background and purposeThe study evaluated the differences in leaf positioning deviations by the log files of three advanced accelerators with two delivery techniques, and established specific assessment parameters of leaf positioning deviations for different types of accelerators.MethodsA total of 420 treatment plans with 5 consecutive treatment log files were collected from the Trilogy, TrueBeam and Halcyon accelerators. Millennium MLC was equipped on the Trilogy and TrueBeam accelerators. A jawless design and dual-layer MLC were adopted on the Halcyon accelerator. 70 IMRT and 70 VMAT plans were selected randomly on each accelerator. The treatment sites of all plans included head and neck, chest, breast, pelvis and other sites. The parsing tasks for 2100 log files were proceeded by SunCheck software from Sun Nuclear Corporation. The maximum leaf root mean square (RMS) errors, 95th percentile errors and percentages of different leaf positioning errors were statistically analyzed. The correlations between these evaluation parameters and accelerator performance parameters (maximum leaf speed, mean leaf speed, gantry and arc angle) were analyzed.ResultsThe average maximum leaf RMS errors of the Trilogy in the IMRT and VMAT plans were 0.44 ± 0.09 mm and 0.79 ± 0.07 mm, respectively, which were higher than the TrueBeam's 0.03 ± 0.01 mm, 0.03 ± 0.01 mm and the Halcyon's 0.05 ± 0.01 mm, 0.07 ± 0.01 mm. Similar data results were shown in the 95th percentile error. The maximum leaf RMS errors were strongly correlated with the 95th percentile errors (Pearson index > 0.5). The leaf positioning deviations in VMAT were higher than those in IMRT for all accelerators. In TrueBeam and Halcyon, leaf position errors above 1 mm were not found in IMRT and VMAT plans. The main influencing factor of leaf positioning deviation was the leaf speed, which has no strong correlation with gantry and arc angles.ConclusionsCompared with the quality assurance guidelines, the MLC positioning deviations tolerances of the three accelerators should be tightened. For both IMRT and VMAT techniques, the 95th percentile error and the maximum RMS error are suggested to be tightened to 1.5 and 1 mm respectively for the Trilogy accelerator. In TrueBeam and Halcyon accelerators, the 95th percentile error and maximum RMS error of 1 and 0.5 mm, respectively, are considered appropriate.

Application of ARIMA-RTS optimal smoothing algorithm in gas well production prediction

For the practical multisensor systems, the communication channels are often unreliable, especially in large, wireless, multi hop sensor networks. Thus, the communication delays often appear and produce random and unknown influence upon the performance of fusion estimators. Recently, data fusion for "Out-of-sequence" measurements (OOSM) attracts a mass of attentions gradually and some filters based on single sensor and multiple sensors have been reported. However, the existing methods for OOSM problem have several shortcomings, such as limited application for single sensor, bad real-time performance for the smooth property, low fusion estimate for neglecting the delayed information, and so forth. To tackle these problems, a novel batch fusion estimator based on the relative measurements for multisensor tracking systems with OOSM is proposed. The estimator is optimal in linear minimum mean square error (LMMSE). The paper also presents the suboptimal recursive form of the proposed estimator. Its principle is to establish the relative measurement equations of delayed observations to the next latest systemic state. Compared with some existingfusion methods for OOSM, the proposed method with arbitrary time delays has the best total performance. At the same time, algorithm analysis and computer simulation validate the advantages of the proposed fusion estimator.

Researchers at the Michigan Aerospace Corporation have developed accurate and robust 3-D algorithms for pose determination (position and orientation) of satellites as part of an on-going effort supporting autonomous rendezvous, docking and space situational awareness activities. 3-D range data from a LAser Detection And Ranging (LADAR) sensor is the expected input; however, the approach is unique in that the algorithms are designed to be sensor independent. Parameterized inputs allow the algorithms to be readily adapted to any sensor of opportunity. The cornerstone of our approach is the ability to simulate realistic range data that may be tailored to the specifications of any sensor. We were able to modify an open-source raytracing package to produce point cloud information from which high-fidelity simulated range images are generated. The assumptions made in our experimentation are as follows: 1) we have access to a CAD model of the target including information about the surface scattering and reflection characteristics of the components; 2) the satellite of interest may appear at any 3-D attitude; 3) the target is not necessarily rigid, but does have a limited number of configurations; and, 4) the target is not obscured in any way and is the only object in the field of view of the sensor. Our pose estimation approach then involves rendering a large number of exemplars (100k to 5M), extracting 2-D (silhouette- and projection-based) and 3-D (surface-based) features, and then training ensembles of decision trees to predict: a) the 4-D regions on a unit hypersphere into which the unit quaternion that represents the vehicle [Q X , Q Y , Q Z , Q W ] is pointing, and, b) the components of that unit quaternion. Results have been quite promising and the tools and simulation environment developed for this application may also be applied to non-cooperative spacecraft operations, Autonomous Hazard Detection and Avoidance (AHDA) for landing craft, terrain mapping, vehicle guidance, path planning and obstacle avoidance.

