Improving cooperative tracking of an urban target with target motion model learning

2015 ◽  
Author(s):  
He Bai ◽  
Kevin Cook ◽  
Huili Yu ◽  
Kyle Ingersoll ◽  
Randy Beard ◽  
...  
Keyword(s):  
Target Motion ◽  
Motion Model ◽  
Model Learning ◽  
Cooperative Tracking

Research of Target Motion Model in Polar Coordinates Based on Dynamic Systems

2012 ◽  
Vol 496 ◽  
pp. 343-346
Author(s):  
Sheng Jie Zhao ◽  
Chuan Wang
Keyword(s):  
Monte Carlo ◽  
Dynamic Systems ◽  
Scientific Data ◽  
Target Motion ◽  
Polar Coordinates ◽  
Motion Model ◽  
Novel Target ◽  
Nonlinear Observation ◽  
Cv Model ◽  
Motion Mode

Abstract:Aiming at the nonlinear observation problem of target motion model in Cartesian coordinates, a novel target motion model in polar coordinates is proposed based on dynamic systems with analysis of scientific data materials. This paper has done about the target motion model in polar coordinates corresponding to CV model and CA respectively and simulated with Monte Carlo. The experimental results indicate that the target motion model is all agreed with targets motion in fact and can be used to describe the targets motion. Simulations show that state estimation of the KF based on the target motion mode with analysis of dynamic systems is efficient.

A new smoothing approach with diverse fixed-lags based on target motion model

2006 ◽  
Vol 3 (4) ◽  
pp. 425-430
Author(s):  
Chen Li ◽  
Chong-Zhao Han ◽  
Hong-Yan Zhu
Keyword(s):  
Target Motion ◽  
Motion Model

Target Tracking in the Presence of Intermittent Measurements via Motion Model Learning

2018 ◽  
Vol 34 (3) ◽  
pp. 805-819 ◽  
Author(s):  
Anup Parikh ◽  
Rushikesh Kamalapurkar ◽  
Warren E. Dixon
Keyword(s):  
Target Tracking ◽  
Motion Model ◽  
Model Learning ◽  
Intermittent Measurements

scholarly journals Strobing of Radar Marks for Trajectory Filtration in a Body-Fixed Frame

2019 ◽  
Vol 22 (5) ◽  
pp. 71-79
Author(s):  
Konstantin K. Vasiliev ◽  
Alexey V. Mattis ◽  
Oleg V. Saverkin
Keyword(s):  
Target Tracking ◽  
High Speed ◽  
The Body ◽  
Target Motion ◽  
Motion Model ◽  
New Approach ◽  
Fixed Frame ◽  
Speed Range ◽  
Radar Information ◽  
Analytical Expressions

Introduction. Modern air targets, particularly drones, are becoming less noticeable, while their manoeuvrability continues to improve. Trajectory processing algorithms have also been improved in order to provide for effective tracking of highly manoeuvring targets. The accuracy of filtering trajectory parameters is largely determined by the reliability of radar information. This has also required an enhanced role for strobe algorithms and the need to increase the effectiveness of strobe radar marks.Aim. To develop and investigate the efficiency of a trajectory strobe algorithm based on the target motion model in a high-speed coordinate system associated with the direction of the target motion and involving the formation of a strobe in the form of a truncated elliptical sector.Materials and methods. The study considered the target motion model in the body-fixed frame. This model was taken as the basis for new trajectory filtering algorithms based on Kalman filtering. Existing methods for strobing radar marks of the target were considered and a new approach based on filtering in the body-fixed frame proposed. The new algorithm assumes the formation of a strobe in the form of a truncated elliptical sector. This form corresponds to the most probable location of the marks of the tracked target. The effectiveness of the proposed solutions is confirmed by the results of mathematical modelling carried out using MATLAB.Results. The study produced analytical expressions for the motion model, recurrent filtering and strobe algorithm in the body-fixed frame. A comparative analysis of tracking effectiveness with the same volumes of the elliptical and proposed strobes was performed. It was established that the algorithm with strobe formation in the shape of a truncated elliptical sector provides for longer target tracking up to the time of the first loss of the mark for speed and highly manoeuvring targets, when compared to the elliptical strobe algorithm. In addition, the average duration of sector strobe tracking does not in practice depend on the initial speed of the target and provides greater accuracy for small measurement error values (less than 50 m) of the coordinates than in comparison with the elliptical one. Conclusion. The described results were achieved by the ability of the strobe in the body-fixed frame to adapt to the direction of motion and target manoeuvring, allowing high-quality target tracking within a larger speed range. Such strobe formation will also reduce the likelihood of skip-ping radar marks from the tracked target and will reduce the number of false marks belonging to other trajectories inside the strobe.

An Expert Data-Driven Air Combat Maneuver Model Learning Approach

2021 ◽  
Author(s):  
Su-Jeong Park ◽  
Soon-Seo Park ◽  
Han-Lim Choi ◽  
Kyeong-Soo An ◽  
Young-Gon Kim
Keyword(s):  
Data Driven ◽  
Learning Approach ◽  
Model Learning ◽  
Air Combat ◽  
Expert Data

PERBAIKAN KUALITAS PEMBELAJARAN DAN HASIL BELAJAR SISWA DENGAN MODEL LEARNING CYCLE COOPERATIVE 5 FASE DALAM PENGAJARAN KIMIA

2015 ◽  
Vol 7 (1) ◽  
pp. 29-38
Author(s):  
Esti Munafiah ◽  
Agus Basir Ali Akbar S
Keyword(s):  
Action Research ◽  
Learning Process ◽  
Mastery Learning ◽  
Learning Cycle ◽  
Model Learning ◽  
Classroom Action Research ◽  
Academic Year

The objective of this study is to see learning process using LCC model for chemistry course.  The study used classroom action research with three cycles each of which implements planning, acting, observing and reflection.  Subject of the study was 40 students of grade 8E of MTsN Blitar in the academic year 2009/2010. The findings of the study are as follows:  (1) Cycle I:  students participation 62.5%, mean score of worksheet 60, mean score of quiz 41,7, and mastery learning 3 students; (2) Cycle II: students participation 86.6%, mean score of worksheet 81, mean score of quiz 72.38, and mastery learning 26 students; (3) Cycle III:  students participation 100%, mean score of worksheet 89, mean score of quiz 72.44, and mastery learning 39 students.

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