Motion Parameters Of Objects Research Articles

The Physical Processes of the Errors Accumulation in Measurement Systems

Abstract Nowadays autonomous measurement systems are applied for the determination of the cinematic parameters of object motion. The principle of operation of such systems is based on the measurement of the object motion acceleration with the further integration of the accelerometer’s signal. These measurement systems are called inertial systems. Platform-less inertial systems are widely used for these purposes. Their specific property is an installation of the primary information sensors directly on the constructive elements of the object case. The inertial measurement systems have also a negative feature to accumulate constantly the errors of the system.

Substantiation of the neural network structure for determining an orbital object motion parameters based on results of its observations from a spacecraft

Substantiation of the neural network structure for determining an orbital object motion parameters based on results of its observations from a spacecraft

Experimental research on influence of wave environment on high-speed water entry load and trajectory characteristics

Wave environment is a common fact happened when objects enter water under real conditions, which changes the morphology of the free interface when entering water. However, the influence of wave environment on the flow when entering water and on the evolution of object motion parameters after entering water is not clear. In this research, a rocking plate wave maker is used to generate a wave environment in the test pool, and a truncated cone rotating body equipped with an internal test system is used as the test model. The compressed air cannon is used to provide launch power, and the launch control system uniformly controls the start timing process of the wave maker and the launcher. The wave maker and the launcher will control the relative position of the object's entry point and the wave surface in collaboration. Various condition tests were carried out, including enter in static water, different wave surface positions and different wave heights. Quantitative trajectory parameters including the acceleration, and attitude angle of the model in the water-entry process were obtained, and the evolution of the flow field was photographed. The experimental results show that under high-speed conditions, the influence of waves on the water-entry process is mainly reflected in the change of the water entry angle relative to the water surface at the water-entry moment. The wave surface encountering negative inclination can effectively reduce the impact load of water entry, but it is more likely to induce the extreme situation such as "jumping".

Research of the Possibility of Creating a Measuring System Based on a Modern Smartphone for Estimating the Parameters of Object Movement

When studying different fast-moving processes, high-speed video recording is now widely used. The main deterrent for its further distribution remains the high cost of the necessary equipment. Herewith modern mobile devices (including smartphones) are constantly improved, some models are supplied with video cameras with high recording speed - 1000 frames/s and higher. In the paper the possibility of creating a measuring system based on one of the modern smartphone models to analyze the parameters of object motion is studied. The block diagram of the system is given; a layout of such a system has been created. To verify the workability of the developed model of the system, a software and hardware facility was developed to imitate the motion of an object on the Arduino Uno platform with an engine and a carriage moving along the guides. Graphs of changing the coordinates and speed of the object obtained using the program Tracker 5.1.5 are shown. A theoretical estimate of the error in determining the speed of an object using the implemented model of the system is performed. In addition, the estimation of the range of object speeds that can be measured using the developed system, as well as the range of permissible object movements was performed. The results of the performed experiments prove the possibility of creating a measuring system on the basis of the considered model of the smartphone to assess the speed of moving small objects with certain limitations. At the same time, to create a full-fledged measuring system that does not require additional processing of the received resulting video image on a PC and is capable of calculating the necessary results immediately after the end of the measurement process, it is necessary to develop our own software, which is advisable to do using the existing free libraries.

Information Processing Systems in UAV Based on Bayesian Filtering in Conditions of Uncertainty

In this article, the author considers the possibility of applying modern IT technologies to implement information processing algorithms in UAV motion control system. Filtration of coordinates and motion parameters of objects under a priori uncertainty is carried out using nonlinear adaptive filters: Kalman and Bayesian filters. The author considers numerical methods for digital implementation of nonlinear filters based on the convolution of functions, the possibilities of neural networks and fuzzy logic for solving the problems of tracking UAV objects (or missiles), the math model of dynamics, the features of the practical implementation of state estimation algorithms in the frame of added additional degrees of freedom. The considered algorithms are oriented on solving the problems in real time using parallel and cloud computing.

DETECTING OBJECTS MOVING IN SPACE FROM A MOBILE VISION SYSTEM

Context. In the study, the task of identifying objects moving in space from a mobile system of technical vision is considered.The analysis of the modern methods of dynamic object identification from both stationary and moving platforms is conducted. Theneed to create a new method for the identification of dynamic objects with a mobile optical-electronic system, which is adaptive tochanging observation conditions, is identified. This is a relevant scientific and technical problem. The object of the study is the model of moving object detection from a mobile vision system.Objective. The objective of this article is the analysis of the modern methods of moving object identification and the creation ofa new method. The method must allow observation from a mobile vision system and must be able to adapt to changing observation conditions.Method. A method for identifying objects moving in space from a mobile vision system is proposed, which allows toautomatically detect moving objects, determine their three-dimensional coordinates with a given accuracy, and adapt to changingobservation conditions. This method is based on the developed mathematical model of stereoscopic determination of motionparameters of objects in space, which allows us to increase the detection accuracy.Results. The proposed method is implemented in software. An experiment confirming the adequacy of this mathematical modelwas conducted. As the result of the experiment, data on the movement of the object and the mobile coordinate system were obtained.Conclusions. The experiments have confirmed the performance of the proposed method and allow us to recommend it whenbuilding mobile automatic tracking and identification systems for objects. The method allows automatic isolation of the movingobjects, determining their three-dimensional coordinates, and adapting to changing observation conditions. Prospects for furtherresearch may be in the creation of hardware tools for the selection of moving objects, allowing to improve the accuracy of theselection.

