Precision Munition Guidance and Moving Target Position Estimation

2015 ◽  
Author(s):  
Sreeja S
Keyword(s):  
Target Position ◽  
Position Estimation ◽  
Moving Target

scholarly journals Calibration Method of Array Errors for Wideband MIMO Imaging Radar Based on Multiple Prominent Targets

2021 ◽  
Vol 13 (15) ◽  
pp. 2997
Author(s):  
Zheng Zhao ◽  
Weiming Tian ◽  
Yunkai Deng ◽  
Cheng Hu ◽  
Tao Zeng
Keyword(s):  
Multiple Input Multiple Output ◽  
Estimation Method ◽  
Target Position ◽  
Position Estimation ◽  
Least Square ◽  
Antenna Structure ◽  
Imaging Radar ◽  
Position Errors ◽  
Calibration Methods ◽  
Array Errors

Wideband multiple-input-multiple-output (MIMO) imaging radar can achieve high-resolution imaging with a specific multi-antenna structure. However, its imaging performance is severely affected by the array errors, including the inter-channel errors and the position errors of all the transmitting and receiving elements (TEs/REs). Conventional calibration methods are suitable for the narrow-band signal model, and cannot separate the element position errors from the array errors. This paper proposes a method for estimating and compensating the array errors of wideband MIMO imaging radar based on multiple prominent targets. Firstly, a high-precision target position estimation method is proposed to acquire the prominent targets’ positions without other equipment. Secondly, the inter-channel amplitude and delay errors are estimated by solving an equation-constrained least square problem. After this, the element position errors are estimated with the genetic algorithm to eliminate the spatial-variant error phase. Finally, the feasibility and correctness of this method are validated with both simulated and experimental datasets.

Ground-Constrained Motion Target Tracking for Monocular Sequence Images

2018 ◽  
Vol 32 (12) ◽  
pp. 1850044 ◽  
Author(s):  
Ling Guo
Keyword(s):  
Background Subtraction ◽  
Target Position ◽  
Video Monitoring ◽  
Moving Target ◽  
Constrained Motion ◽  
Otsu Method ◽  
Test Platform ◽  
Monitoring Test ◽  
Nonlinear Compensation ◽  
Nonlinear Imaging

For the detection of a moving target position in video monitoring images, the existing locating tracking systems mainly adopt binocular or structured light stereoscopic technology, which has drawbacks such as system design complexity and slow detection speed. In light of these limitations, a tracking method for monocular sequence moving targets is presented, with the introduction of ground constraints into monocular visual monitoring; the principle and process of the method are introduced in detail in this paper. This method uses camera installation information and geometric imaging principles combined with nonlinear compensation to derive the calculation formula for the actual position of the ground moving target in monocular asymmetric nonlinear imaging. The footprint location of a walker is searched in the sequence imaging of a monitoring test platform that is built indoors. Because of the shadow of the walker in the image, the multi-threshold OTSU method based on test target background subtraction is used here to segment the images. The experimental results verify the effectiveness of the proposed method.

scholarly journals A Framework for Multiple Ground Target Finding and Inspection Using a Multirotor UAS

Sensors ◽  
2020 ◽  
Vol 20 (1) ◽  
pp. 272 ◽  
Author(s):  
Ajmal Hinas ◽  
Roshan Ragel ◽  
Jonathan Roberts ◽  
Felipe Gonzalez
Keyword(s):  
Target Detection ◽  
Low Cost ◽  
Target Position ◽  
Position Estimation ◽  
Quality Data ◽  
Unmanned Aerial Systems ◽  
Modular Software ◽  
Ground Target ◽  
High Level ◽  
Aerial Systems

Small unmanned aerial systems (UASs) now have advanced waypoint-based navigation capabilities, which enable them to collect surveillance, wildlife ecology and air quality data in new ways. The ability to remotely sense and find a set of targets and descend and hover close to each target for an action is desirable in many applications, including inspection, search and rescue and spot spraying in agriculture. This paper proposes a robust framework for vision-based ground target finding and action using the high-level decision-making approach of Observe, Orient, Decide and Act (OODA). The proposed framework was implemented as a modular software system using the robotic operating system (ROS). The framework can be effectively deployed in different applications where single or multiple target detection and action is needed. The accuracy and precision of camera-based target position estimation from a low-cost UAS is not adequate for the task due to errors and uncertainties in low-cost sensors, sensor drift and target detection errors. External disturbances such as wind also pose further challenges. The implemented framework was tested using two different test cases. Overall, the results show that the proposed framework is robust to localization and target detection errors and able to perform the task.

Regions of Interest Detection Algorithm Based on Improved Visual Attention Model

2014 ◽  
Vol 513-517 ◽  
pp. 3368-3371 ◽  
Author(s):  
Zhen Hui Xu ◽  
Jun Yang ◽  
Wan Jun Zhang ◽  
Zhen Jun Yang
Keyword(s):  
Visual Attention ◽  
Target Position ◽  
Detection Algorithm ◽  
Regions Of Interest ◽  
Moving Target ◽  
Visual Attention Model ◽  
Attention Model ◽  
New Thinking ◽  
Interest Detection ◽  
Improved Model

Regions of Interest (ROI) detection algorithm based on Visual Attention Model can rapidly focus the attention in the conspicuous target region, and extract the interested region. As to some complicated scenes, it is very difficult to detect the target accurately by using general target detecting method, but using Regions of Interest detection algorithm based on Itti Visual Attention Model can detect the target position very well. But pay attention to Itti Visual Attention Model, it utilizes the luminance, color and texture character of the target to detect the position of it. As little moving target, these characters of it are not obvious, so the detecting result is not satisfactory that utilizing Itti Visual Attention Model directly. According to the problem, this text proposes one Regions of Interest detection algorithm on the basis of improved Itti visual attention model by introducing movement character. The experiment shows that the improved model puts forward a new thinking of little moving target detection.

Tracking Compensation of a Moving Target for a Biped Robot Based on Vision Sensor

2010 ◽  
Vol 44-47 ◽  
pp. 788-793
Author(s):  
Yun De Shen ◽  
Dong Soo Cho ◽  
Chang Doo Kee ◽  
Zhen Zhe Li
Keyword(s):  
Rotation Angle ◽  
Biped Robot ◽  
Position Estimation ◽  
Moving Target ◽  
Vision Sensor ◽  
Matching Algorithm ◽  
Image Frame ◽  
Affine Transform ◽  
Search Area ◽  
Starting Point

In this paper, the visual tracking algorithm for a moving target is proposed for the biped robot of which camera movement is irregular. Hexagonal Matching Algorithm is used to measure the changes of size, location, and rotation angle for a moving object from its image frame. For enhancing the efficiency of the tracking, we can adaptively adjust the starting point and the size of search area from the image information obtained. Finally, by using Affine Transform and Kalman Filter, the position estimation of the moving target is refined against the swing of the camera. Experiments with 20-DOF biped robot using mono vision sensor are implemented to prove the reliability of the proposed method.

Sign in / Sign up

Export Citation Format

Share Document