The Army Research Laboratory (ARL) Robotics Collaborative Technology Alliance (CTA) conducted an assessment and evaluation of multiple algorithms for real-time detection of pedestrians in Laser Detection and Ranging (LADAR) and video sensor data taken from a moving platform. The algorithms were developed by Robotics CTA members and then assessed in field experiments jointly conducted by the National Institute of Standards and Technology (NIST) and ARL. A robust, accurate and independent pedestrian tracking system was developed to provide ground truth. The ground truth was used to evaluate the CTA member algorithms for uncertainty and error in their results. A real-time display system was used to provide early detection of errors in data collection.

The NIST Construction Metrology and Automation Group is researching structural steel pick-andplace operations using a robotic crane coupled with sensor data distribution and construction component identification and tracking systems. This paper outlines new developments in this research including the addition of an automated gripper mechanism for RoboCrane and 4D-CAD sequenced multi-component placement. In addition, initial efforts to incorporate high-resolution scanning LADAR (Laser Detection and Ranging) data for world modeling and high frame-rate flash LADAR data for obstacle avoidance are discussed.

Methods for fitting circles and spheres to point sets are discussed. LADAR (LAser Detection And Ranging) scanners are capable of generating ‘point clouds’ containing the (x, y, z) coordinates of up to several millions of points reflecting the laser signals. In particular, coordinates collected off objects such as spheres may then be used to model these objects by fitting procedures. Fitting amounts to minimizing what is called here a “gauge function,” which quantifies the quality of a particular fit. This work analyzes and experimentally examines the impact of the choice of three such gauge functions. One of the resulting methods, termed here as “algebraic” fitting, formulates the minimization problem as a regression. The second, referred to as “geometric” fitting, minimizes the sum of squares of the Euclidean distances of the data points from the tentative sphere. This method, based on orthogonal distance minimization, is most highly regarded and widely used. The third method represents a novel way of fitting. It is based on the directions in which the individual data points have been acquired.

OPINION article Front. Physiol., 22 January 2014Sec. Integrative Physiology Volume 4 - 2013 | https://doi.org/10.3389/fphys.2013.00403

The Digital Imaging and Remote Sensing Image Generation (DIRSIG) model is a synthetic imagery generation model developed at the Center for Imaging Science (CIS) at the Rochester Institute of Technology (RIT). It is a quantitative first principle based model that calculates the sensor reaching radiance from the visible through to the long wave infrared on a spectral basis. DIRSIG generates a very accurate representation of what a sensor would see by modeling all the processes involved in the imaging chain. Currently, DIRSIG only models passive sources such as the sun and blackbody radiation due to the temperature of an object. Active systems have the benefit of the user being able to control the illumination source and tailor it for specific applications. Remote sensing Laser Detection and Ranging (LADAR) systems that utilize a laser as the active source have been in existence for over 30 years. Recent advances in tunable lasers and infrared detectors have allowed much more sophisticated and accurate work to be done, but a comprehensive spectral LADAR model has yet to be developed. In order to provide a tool to assist in LADAR development, this research incorporates a first principle based elastic LADAR model into DIRSIG. It calculates the irradiance onto the focal plane on a spectral basis for both the atmospheric and topographic return, based on the system characteristics and the assumed atmosphere. The geometrical form factor, a measure of the overlap between the sensor and receiver field-of-view, is carefully accounted for in both the monostatic and bistatic cases. The model includes the effect of multiple bounces from topographical targets. Currently, only direct detection systems will be modeled. Several sources of noise are extensively modeled, such as speckle from rough surfaces. Additionally, atmospheric turbulence effects including scintillation, beam effects, and image effects are accounted for. To allow for future growth, the model and coding are modular and anticipate the inclusion of advanced sensor modules and inelastic scattering.