Target Doppler Rate Estimation Based on the Complex Phase of STFT in Passive Forward Scattering Radar.

This article presents a novel approach to the estimation of motion parameters of objects in passive forward scattering radars (PFSR). In such systems, most frequency modulated signals which are used have parameters that depend on the geometry of a radar scene and an object’s motion. Worth noting is that in bistatic (or multistatic) radars forward scattering geometry is present thus in this case only Doppler measurements are available while the range measurement is unambiguous. In this article the modulation factor, also called the Doppler rate, was determined based on the chirp rate (equivalent Doppler rate) estimation concept in the time-frequency (TF) domain. This approach utilizes the idea of the complex phase of the short-time Fourier transform (STFT) and its modification known from the literature. Mathematical dependencies were implemented and verified and the simulation results were described. The accuracy of the considered estimators were also verified using the Cramer-Rao lower bound (CRLB) to which simulated data for the considered estimators was compared. The proposed method was validated using a real-life signal collected from a radar operating in PFSR geometry. The Doppler rate provided by a car crossing the baseline between the receiver and the GSM transmitter was estimated. Finally, the concept of using CR estimation, which in the case of PFSR can be understood as Doppler rate, was confirmed on the basis of both simulated and real-life data.

Detection of Moving Objects by a Passive Scanning System

The problem of detection and estimation of spatial coordinates of moving objects by a passive scanning system of vision is solved. Algebraic and algorithmic approaches to determining the spatial coordinates and parameters of object motion are proposed. These approaches differ by taking into account the object velocities in searching for conjugate vectors of directions to the objects. The algorithms developed on the basis of these approaches show that the approach with allowance for motion parameters offers significant advantages of higher accuracy of coordinate estimation and higher probability of detecting all objects.

Adaptive estimation of an object motion parameters based on the hybrid stochastic model

This paper examines the problem of estimating parameters of the motion of an object moving along a complex trajectory in the presence of incomplete noisy measurements. This problem is of current interest because of the importance of its practical applications. Examples of such applications are the tracking problems of moving technical devices in robotics, navigation, ground vehicles. We propose a solution to the problem of adaptive estimation of the motion parameters of an object based on the hybrid stochastic model, which is a set of discrete linear stochastic models corresponding to various pieces of the object’s trajectory. The linearity of the models allows us to apply the optimal Kalman filtering to calculate the estimates of the motion parameters of an object. To identify the current motion mode of an object at a known time moments, new algorithm based on the use of the Kalman filters bank and sequential ratio probability test is developed. Numerical experiments confirm the efficiency of the obtained results.

Bearings-Only Tracking: Observer Maneuver Recommendation

In the maritime environment, object motion analysis using bearings-only measurements in a two-dimensional plane is carried out. The observer usually performs S-maneuver on the line of sight for range observability. This traditional S-maneuver is not preferable always. So, in this research work, a procedure is tried out to understand the scenario online and recommend the maneuver accordingly. Object motion parameters are estimated based on one selected acceptance criteria. Online observer maneuver recommendations are carried out to obtain the solution fast. The algorithm is realized using Monte-Carlo simulation and evaluated against number of scenarios.

Algorithmic compensation of video image dynamic errors with measurement data about geometric and object motion parameters

Abstract This article considers the mathematical models and methods of identifying the video image dynamic errors. These movies contain information on measuring the geometric parameters and motion parameters of natural stone products and equipment used in their manufacture. The details of dynamic errors are required to develop the algorithmic procedures of their compensation and to improve the accuracy of measuring these geometrical and motion parameters of the measurement object.

Estimation of bulky object motion parameters by means of the least squares method

The article is dedicated to research of identification procedure efficiency of model parameterand a selection of optimal coefficients values that emerge during the launching and lifting ships. Solvingthe problems of operational control optimization of such shipbuilding equipment as a slipway ispresented

Investigation of position estimation accuracy of celestial objects on the CCD frames

High position estimat ion accuracy of objects is needed for better detection of celestial objects with nonzero apparent motion, and further clarif ication of the motion parameters of objects by a small number of measurements. However, the studies of the accuracy of currently used methods for position estimati on of objects at the moment ha ve not been carried out. The estimation accuracy of equatorial coordinates of thirty most productive observatories in the world was investigated in the paper. The analysis was conducted by comparing the estimates with their predicted values, obtained on the Minor Planet Center website. Mean values of residuals by right ascension and declination, estimates of the standard deviations of the position estimates of objects, the average module of the measurement residual were calculated for each observatory. The study has shown a significant advantage of observatories, which use CoLiTec software for processing the observation results. According to the average module of residuals and standard deviation in pixels, CoLiTec observatories-partners have taken a leading position among the small aperture telescopes. High measurement accuracy indexes were obtained using sub-pixel Gaussian model.

Estimation of parameters of object motion based on stationary quasi-autonomous direction finder

A method for parametric identification of an object motion model represented in terms of generalized polynomials is proposed. The method is based on a stationary direction finder that, in addition to its own angular measurements, obtains data about the slant range to the observed object.

A MULTISCALE PHASE FIELD METHOD FOR JOINT SEGMENTATION-RIGID REGISTRATION — APPLICATION TO MOTION ESTIMATION OF HUMAN KNEE JOINT

Image based registration of rigid objects has been frequently addressed in the literature to obtain an object's motion parameters. In this paper, a new approach of joint segmentation-rigid registration, within the variational framework of the phase field approximation of the Mumford-Shah's functional, is proposed. The defined functional consists of two Mumford-Shah equations, extracting the discontinuity set of the reference and target images due to a rigid spatial transformation. Multiscale minimization of the proposed functional after finite element discretization provided a sub-pixel, robust algorithm for edge extraction as well as edge based rigid registration. The implementation considerations of the proposed method, including memory usage, convergence rate and effects of parameters selection, was discussed and its efficacy was examined in a comprehensive set of synthetic, phantom and clinical experiments. It was found that the proposed joint segmentation-rigid registration method provides improved results, in comparison with the currently available methods which are often based on maximizing images similarities, especially when the reference and target images are of different qualities. A high registration accuracy was obtained when estimating the knee joint kinematics through MR images taken at different joint configurations. It was concluded that the proposed method can be effectively used in applications where 3D image registration of rigid objects is concerned, e.g. for estimation of the motion parameters of human joints.

Four-dimensional flash trajectory imaging using time-delay-modulated range-gated viewing

We present a four-dimensional flash trajectory imaging method to image object trajectories over time in three-dimensional space. In the method, time-delay-modulated range-gated viewing with multiple exposures is presented so that the time evolution of object trajectories free from background interference is directly given without complicated image processing and the motion parameters of objects can be estimated. The method is demonstrated by a ball oscillating as a pendulum.

モバイル映像メディアと画像符号化 修正ＨＳＶ表色系を用いた人物領域の特定法に基づく動画像の超低ビットレート符号化

An efficient video coding algorithm for coding the upper half of a human body is proposed. In the coding system, the facial area, which is a moving object in the image sequence, is extracted from both the sending and receiving sides without any control information. The candidate areas of the person are segmented using color information and the moving areas. The color information, which represents skin color, is extracted with a modified HSV color system. The moving areas are estimated using motion parameters of objects, which are utilized for constructing previous frames. The face is then extracted by merging the candidate areas based on hue elements of the modified HSV color system. The standard “Claire” and “Miss America” videos are used for the computer simulation, and facial areas are accurately extracted in all frames.

Tracking moving objects during low altitude flight

A computer-vision system to assist pilots during low-altitude flight has been developed in this research study. During this critical section of flight, a system that can detect various objects on the ground would be very useful both for enhancing the safety of navigation and for relieving pilots of a part of their workload in flight control. Such tasks can generally be automated by computer-vision-based methods, which provide the ability for object detection and tracking. This paper describes the algorithms developed for accomplishing such tasks. There are two main stages in the vision system. First, independently moving objects in the scene are detected and segmented from the background. Then, they are tracked from frame to frame, and their 3D motion parameters are recursively estimated with Kalman filtering techniques. Experiments using real-world image sequences have been carried out, and the results show that tracking moving objects is successful and the estimation of object's motion parameters are quite accurate.

Estimation of Object Motion Parameters from Noisy Images

An approach is presented for the estimation of object motion parameters based on a sequence of noisy images. The problem considered is that of a rigid body undergoing unknown rotational and translational motion. The measurement data consists of a sequence of noisy image coordinates of two or more object correspondence points. By modeling the object dynamics as a function of time, estimates of the model parameters (including motion parameters) can be extracted from the data using recursive and/or batch techniques. This permits a desired degree of smoothing to be achieved through the use of an arbitrarily large number of images. Some assumptions regarding object structure are presently made. Results are presented for a recursive estimation procedure: the case considered here is that of a sequence of one dimensional images of a two dimensional object. Thus, the object moves in one transverse dimension, and in depth, preserving the fundamental ambiguity of the central projection image model (loss of depth information). An iterated extended Kalman filter is used for the recursive solution. Noise levels of 5-10 percent of the object image size are used. Approximate Cramer-Rao lower bounds are derived for the model parameter estimates as a function of object trajectory and noise level. This approach may be of use in situations where it is difficult to resolve large numbers of object match points, but relatively long sequences of images (10 to 20 or more) are available.